Don’t Make Me Think!

So hi, and thank you for having me. When Spencer [Keralis] asked me to do this talk, I replied with the question I usually ask people who want me to do talks: “what kind of talk are you looking for?” And Spencer said a polemic might be good. Spencer, I love you, but I am not convinced of the wisdom of this idea. But no, I know, if I’m known for anything in the wide world it’s for polemics, so fine, go with the flow, right?

So let me kick this off with a possibly-polemical truth: I do not feel welcome here, among you, in this context. I do not feel that I belong at this conference at all, never mind up here at the podium! Now, Spencer, don’t panic; it’s got nothing to do with you, you’re fine. And it’s not this specific conference, either; Digital Frontiers actually feels a lot more hospitable to me than most digital-humanities conferences—well, any digital humanities conferences. Some of that is in the about statement on the Digital Frontiers home page: Digital Frontiers exists to “explore innovation and collaboration across disciplinary boundaries in the arena of public humanities and cultural memory.” Boundary-crossing, hey, I am all about that, ask anybody! I cross a lot of lines! Oh, wait, that’s not quite the same thing. Or maybe it is. Whatever.

But when I seriously got down to thinking about what I’d say today, I noticed that I was starting to feel discomfort at the whole thing. And the closer this date got, the worse my internal discomfort got, and in me, this kind of discomfort plays out as rumination and insomnia, always has—so you folks have no idea how glad I am to get this over with finally!

But here’s the thing. I’m pretty sure I am not the only person in this room feeling a little unwelcome, maybe intimidated, maybe scared. In fact, I can almost guarantee it. And again, I’m not trying to say anything bad about Digital Frontiers. It’s not about that. It’s about a whole collage of weirdness, in the academy generally and in the humanities and in librarianship, and since humanities faculty and academic librarians form the bulk of the digital humanities, there’s weirdness in DH too. And some weirdnesses that are really awful and destructive, all I personally can do is acknowledge them, because I am not the right person to talk about them. Racism and colonialism in digital humanities, just as one example? We don’t need any more middle-aged white women like me talking about that like we’re some kind of authority, right? I’m not an authority on that, of course not. That’s there, and it absolutely makes people feel unwelcome, and I’m sorry for that and I bring it up because I don’t want anything I say today to erase it. I’m not going to emphasize it today, though, not because I don’t think it’s important, but because I’m not a person who can say much that’s useful about it.

But some of these weirdnesses that make me personally feel uncomfortable? I can interrogate them, and I thought it might actually be helpful (and at least possibly amusing) to others who feel like me if I did. Because the academy generally sometimes acts like its own little hermetically-sealed self-contained world, and so does librarianship, and unless you’re steeped in them, they look absolutely bizarre from the outside! And sometimes even from the inside! So I’m going to try to explain why I don’t feel welcome here. I hope it helps.

As I lay awake at night ruminating (with the cat stomping all over my kidneys; he’s a great cat but he will do that), I kept imagining and reimagining this conversation between a couple of imaginary conference attendees, Serious Academic Types or Very Important Librarians, who are both rolling their eyes practically out of their heads. And the conversation these eyerolly people in my head keep having goes like this: they see my name in the conference program and one person says, “Oh, her,” with that eyeroll. And the other person says, “Why’d they invite her?” with a matching eyeroll. And the first person says, “She…” and there I just fill in the blank; it’s different every time this conversation unrolls in my head.

Now here’s a thing. A whole lot of people in this room just filled in that blank in their head. Whether they actually know me, or heard about me from other people, or just read my bio on the conference website, they filled in that blank. They instantly came up with a reason I do not belong here! So no wonder I don’t feel welcome, if it’s that trivial to come up with a reason I don’t belong. And it’s no surprise either that I’m not the only one not feeling welcome, because I’m not a special snowflake. Anything making me feel uncomfortable or unwelcome or unwanted is also making others feel that way, guaranteed. So if you have eyerolly people in your head too, let’s get together and talk about it.

Part of how this happens is that there’s just something in the way people think, in the academy and in librarianship, that’s ineluctably Calvinist, this habit of reflexively classifying other people into the Elect and the Damned. And unlike Calvin, it can’t be blamed on a deity or on pre-established fate—it’s coming from within, it’s everybody, all of us are implicated! Our treacherous evil little brains do their level best to exclude people! Am I immune to this? I only wish I were. I’m trying to be, but I don’t always make it either!

The academy doesn’t talk about this much. Neither does librarianship. Now, I do talk about it, but I can only talk about it as much as I do because I am one of the Damned, both in the academy and in librarianship. They seriously don’t want me any more! And there’s basically nothing I can do about my damnation—it’s fixed and it’s irrevocable—so I take advantage of the only useful privilege it confers, which is speaking some of the unspoken aloud.

So, first question. If we, we all of us, inside and outside the academy, inside and outside librarianship, don’t want this exclusionary Calvinism in our DH, what do we want? Here’s how I ended up answering that question for the eyerolly people in my head, so I could finally get some sleep: “Anyone curious enough to want to be here should feel welcome here.” This is what I really desperately want, and what I hope and believe everybody here also wants. Anyone, anyone at all, curious enough to want to be at a DH gathering in the first place, anyone like that should feel welcome at DH gatherings. Me included! I would like to feel welcome here! That would be great!

But I don’t yet. I’m totally still stuck on this imaginary conversation between the imaginary eyerolly people in my head. So let me try to guess how some folks in this room and outside it would fill in this blank, because I know that in reality some of them did, and as I guess, I’m going to enlarge the context a bit, to see how that blank-filling plays out in who does and doesn’t feel welcome in DH.

Here’s one. “Oh, her. Why’d they invite her? She is not a theoretician.” Now, when I was studying for Ph.D comprehensive exams in Hispanic philology way back in the day, the hot thing in Hispanic philology was this guy named Roger Wright, whose big thing was when we can call Spanish “Spanish,” as opposed to calling it some kind of Latin. I read his book three times to be sure I could follow and reproduce his dense, highly theory-driven argument, and when I was done reading, my reaction was who cares? Who cares about this? It is a stupid useless argument based purely on definitional hairsplitting that does not usefully expand our understanding of anything!

Oops. One is not supposed to say that about theory in the academy, not ever. One of the biggest insults floating around DH in the academy is that DH is “insufficiently theorized,” whatever that even means. So, is this talk I’m giving insufficiently theorized? You bet it is! Theory is not what I do, it’s not what I teach, and it is not the world I live in. The world I live in involves:

  • actively preserving analog and digital materials before entropy claims them
  • coming up with concrete actions in response to new open access and open data policies
  • navigating titanic changes in how libraries and archives describe what they collect, and
  • changing the way scholarly communication works so that it’s less broken.

Some of the stuff that I teach and do relies on theory, but it is not itself theory. I’m not waving this as a flag. I know a lot of people live in Theoryworld and I respect that; they’re not all Roger Wright. I live in a world of praxis, however, and I’m actually basically all right with that. So when my utter uselessness at theory means people don’t find me worth listening to, wow, I don’t even know where to go with that, except to remark that yes, this reaction feels amazingly unwelcoming to me.

But that reaction is minor, in the grand scheme of things. I’m guessing this one was about half the room, give or take: “Oh, her. Why’d they invite her? She doesn’t even have a Ph.D.” I mean, it barely takes three seconds on a search engine to find somebody with a Ph.D dissing librarians in public online. Am I right, librarians? I am so right; try it. Or just read comments on the Chronicle of Higher Education for a while. No, actually, don’t do that, don’t read comments at the Chronicle; it’s bad and you will feel bad.

But you can’t tell me this isn’t a thing in DH. I mean, DH is part of the academy, and this is absolutely a thing in the academy. As I said, I’m a Ph.D dropout. I didn’t even make it to comprehensive exams—Roger Wright just broke me—and when I dropped out finally, my own father the Ph.D anthropologist made a huge point of telling me how much of a thing this is! So, if anybody here is squirming right about now, I am not sorry, because this dismissiveness and bullyragging is not acceptable. There are a whole lot of people without Ph.Ds, librarians and students and IT professionals and others, interested in and actually doing digital-humanities work who deserve better.

One place this mode of thought that only values Ph.Ds and writes off everybody else hits DH really hard is what I call the Academic Library Space Wars. It’s like clockwork, right? Every month or so another story in the Chronicle or a retweet frenzy because another tiny branch humanities library is being merged into the main library at another university, and humanities faculty are up in arms about it.

First, this is incredibly insulting to professional librarians, who somehow never get mentioned, much less heard from, in Academic Library Space Wars. Usually (though admittedly not always) it’s us librarians making the closure decision, and faculty who protest that decision without even talking to their librarians about why it was made are undermining those librarians, consciously or not.

Second, you know what’s invariably—I mean, always—missing from these faculty protests? Any concern at all about library staff, that’s what. It’s always about the books. Now, I dig books, and I dig library spaces, but when I see these protests that don’t even include the word “librarian,” it tells me loud and clear that I am invisible to humanities faculty. They do not have my back as a librarian, much less a digitally-focused librarian. They will not defend me; they’ll only defend the books. Is that part of why I feel unwelcome here in DH? Oh, you bet it is; I’m not necessarily among friends and I know it. And don’t get smug, librarians, because faculty get away with this nonsense when we don’t stand up for one another and our decisions. And we do not stand up for one another when faculty attack us; we duck and cover and tell ourselves “oh, whew, at least they’re not mad at me.”

Third, libraries are not plentifully endowed with space or money or staff these days, so any space dedicated solely to books is space that can’t do anything else at all for DH. And any book-only space that is kept open despite low usage means a library staff complement that could be doing DH work but isn’t, because keeping a space open even if nobody’s using it takes work. So if you sense a kind of friction sometimes between librarians and faculty, you’re not imagining things; it’s real.

Another site of Ph.D-or-not friction, of course, is the DH Labor Wars: who actually gets DH jobs, especially in libraries. I won’t lie, I have a dog in this hunt. I teach library school, and some of my library-school students want to do DH work in libraries, or want other library jobs that DH skills will give them a leg up on. Of that group, some of them have humanities Ph.Ds and some don’t. It’s really unclear to me how I’m supposed to explain their options to them. Am I supposed to say “You can’t do library DH work if you don’t have a humanities Ph.D?” I don’t want to say that. I’m pretty sure it’s not true. I don’t even think that DH wants it to be true, though I could be wrong. But that sure is the message a lot of DH employment announcements are giving me. Ph.Ds only! MLSes need not apply! There are grant agencies like CLIR and ACLS who will fund Ph.Ds but not MLSes, for example.

Here’s where I plant my flag: I believe some of my students without Ph.Ds are legitimately competitive for library DH jobs, and excluding them solely on the basis of degree is unfair. I’m not even convinced it helps the Ph.Ds sometimes, because librarians aren’t stupid— librarians know what the score is; librarians know this is unfair; and librarians know that Ph.Ds do not automatically have the competencies that libraries need. If I’m wrong and my non-Ph.D students aren’t legitimately competitive, they just won’t get the jobs, and that seems fine to me. But if I’m right, that’s bad for DH; DH isn’t getting the best people because it’s excluding some. Moreover, as Miriam [Posner] alluded to yesterday, excluding MLSes a priori gives libraries excuses to be suspicious of Ph.Ds hired into library DH jobs, to treat them really badly, and to set them up to fail. As a sometime academic librarian, I wish we wouldn’t do that! It’s not those Ph.Ds’ fault that grant agencies are trying to sell out academic librarianship for a mess of pottage! I don’t like that either, I won’t lie, but librarians who take out that frustration on the Ph.Ds are bullies, and I don’t want to train people to enter a profession full of bullies.

It turns out that academic librarians have their own version of the you-don’t-have-a-Ph.D thing: “Oh, her. Why’d they invite her? She isn’t even a librarian.” And librarians do this to technologists and Ph.Ds who work in libraries, but they do it to other librarians too. This makes no rational sense whatever, so I feel like I have to explain it—it’s based partly on whether the work a librarian does is relatively new to libraries or not, partly on whether a librarian actually works in libraries. Since I gravitated to new-to-libraries work right out of library school, I’ve been getting this since practically the day I graduated. A whole lot of librarians have taken considerable pains to make me unwelcome in librarianship, and I am very much not alone in being that kind of target.

You know what? Cheers, those librarians won. I’m not a librarian—not in the sense that I don’t have the degree, because I do, but in the sense that I don’t work in a library and probably never will again, not because I don’t want to, but because I am one of librarianship’s Calvinist Damned: no library anywhere will take a chance on me. Jobs aside, I never know when that’s going to jump out and bite me. It could be anywhere, including here. I do know that a lot of really sharp, bright, skilled librarians and technologists and other DHers I know have fallen afoul of librarianship’s amazingly weird unwritten rules about what you can and can’t say, and about what is “acceptable” expertise and “acceptable” library work, and what is “acceptable” public exposure. If you leave libraries for that or any other reason, suddenly you’re not a librarian any more and you’re absolutely supposed to feel uncomfortable in librarian gatherings. This is another thing that just really bothers me and I hope that saying it out loud helps us stop it! Not even for me—I’m a lost cause—but for my students, some of whom have been badly hurt by it.

But here’s the real kicker, for librarians: “Oh, her. Why’d they invite her? She teaches library school.” That horrible woman teaches library school. Eyeroll! What business does she have talking to anyone about anything? This is just a librarian thing. If there’s anyone in this world that librarians hate more than library-school instructors, I do not know who it is! We are worthless! We are the living embodiment of fail! How am I supposed to help defend libraries’ and librarians’ value to DH when librarians constantly undercut me and my teaching work like this? A shred of retained credibility, that’s all I ask!

The Ph.Ds add to the weirdness. Oh, library school, that’s just professional school, it isn’t real grad school. Frankly, given my experience with so-called “real grad school,” I consider that a feature, not a bug. And oh, say the Ph.Ds, they let practitioners teach, people who don’t even have Ph.Ds; clearly library schools aren’t serious about graduate education.

I hear and read this stuff constantly; I cannot escape it, though I try. If you happen to follow me on Twitter, you might have seen one of the times I just boiled over about it, because I am trying so hard to be good at what I do, and to do good with what I do, and the absolutely constant stream of negging I get back, it just hurts. And I shouldn’t have boiled over on Twitter, and I know that, and these days I just mute tweeps who make me feel like boiling over so I don’t do it again. But this is so unwelcoming.

This is especially problematic because digital humanities has still not resolved its internal question of how DH professionals get praxis training. It just blows my mind, how library schools get left out of that discussion, because a lot of the stuff we teach, fun nerdy stuff like metadata, digital preservation, online digital libraries, XML, linked data, database design, project management, scholarly communication and copyright—all this is stuff DHers often need to learn. That’s just the stuff I personally teach; it’s not even everything on this slide, and it’s not even close to everything library schools have to offer DH! But it feels to me like DH hasn’t noticed that, much less welcomed it. I feel like I’ve been written off in favor of DH education reinventing wheels, and yes, that makes me feel unwelcome.

Here’s where I admit that I, I myself, have contributed to my own Calvinist damnation. How have I done that? Miriam nailed it yesterday: by teaching workshops. And I’m even going to go beyond Miriam to extend that to the two-day or one-week-bootcamp variety of workshop. I hereby declare that I’m done with that. I’m just done. When I let people think that a one-week bootcamp is enough to teach anybody, Ph.D or no Ph.D, the library-schoolish parts of DH praxis… well, one, that impression is just wrong, and two, it totally sells short the complexity and the perceived value of what I teach and the school I teach it in and the students I teach it to. If it only takes a week to learn, how important can it be? It takes seven to ten years to get a typical Ph.D! So weeklong workshops are practically begging people to disrespect and undermine me and my students and make us feel unwelcome. I can’t ethically do that. I love my students, and I owe them better than that. No more workshops, no more bootcamps—my checkbook is crying because they actually make me money, but forget about the money, I’m done. If people want me to teach them, they need to make more of a commitment than that: the kind of commitment my library-school students make. A week is not enough.

Ultimately, what all these imaginary conversations between the eyerolly people in my head boil down to is, whatever it is I am, I’m not a real… something. Not a real librarian, not a real humanist, not a real DHer, not a real professional—sometimes I get to wondering if I’m actually even a real person! Maybe I’m imaginary, I don’t even know any more! That probably makes me sound like a total conspiracy theorist, what with all the weird voices in my head, but I don’t believe anybody much is actually out to get me, and I know I can’t trust what goes on in my head in the middle of the night when the cat is tenderizing my kidneys.

So if all these very real, very real-world phenomena I’ve just talked about are not a conspiracy to belittle and dismiss me, what are they? I think it’s an uninterrogated thought pattern that repeats over and over and over again just like the eyerolly people in my head. And it’s a thought pattern that I absolutely believe that you, you people here, you who use the products of digital librarianship and the digital humanities, can help interrupt.

This is the thought pattern: Don’t Make Me Think. (This is the actual talk title; you were probably wondering when I’d get to it, right?) If web usability is your thing, you might have recognized the phrase already, because I stole it from my favorite web-usability book, Don’t Make Me Think by Steve Krug. The title is just a fabulous summation of good usability. When I’m just trying to find information, or buy something, or ask a friend a question, don’t make me think about how to do that! It should be obvious. Perfect guiding principle for usability in design… but it doesn’t work outside that context. It completely doesn’t work if “I don’t feel welcome here and neither do a fair few other people” is our problem. “Don’t make me think!” answer the eyerolly people in my head, and no, that doesn’t work. Don’t Make Me Think will not get us to this place we want to be, where anybody with curiosity feels welcome. It won’t help us fix the frictions I’ve laid out for you, much less fix the underlying cultural weirdnesses that lead to those frictions.

My sense is that this exact principle—don’t make me think!—guides much too much of the academy, much too much of librarianship, much too much of DH. Got a hard problem? Like fixing scholarly publishing so everybody everywhere can have access to scholarly work, or weighing credentials fairly in the DH labor market, or allocating library space and staff so digital projects get a fair chance at them? Talk to the hand, don’t make me think!

For example, “Don’t make me think about hard problems! Just let me pontificate about them!” This, I firmly believe, explains a lot about comments on the Chronicle of Higher Education. But it also explains way too much about faculty behavior in the Academic Library Space Wars, doesn’t it?

I don’t actually think it’s hard to make people stop and think when they’re just spouting off. Sometimes it just takes one question, like asking an outraged faculty member, “Did you talk to the librarians?” during the Library Space Wars. Seriously, everybody, say it with me, “Did you talk to the librarians?” Did you treat them as fellow professionals who don’t make arbitrary decisions? And librarians, when was the last time you talked to a library-school instructor? Not lectured, not dissed, not yelled at, not talked at, I mean talked to. Maybe, just maybe, that would be a productive thing to do?

“Don’t make me think that someone else might know more about something than I do. Much less that it might be an important thing.” I’m sure a lot of you in this room have felt this, maybe from Ph.Ds, maybe from librarians, maybe both. And it’s not cool, and I encourage you to stand up to it.

Where I get this is facultysplaining about open access to the scholarly literature. Good heavens. Faculty have shopped their dissertation to university presses and maybe done a few reviews, and check them out, they’re scholarly publishing experts. I used to mark up and typeset scholarly books and work on ebook content standards, I’ve been an author and editor and reviewer and six years an institutional repository librarian and run a journal-hosting service and watched events closely for a decade and written about them and talked about them and taught a course for three years about various book and journal economies, but guess who’s the expert on scholarly publishing and open access? It ain’t me!

I absolutely think this plays into why library schools don’t appear more often in DH education discussions. An august doctoral candidate might have to learn something from a mere totally untheorized librarian, so let’s all have the vapors! I don’t know how to fix this except to encourage us all not to just accept it. We all bring something useful to DH, every single one of us in this room—even me sometimes—and we all, even me, deserve to have that respected.

And sometimes it’s “Don’t make me think about this hard problem! Just let me go right on doing what I do because I’ve always done it.” Because that has to be all right! And anyway you aren’t the boss of me, you can’t make me. You can’t make me think, and you can’t make me change. This explains way too much about theory-theory-theory as well as coding-coding-coding, and it helps explain why nobody shows up to workshops. While I’m at it, this also explains way too much about library approaches to new service models and new collaborations. You know, I’ve learned not to reflexively refer faculty I meet at conferences who are interested in DH to their libraries, because I don’t know what response they’ll get from their librarians. It might be great, or it might absolutely be “don’t make me think.” And what on earth is that, librarians? Thinking is only for other people? Lifelong learning, which we talk about a lot as a central part of the library mission, is only for other people? Come on, we call ourselves information professionals, we’ve got to do better than this. It’s our example to set, right?

Or sometimes it’s “Don’t make me think! Make somebody else do that! Even better? If it’s somebody I don’t actually care about as a fellow professional, or worse, a fellow human being.” If it’s somebody I can force into supplying what Miriam called “hope labor” yesterday: no credit, no pay, no nothing. So if you’ve been on the wrong end of that, you are not alone.

A few years back I sat in on early DH discussions at an institution that will remain nameless to protect the guilty and also myself. During the initial faculty-only focus group, this idea came up of a group of people who were going to do all the work of bridging faculty theory with technologist and librarian praxis. These people would know it all, the theory and the praxis, and they’d mediate between people who sometimes have a hard time communicating across those boundaries. And the faculty just loved this idea, and they gleefully volunteered—not themselves, of course not; they volunteered their graduate students to do it.

Having been a grad student myself, I felt danger signs there, and it turned out that I was completely right. A week later, we had their grad students in for a focus group. And of course a lot of them were already doing that translation work, not exactly by choice, along with a giant wodge of the actual tech work. I don’t even need to tell you what those grad students said about how these same faculty treated them and compensated their work, do I? I didn’t think so, no.

Librarians, we do this too. It’s absolutely part of the Calvinist damnation thing for us, and also part of how we treat library school instructors. It also fuels hope labor in libraries and especially in archives. It fuels the staffing anti-pattern that both Miriam and I have talked and written about (and that we’ve even seen today, frankly), where the library or an academic department hires one person, usually a new MLS or a grant-funded Ph.D postdoc, as Digital Humanities Coordinator and then it dumps that person in a dusty corner with no authority and no budget and no support or community whatsoever, and then it proudly proclaims that now the library does DH! Well, no, whatever that library is doing, it is not DH. This conference shows that DH is in large part community, and one person stuck in a dusty corner is not community. This is not acceptable! I have been railing about it my whole career, and I’ll keep railing about it until it stops. I do believe that a a lot of times when this comes up, it comes from a “make somebody else think so I don’t have to” place.

So why is “Don’t Make Me Think!” a thing in DH, and what can we do about it? I really believe that this isn’t usually actual conscious evil, just unconsidered reflex. Librarians, faculty, me myself, everybody, we just do not think about it before it comes out of our mouths. And it’s that not-thinking, as much as the responses themselves, that causes a lot of the unwelcomeness that I, and maybe some of you, and certainly others like me feel in DH.

If we got into this mess by not thinking, we get out by thinking. So I’ll just say that I don’t know that I have all the answers here. I’m not even sure I’m always asking the right questions. So make me think! Seriously, make me! And think along with me! Because from the bottom of my heart, I don’t believe DH has to be this way, and I believe thinking, and making one another think, is what fixes it.

So I’m going to close with a few things I think we can all do to deal with this unspoken baggage that makes me and others like me feel unwelcome in DH. And they’re pretty small actions, which I like because in my way I’m a pretty small person—not physically, obviously. But seriously, I’m no good at making big things happen; I know this about myself because I’ve tried, and really, I’m just useless at it. Keeping it small, then…

Can we all, all of us, just stop the immediate talk-to-the-hand conversation-enders, the flat statements that don’t allow for discussion? “Open access will never work in the humanities.” That’s one. Wow, I’m not sure where to go with that. When somebody puts it that way, they’re making it clear that it doesn’t matter what I say, so I shut up and feel unwelcome. “Library school sucks.” Wow, I’m not sure where to go with that either. The slightly less blunt version in which Ph.D education is automatically and forever better than library school isn’t really any better, nor is some of the wagon-circling I see in librarianship about the MLS. We’re a mongrel profession, we always have been; I consider it a strength rather than a weakness, and it’s on us to negotiate it properly! “No DH without theory” is just as bad as “no DH without coding.” It’s more complicated than both of those, so why shut down the discussion of what we all have to contribute? “I can’t because tenure and promotion,” tenure-track folks. “I can’t because I have no time,” librarians. “I can’t because, I can’t because.” I get that a lot, and I know what it really means. It really means “I don’t want to talk to you, I don’t want to help you, I don’t want to know anything about you, I don’t even want to admit that what you do might be important, so go away.” And that’s profoundly unwelcoming.

One way to deal with this is to have a standard response that politely points to how hurtful that is and asks for a little conversational space. You’ve heard mine already, and you’re all welcome to steal it: mine is “Wow, I’m not sure where to go with that.” Say it with me: “Wow, I’m not sure where to go with that.”

There’s an even better way, though. Last week I was in a meeting where I nerded out briefly (I admit it, it was really bad of me) and a colleague who isn’t heavily into technology said, “I didn’t understand a single word you just said.” And if she’d stopped there, that would have been exactly the kind of conversation-ender I’m talking about, right? But she didn’t stop there. That’s the key. The next words out of her mouth were, “Could you back up and explain?” So I apologized, backed up, and explained. And that is how it’s done, folks. I love where I work with all my heart, and you just found out one reason why. We can all do what my colleague did. We can all reach across gaps in knowledge, from both directions, and teach each other, and learn from one another.

Another thing I think we can do is work together to do what I call “reducing the excuse space,” inside and outside the various communities we’re part of. Reduce the rhetorical space people think they have to make excuses about why they are special snowflakes who don’t have to think, or learn, or listen, or have some basic consideration for people who are not exactly like them. To be honest, I think the conversation after Miriam’s keynote yesterday about training-by-video is partly about that. We throw workshops that nobody comes to, but everybody still yells and screams about how they need training, so we put together an online video and say “ha, what’s your excuse now?”—and the thing is, they’ll still have one. So what do you do? I actually think the video strategy still has merit, because it’s an excuse-space reducer, and reducing the excuse space bit by bit really is useful, slowly and cumulatively over time.

I’m writing a book called Expanding Your Skills to be one way I’m personally reducing excuse spaces, because I just cannot endure that thing in librarianship where lifelong learning is only for other people any more. Some librarians put up a bazillion excuses for why they can’t learn things—things like DH skills!—and a lot of those excuses are bogus, and some of them are not bogus but are surmountable with some thought and effort. That’s what the book is about.

Now, you don’t have to write a book to reduce excuse spaces, thank goodness. All you have to do is not let people stand pat on excuses. Instead, sympathize and suggest. “I can’t because tenure and promotion.” Yes, tenure and promotion are rough, have you considered self-archiving or blogging to raise your professional profile? “I can’t because time.” Yes, time’s short, I find that a newsreader helps me keep current efficiently. It’s not even about whether they follow through, really. It’s about quietly making clear that threadbare excuses do not cut it with us. Sympathize and suggest. Because once we all strip ourselves and each other of the excuses, we’ll stop turning away people that those excuses devalue.

Another thing we can do that I think DH particularly is really good at is documenting and analyzing patterns, especially rhetorical patterns, speech patterns. If we apply this skill to some of the things I’ve talked about today, it should reduce some more excuse spaces, maybe even make some people think instead of falling back on their usual don’t-make-me-think behaviors.

Consider the Timeline of Incidents from the Geek Feminism wiki, because it’s a great example of what I mean. Before this existed, there was unbelievable amounts of “psh, you gals, you’re just making things up” about sexism in information technology and computer science and fandom cultures. While the sexism is emphatically not gone yet, the making-things-up excuse pretty much is gone, because the wiki has gathered a whacking lot of evidence in one place, which both enables analysis of, and to some extent forces recognition of, the problematic patterns. So, some homework for you all, just by way of example: go document and analyze the Rhetorical Absence of Librarians from the Library Space Wars as they’re fought in the higher-ed trade press and on Twitter and in blogs. This is absolutely a DH kind of thing, right? Go for it!

Because for all the shade I’ve been throwing this whole talk, here’s one more thing I believe: where there’s real thought and action about practical issues in the humanities, not to mention real thought and action about exclusionary patterns in the academy? It’s in DH. DHers are doing this work, here at Digital Frontiers and on Twitter and in blogs and in open-access scholarly venues. I think that’s hugely necessary, and I personally, from the weird kind of liminal position I’m in, I’m deeply grateful for it. So I’m turning everybody loose now to do more of it! Thank you.


Don’t Make Me Think: Introduction

This talk was given at the Digital Frontiers 2014 conference in Denton, Texas.

Since I graduated library school, no matter where I was or what I was doing I have felt like an outsider. Women were outsiders in library technology a decade ago, though matters are ameliorating somewhat. Institutional-repository managers have always been outsiders in academic librarianship. Now, of course, I’m teaching in a graduate department without holding a Ph.D.

I don’t like the demarcation game. That comes through perhaps louder than I meant it to in this talk.


Grab a bucket! It’s raining data!

Hi there. Thanks very much to Mark Leggott for inviting me here, and to all of you for lending me your ears for a time. You’ll have noticed that the title of this talk in the program notes is very formal and buttoned-down. ‘Representing and managing the data deluge.’ Well, I am not a formal and buttoned-down person, but when Mark approached me to speak here, I was actually scared to death to accept, and so I wrote this really terribly boring title. I’ve just up and changed it: the real title is ‘Grab a bucket—it’s raining data!”

To hear some folks tell it, it’s a golden age to be a digital librarian. Here we have an entire new form of scholarly publication—digital research data—and it’s ours for the asking! In times when we’re all worried about the future of libraries (and let’s face it, librarians, we are), this feels heaven-sent. Grab a bucket, it’s raining data, hallelujah!

It so happens that in some quarters, I am now styled the “Cassandra of Open Access.” Cassandra, for those not up on their Greek myth, was a Trojan prophetess who was cursed such that nobody believed what she said until it was too late. Being from Troy, which was of course completely doomed, most of her prophecies were fairly dire, too. “Hey, the Greeks are about to wheel a big wooden horse into your city so they can burn it down and kill everybody!” Not happy-making stuff we’re talking about.

Some people have mistaken my Cassandra-nature for an onus against open access generally and institutional repositories in particular. I’ve never had it in for open access! Who doesn’t like open access? It’s similar to what Cory [Doctorow] said yesterday, it’s hard to be against an unambiguous good like open access without sounding like a total jerk… which hasn’t stopped some publishers, of course. But I’ve been running institutional repositories for close to five years now, and the on-the-ground reality has been quite a bit… blurrier.

  • Conflicting, contradictory, and in some cases flatly impossible goals.
  • Minimal means, because of people who seem to have been reading the mythical “Frommer’s Institutional Repositories on $5 A Day.”
  • Asking for time, effort, and data from faculty without giving them any real service or any return on their time investment that made sense to them.
  • Cramming things into IRs that just didn’t fit with the very limited IR view of the digital universe, just because we hadn’t anywhere else to put them: our content didn’t fit in the container we had.
  • Completely ignoring faculty needs and desires.

I’m seeing some of the same thought and design processes happening now with regard to e-science, e-research, cyberinfrastructure, data curation—whatever you want to call it. This troubles me. So I can’t help but wonder if I’m becoming the Cassandra of Data Curation.

Optimistically, though, it’s early days yet. There’s no reason we have to make the same mistakes with data that we made with IRs. So, I don’t want anyone to think that I’m raising the problems I’m going to raise in this talk because I’m somehow against research data curation, or I think libraries shouldn’t get involved with it. I am all for research-data curation, and I believe very strongly that libraries need to get involved. I just think we should know what we’re getting ourselves into, and if that means I’m a little Cassandraic, well, so be it.

I will focus this talk on the fit between content and container, though I may touch on other things. I’ll examine some of the qualities of typical research data, then talk about digital libraries and IRs, looking hard at some of the impedance mismatches we’re liable to run into, and then I will strategize a little bit about how to make ourselves and our systems better now, before we run headlong into another mess. The lens I’m going to be looking through is a human lens, not so much a technological lens. This is not just a technology problem, I can’t say that loudly enough.

What do we know about data?

There’s a lot of it. I’ll just reiterate something we heard yesterday: Even if we admit that the Large Hadron Collider types are probably going to take care of themselves—and this isn’t something I necessarily admit; I know huge, well-funded projects that are making huge messes with their data—even if we admit that, we’re still looking at an incredible flood of stuff.

Have we got big enough buckets? I don’t know. At this juncture I feel it incumbent upon me to say the word “cloud.” Cloud. There. I have said it. I now feel no need at all to say it again. Look, I understand that storage and networking are problems that have to be solved before we can do anything else. Just—to me, it’s necessary but not sufficient, even though it seems to be getting all the attention right now. So I’m going to move on from storage size to characteristics of research data that I’m more interested in.

Data exist to be interacted with.

One thing I think we need to keep in mind about data is that they are not an end in themselves. We don’t keep data just to keep data; we do it because researchers can pick up shovels and dig around in the sands and build knowledge like sand castles! Data are there to do things with. To be examined, cleaned up, verified, refuted, corrected, number-crunched, mashed up with other data, graphed, charted, visualized… and if we treat them as though they were unchangeable museum objects—look but don’t touch, like books chained to a medieval lectern—we are actually getting in the way of making new knowledge. If nobody can do things with data, there is no point in keeping it all! That’s what CC0 is about, as we heard in a Q&A session yesterday: removing legal barriers to messing about with data. We, we librarians, need to remove technical barriers to messing about with data.

What’s more, different kinds of data have different affordances. You don’t use a plastic sand-shovel to dig a rock quarry, just the way you don’t use a backhoe to build a sand castle. The way a sociologist interacts with census data is just wildly different from the way a medical researcher interacts with MRI data. The data buckets we build will have to internalize and respect those affordances, or at the very least allow researchers to build tools on top that respect those affordances.

Data are wildly diverse in nature

… as are data’s technical environments. In other words, data are diverse, so the buckets we put them in will need to be different shapes and colors in order to respect that diversity.

Now, differences in data can sometimes be skin-deep. The difference between a digital image of a sculpture and a digital image of a physics field station in Antarctica is in some ways not much for our purposes, however different our researchers may think they are. But sometimes the differences really do matter. You can’t treat a book in TEI markup the same as a book of page-scanned images; you will be doing violence to readers of one or the other. A microscopy researcher on my campus does cell sections digitally; you can train a microscope to focus from the top of the cell all the way through and down, and then you can create a 3D cell image to play with. It’s really cool! But a system such as DSpace that treats each section image as a wholly separate and unrelated thing is making it impossible to get any knowledge out of those data.

Think for a moment about a single bucket that works for the TEI book, the book of page scans, the images of the Antarctic field station, and the microscopy data, and you’re starting to realize the scope of the data-diversity problem.

Again, we don’t control the technical environments our researchers are using to generate data. Some of those environments are proprietary, and Mike Rylander talked yesterday about why that’s a dangerous, dangerous problem. But even leaving that aside, if we’re really, really lucky, we might have a chance to make recommendations to researchers about their data. For the most part, though, we are the ones who will have to adapt to whatever they’re doing.

Data are already out there.

Why is that? It’s because we’re not creating all the digital research data out there; the researchers are. And they’ve created it in huge volumes already. So I’m really interested when Dan Chudnov says that the Library of Congress is working to capture data at world-scale and web-scale, because I want them to teach me how to do that.

So, researchers. They’re not thinking long-term about the data they’ve created. They’re not thinking past the expiration of their next grant! That means we have to. We’re the only people with a long-term time horizon. Furthermore, they’re not likely to come to us; for the most part they can’t even imagine that we can help. The inescapable corollary here is that we can’t just sit back and wait for data to come to us—a lot of it we’re going to have to go out there and rescue!

And I may be airing some library dirty laundry here, in which case please forgive me, but it’s not just them—it’s us. We have plenty of unsustainable digital projects sitting around our libraries. Just think for a second: how many different digital-library, repository, and storage platforms are running inside your library? I won’t even answer for mine; it’s a scary large number. The stuff in those platforms is in danger. We made this mess, we librarians; we have to clean it up. As Richard said yesterday, we have to set an example with our own data! How are we going to establish ourselves as authorities in describing and organizing data if our own datastores are not in order?

A lot of data are analog.

… but really want to be digital. For example, scientists still use paper lab notebooks. I wish they didn’t too! The university archivist on my campus really wishes they didn’t, because they keep trying to give him hundreds of boxes of lab notebooks that he can’t possibly find space to store! And that’s just one example. Linguistic field notes, on paper. For one of the linguists I’ve talked to, her notes are some of the only attestations of the language we have! Slides are a constant bugaboo in visual arts communities. Faculty have a tremendous volume of analog materials that would be much, much greater use if they were digital. Can we scale up to that? Again, I don’t know, and I’m not going to talk about this problem again. It’s there, we probably need to solve it, end of story.

Data are project-based.

Aha. Now we get interesting.

Exploring the Hype(r) is a dissertation. It includes its underlying data, as it says: “Explore the primary data from this research project and construct your own hypermedia ethnography.” As you may be able to see at the bottom of the page, it’s built on the blogging tool WordPress and the Center for History and New Media’s exhibit-builder tool called Omeka. These are great tools! I love them both. But what are we librarians going to do as our dissertators pile random webtools on top of each other to build their dissertations? That’s what project-based thinking gets you: total technological randomness. But our researchers think in terms of projects. The latest grant. The latest collaboration. And when it comes to technology, they’re not above doing something different and sui generis for every single one.

Data are sloppy.

By the same token, faculty are not librarians. They are messy, messy people, a lot of them. Many more of them leave petty chores like, I don’t know, organizing research materials and results—to their grad students. This means that our data buckets are not going to fill up with nice neat orderly well-described, data-dictionaried columns of numbers. Honestly, what we’re doing is catching sloppy leaks, and we can expect to be for a long, long time.

And when our systems, library systems, only accept data that’s clean and pretty, we have a problem. Data standardization is not even seen as a desideratum by data creators yet. I know most of us know this, but in the print world, the journal-article-and-book world, we have publishers to impose some kind of uniformity. Data doesn’t live in that kind of world. We may yet get there, but honestly? I don’t expect it in the length of my career.

That’s our trawl through some basic characteristics of research data. What do we have in libraries to throw at this problem?

Our Big Buckets

The digital library

People think that primary-source data, even big data is a new thing to libraries. It’s not. We were doing big digital data before the researchers were, in the form of the digital library! What did I hear yesterday, ten terabytes of TIFFs from a single digitization project? So it’s possible to think hey, we’ve got this solved! We just apply our existing digital-library infrastructure, human and technological, to this new problem.

The institutional repository

If that’s not enough, at the same time, we’ve been building another kind of digital bucket; we’ve called it the institutional repository. And again, some people think that IRs just solve the data problem. Magic IR pixie dust, or something!

Impedance mismatches

Well, it won’t surprise anyone that I don’t think that’s true. There is no magic pixie dust for research data curation, not in digital libraries and not in IRs. What we’ve done with digital libraries and IRs gives us a lot of the skill and knowledge we need to work with research data; I firmly believe that, though it’s hard to find researchers who do. But we’re going to have to do a lot of rethinking and reworking the way we do things. Otherwise, we’ll just trip all over ourselves and the impedance mismatches between the characteristics of research data and the characteristics of digital libraries and IRs. So let’s take this a piece at a time.

What do we know about digital libraries?

Where I am, we’re trying to rebrand our digital collections, because we don’t think “digital” should be what linguists call a ‘marked’ state any more. Digital is ordinary, or it should be. Digital is normal. So given that, how do you brand digital collections? If you have an idea, see me after, will you?

Anyway, what are digital libraries like? And how is that going to work with research data? Just like our print libraries, we’ve built our digital libraries carefully, out of the best materials. We’re not making digital libraries out of any old thing; we select what we’re prepared to lavish effort on. And we do lavish effort! Look at this Library and Archives Canada website! It’s a lexicon of a First Nations language called Naskapi that’s available in that language, including the fonts to represent that language—I love this site! It’s beautiful![1. The site no longer exists. It was probably destroyed in the early-2010s gutting of Library and Archives Canada.]

How are our thoughtful, careful collection-development policies going to cope with what’s already out there? How will we decide what we pick up and what we leave behind? I already see troubling signs that in the absence of better policy, cyberinfrastructure shops are deciding to help whoever has money. I don’t like that trend and hope we in libraries challenge it. When I go to data curation workshops, most people think of data curation as “the new special collections” or “the new archives.” Understanding that we can’t keep everything, they’ve come up with elaborate decision mechanisms for figuring out what to keep and what to toss.

Well, I think there’s a problem with that. It’s a human problem. It’s the faculty member who, when told you’re not going to curate his lousy badly-designed badly-described dataset, turns around and never darkens your door again—even when he’s got a dataset that will revolutionize his field. How do we harmonize the need to provide good service with the need not to swamp ourselves with garbage? I don’t know, and I suspect answers will differ, but I do know we need to figure that one out.

How are we going to rescue data when, by our standards, a lot of it is sloppy? Are we prepared for the work involved in rescuing other people’s sloppy data? Are we prepared to let other people’s sloppy data in alongside our nice clean pretty data?

And given that many datasets are project-based, are we going to pick and choose among projects? Based on their software platforms? Can we? What about dissertations, which are institutional records no matter how they’re created? We’re going to have to rethink how much and what kind of care we can and should give our data libraries. Like it or not, they can’t all look as beautiful as this; volume and condition forbid.

Production is a Taylorist’s dream.

Where I’m from, and perhaps where you’re from too, we like our production of digital objects, mostly but not entirely through digitization, to run like a well-oiled machine. It’s generally more cost-effective to do things in large volumes and in systematic ways. In the States, we call this a “Taylorist” way of going about things. For those who don’t read management literature, Frederick Taylor was the guy who taught Henry Ford how to run auto production. Taylor measured how long it took people to do things, and made it so people had to make the fewest and smallest motions possible to get the work done.

What Taylorist production methods mean in a digitization context, of course, is that you tend to limit the type of work that you do to what you can easily automate and train for, which in practice means only a few kinds of data per library. We do our image collections or our newspapers or our finding aids or our text collections—we in essence specialize ourselves by data type, again for efficiency’s sake.

How well is that going to serve us when we’re not in control of the data-creation process? When the data don’t fit into the buckets we’ve designed for our own particular digital-data specialties? If we’re going to come to grips with data on an institutional basis, we won’t have the luxury of specializing any more. How are we going to cope? How can we be Taylorist about gathering and describing data when the data just aren’t standardized? And if we can’t be Taylorist about it, how do we keep up with the flood?

How are we going to manage when there’s a technical-infrastructure mismatch between their project silos and our Taylorist, tailored environments? We have some choices, but none of them are particularly good. Do we pull the data out and start over, ignoring the effort put in on the original interface? If it’s on the web, do we take a static snapshot of the original? That feels a bit to me like pinning a gorgeous butterfly through the head, killing it, to display it in a glass case, though I have to admit that I do it because I don’t necessarily have a better option. Do we recreate the original interface, and take on the work of maintaining and improving it? Those don’t sound like Taylorist processes to me!

I’m frightened—honestly scared to death—at how many librarians do not realize that this is a problem. They really seem to think that you wave a magic wand over somebody’s random dataset and it miraculously shows up in a repository! It does not work that way! For every new input, somebody has to figure out what’s in there, how best to represent what’s in there on the repository technology platform (whatever that is), and how to move the old representation into the new one. That… looks suspiciously like work. No, look, I do it—trust me, it’s work.

Where I work we’re starting to think and talk very seriously about this, because our digital-library processes are very Taylorist, and we’re realizing that that’s not serving us well as smaller and more specialized projects come our way. Everything right down to how we budget projects is going to have to change. Honestly, we’re finding this a struggle—but a necessary one, and one that I am proud to say that we’re confronting head-on.

Some of you are looking at me right now with utter bemusement. Your digital-library production isn’t Taylorist at all! You only wish it were. What it is, is completely ad-hoc. Something interesting comes in, you build a way to deal with it, you slap it up on the Web somehow or other, problem solved.

And thus are born project silos, both inside and outside libraries!

One of the problems with project silos is that they aren’t replicable across libraries and institutions… and the last thing any of us need is to reinvent the wheel! If you’ve never looked at Decameron Web, I love it, check it out—there’s some nice TEI-based user-interface work in there. But I can’t build DanteWeb or CervantesWeb based on DecameronWeb; the innards of Decameron Web are opaque to me. It should be easier.

And another problem: project silos aren’t part of the web. It’s what I saw called a “cabinet of curiosities” in an article I was reading: nice to look at, but impossible to really work with. Now, this isn’t entirely the fault of library technology. It’s partly the fault of librarians who natter on about “context” as though it were the be-all and end-all. My belief is that context is fluid, not fixed; it’s constantly being built and rebuilt, rather than something trapped like a fly in amber. We have to expose our digital objects so that they can appear in entirely new contexts. That’s not decontextualization! It’s re-contextualization, and cabinets of curiosities don’t allow it. Many are content-specialized, such that presentation is content-specific. For each project silo, its own user interface. Books browse differently from maps, which browse differently from finding aids. Right? I wonder. How can we maintain all this user-interface code?

Now, I’m the last person to tell you to build The One User Interface To Rule Them All. Not possible! As I said earlier, data have affordances, ways they want to be interacted with, and we absolutely need to respect that. However, it’s possible to go too far in the other direction, building interfaces so content-specific that the content winds up in a cage of jargon and non-interoperability. That’s where I think we are in digital libraries, and it’s a problem.

These practices have a lot in common with what our researchers do! Everything is its own project with its own technology stack and its own silo. Well, this isn’t workable. It’s wasteful duplication of technical effort, for one thing; why build—oh, a tagging infrastructure—more than once? It also creates huge headaches for discovery processes and especially for digital preservation. The more interaction you have to preserve, and the more different ways it’s coded, the more lines of code we’re all maintaining, and who needs more lines of code to maintain?

But it’s happening anyway, and if we’re serious about data we’re going to have to deal with the result.

Now I’m going to go a little Cassandra on you—we have already lost a lot of digital projects to the project-silo problem, particularly in the digital humanities. Some of those projects were ours: developed in libraries, but not sustainably. I predict with absolute confidence we will lose more such projects. There is a crying need for academic librarianship to develop a coordinated, collaborative rescue effort for early digital projects, if only to stem the bleeding.

On a happier note, if we do take the trouble to rescue our own projects, we will learn a lot about rescuing other people’s. I think that that learning process all by itself should be incentive for forward-thinking academic libraries and librarians to start undertaking rescue efforts.

So that’s where we are with digital libraries, and where I think our practices are going to come up short in the new data world.

What about institutional repositories?

The word “institutional” is becoming a serious problem. I would argue it always was. In my worklife, if I run into digital objects needing archival, I cannot go anywhere near them until I prove a link to one or more faculty members in my home institutions, and the weaker that link is, the more red tape and bureaucracy I have to go through to get permission to help with the project—no matter how important I think that project may be.

The problem is most acute for already-existing data. For example, think about what happens when a researcher leaves your institution for a different one. Their institutional web presence tends to remain behind. There may be valuable data there. But can the IR get involved, if the researcher doesn’t have a connection to the institution any more? Of course, it also means that data at institutions without IRs just fall between the cracks. Definitely not ideal, not what we want.

This is another aspect of data sloppiness. A lot of them don’t clearly belong to one institution, or indeed to any one institution! Consider something like a disciplinary data or e-print repository. One of those just came up for rescue, the anthropology repository known as Mana’o. Would I, as an IR manager, like to rescue it? Sure! Do I have the technical capacity to do it? Mostly; I could at least take a stab at it. Can I do the rescue? Oh, goodness no. Not in my remit; I’m not allowed. It’s not institutional data, so I can’t touch it.

So it follows, at least to me, that if we’re going to grapple with data in our institutions, we will have to give up on the purely inward-looking focus that IRs have had. Maybe different institutions will choose disciplinary specialties to focus on. Maybe we’ll just drop the idea that data have to originate within our institution before the institution is interested in them. I don’t know. But if IRs are going to play in the data space, something in the policy environment has to give.

This restriction, this institutional cage, is an artifact of the scholarly publishers; it’s not something libraries invented. Some publishers allow self-archiving only in “institutional” web presences. If an IR opens itself to a lot of stuff that doesn’t have strong and obvious ties to the institution, it is opening its institution to a very real legal risk, a risk that some publishers will sue the institution, making the argument that it’s not an “institutional” repository any more because it contains non-institutional content. But the reality is that research does not stop at institutional borders. And the more that IRs cling to that institutional cage, the less we can actually do to salvage and protect research data.

Data diversity

Unlike digital libraries, at least in theory, IRs were supposed to accept any kind of digital content or data at all! But the snag there is that they’re not really designed for it; they’re optimized for research papers. So in practice, you get the famous Henry Ford statement about Model T cars: you can have any color you want, as long as it’s black!

The “we’ll take anything” promise is broken and has always been broken. We’d take anything immutable. I use this photo of a junkyard advisedly, because for a lot of faculty, once something they produce is static and final and immutable, it’s junk! It’s out of their sight and they don’t care about it any more. So it never gets deposited in the IR to begin with, which means nobody’s taking care of it. The researcher sure isn’t; it’s old news.

The “static and final” model is absolute garbage for interactive data. It’s especially garbage if interacting with the data is one of the ways that the data are made more reliable! Maybe the first reduction of the data is wrong. If we then can’t change it because our repository only handles what’s final and static… we are not serving the need here. It’s also not ideal for what’s already out there. We know a lot of that stuff is in bad shape, but if we wait to ingest it until we can clean it up into an acceptable final form, we may lose it altogether.

IRs are lousy at dealing with data diversity. I’ll have a few more words about this later, but for now I’ll just state the obvious: putting research data into a user-interface optimized for research papers is a total loser. Papers have built up a lot of uniformity over the centuries we’ve had journals. Data are a whole different story.

Again, all this is a profoundly human problem, and another place where the technology we created has an impedance mismatch with the way researchers actually work and think. Richard’s Q&A session yesterday brought up a key problem with the static-and-final idea: sometimes you think something is static and final when it’s really, really not. And some things are just not even meant to be static and final! DSpace, for example, assumes the static-and-final, so much so that it makes correction of an item already ingested into DSpace difficult and perhaps impossible unless you’re the systems administrator. How much time I have wasted swapping out files for people, you really don’t want to know. Fedora users, don’t get smug here, because Fedora has similar problems.

We can’t accept that for data. Humans are imperfect. The artifacts that we produce are imperfect and incomplete. Our systems need to accept and work with that imperfection, allowing us to work toward perfection, conscious that we’ll never quite get there. Librarians tend to hate this point of view; we’re all about the static and final and authoritative. I am here to say we have to get over our bad selves. We have to, if we’re going to do justice to research data.


So, IRs promise to take anything you’ve got, anything at all—but you have to put it in one file at a time, like coins into a glass piggy bank. Putting data into repositories one file at a time, manually, is like emptying the ocean into a bucket with an eyedropper! And since data are already out there, we have to make it easy to dump in large quantity into our buckets. That means more APIs and protocols. SWORD is good, I like SWORD, I love what I heard about BagIt yesterday—but honestly, it’s got to be even easier than that. I want researchers to be able to push the “Archive It!” button and have it just silently, seamlessly work.

IRs promise that you can customize their look and feel, but in practice, it’s too hard. How many people in here can tell a DSpace from an EPrints install just by looking at the front page of the site? I sure can. And anyway, what you get even when you customize is this very sterile, boring, libraryish look and behavior; it’s not appealing to the researchers whose hearts and minds we need to capture. Look, I did this redesign for MINDS@UW, I am hoisting myself on my own petard here, but we need to do better than this!

Look at this gorgeous little site for Exploring the Hype(r)! Isn’t it appealing? If I promise the researcher here that I’ll take care of her data forever and ever at the cost of it losing all its visual appeal and its individualized usability, is she going to take me up on that? I wouldn’t take me up on that! So this becomes a content-recruitment problem; researchers see IRs’ ugly, pathetic little one-horse interfaces and interaction patterns and they run screaming in the opposite direction.

I know I keep coming back to this data-diversity issue like a bad record, but so much of our infrastructure just fails when confronted with it. One interface does not fit all. There is some experimentation happening in IR space. Manakin for DSpace making collection-based theming possible was definitely a step forward, though perhaps not enough of one; too much of the page-construction logic still lives in Java. The KULTUR project in the UK is adapting ePrints to be appealing to visual and performing artists. All of this is good and we need more of it, but I think we have to confront a wider issue: building our platforms with enough flexibility to be easy to customize for as much variation as we can manage. We also need to make it easy for people to construct their own look and feel on top of our stuff, or just with our stuff in it where that makes sense. Our silos really get in the way of that now, and it’s a problem.

Metadata and content models

IRs will let you have any metadata you want, as long as it’s no more complex than key-value pairs. I hate this. All the marvelous work being done with linked data, XML, semantic webby sorts of things, and all I can have in my IR is key-value pairs? What is up with that? The diversity of data environments includes diversity in metadata; I’m sure that’s a surprise to no one. It also means a diversity of metadata content models, well beyond key-value pairs. Imagine the ideal data project. It’s already well-described in an elaborate schema and well-organized. Are we seriously going to tell the provider that they have to dumb it down to key-value pairs before we can take it? Seriously? I hope not. Reality check: anybody developing a metadata standard these days expresses it in XML or RDF or both. Key-value pairs don’t cut it, and arguably never did.

As for end-user functionality, IRs can take in digital files and they can give them back. Honestly, that’s pretty much all they can do. This just kills us with interactive data. It kills us! A lot of these data need APIs. If we’re not providing them, honestly, we might as well not bother. Interact with data? In an institutional repository? Mash it up with something else? Heavens forfend—that would imply that digital objects are somehow related to each other, and that’s just crazy talk. So we have a lot of interface and API work to do. A lot of it!

Here’s a real-world example of the difficulty. A project I’m helping with for the UW-Madison Zoology Museum involves a teaching collection of animal skeletons that students measure and do comparisons on. We’re photographing those and whomping up an interface that lets students do that measurement work digitally. This saves wear and tear on fragile realia, allows distance students to participate fully, and, we hope, creates an archive that’s useful outside our campus borders.

We’re using Fedora for this, and the content modeling gets complicated. We have a specimen—say, a squirrel—which has any number of actual bones, and each bone may have several photos in various views, and this matters as far as “where do we hang which metadata” and “what do you want people to find in a search?” and “how do you display on a specimen page all of its component bones and views?” These questions have sparked a lot of entertaining (and sometimes macabre) conversations.

Now, imagine for a moment that this had been a DSpace project. Here is the content model for DSpace, the only content model: communities, collections, items, bundles, and bitstreams. “Community” is not even relevant here; “collection” sort of fits, but not terribly well. So we’re left with items, bundles (whatever they are), and bitstreams. And only items can carry metadata! I don’t need to say any more. DSpace, which is running the lion’s share of institutional repositories in the United States, is completely functionally inadequate as a serious data bucket! So much for the IR.

So where does all that leave us?

We need bigger, better buckets. I love the idea of just grabbing a bucket and going after data. I admit it’s probably an 80/20 thing; there’s 20% of the problem-space we’re looking at that we cannot realistically solve. But I know we haven’t served 80% of our users or 80% of our potential content. We can do better, and we need to.

Silos are both necessary and unacceptable. At some level data are all bits, and at that level, silos tend to be counterproductive and stupid. We shouldn’t have to build a checksum engine for sixteen different silos! Where I am, we’re working toward combining our digital library and our institutional repository on a single technical infrastructure, because it just makes sense to do that.

But because data come in thirty-six flavors and then some, once you get above the pure-bits level it’s unrealistic to think that we can design one silo that will work equally well for everything. Our infrastructure has to be flexible, it has to have APIs that other people can build on as well as ourselves, and it should make the most of the commonalities we do find in wildly diverse and heterogeneous data. Homogeneity whenever possible, flexibility where necessary: that needs to be our motto as we build these systems.

We have a lot of modeling to do. Again, because of data diversity, the content-modeling exercise I talked about with the zoology skeletons will have to be replicated, over and over and over again, as new kinds of data come our way. I don’t know if this scares you—it sure scares me. Add standardization processes on top of this, because we can expect some kinds of research data to develop standards, and it gets even scarier. Fundamentally, we need more efficient ways to do this work—a sort of meta-model for content modeling, if you will. I don’t know how that can work; I just know it has to.

We have a lot of code to write. This should be uncontroversial. I know a lot of you are already writing this code! Thank you. Now share it with the rest of us, please, because here is another Cassandraic dire warning: we cannot possibly hope to keep up with the data flood if we’re all making our own little content models and coding up discovery and dissemination frameworks in isolation. Why should anyone out there have to decide how to represent skeletons and bones? At Wisconsin we’ve done that for you!

“We love open source; no, you can’t have our code” won’t work any longer, folks. We have no choice but to figure out how to share code better. What’s more, we have to figure out how to share code with people no more technically inclined than I am, and perhaps less. Now, just a little bit about me: I hate Java. I am violently allergic to Tomcat. I don’t even like man pages! Can you build a system for me? Now think about the vast DSpace installbase out there. Think about how many of those installs happened because DSpace was supposed to be an out-of-the-box solution. Now think about how we’re going to migrate these people to something more flexible. Scared yet? I am!

Brian Owen talked yesterday about how hard it is to solve these collaboration problems. I agree with him! It’s hard. It’s a human problem, and human problems are hard. The problem is, all the alternatives to solving this problem are even harder. We’ve got to fix library-technology collaboration.

Of the digital-library and institutional-repository platforms out there today, I think Fedora is the horse to bet on. It’s the only one that comes close to the storage and presentation flexibility needed for a big data bucket, and I think the data buckets such as RepoMMan that have already been built atop it are all by themselves a pretty good indicator that it is the future. But Fedora needs to make some changes—some technical, some social. Content models, service definitions, and their associated code need to be pluggable, to avoid the wheel-reinvention I’ve said we can’t afford. I don’t entirely know how this needs to work, though the plugin and mod structures for projects like Drupal and WordPress may be models. I do know that it does need to work, or we’re all going to drown in our buckets. And then we have to build the social scaffolding to actually share these pieces of code, which may turn out to be harder than the actual technology!

Fedora also made the same mistake DSpace did with regard to the editability and replaceability of objects. Getting stuff into Fedora you can do with what Fedora hands you. Removing stuff, you can do. Editing stuff? No, unless you want to edit XML as text in an incredibly clunky and ugly Java app. Replacing an object with a better object? No. This is not acceptable, Fedora; it needs to be fixed as soon as possible.

We also have to put easier tools on top of Fedora, both on the data-producing and data-consuming ends. That’s being worked on: Islandora, Omeka-over-Fedora, lots of things, and that is all to the good. Fundamentally, we have to figure out ingest straight from whatever unholy mess a researcher has, and we have to be able to translate the affordances of a particular dataset easily into our systems. I don’t think either of those solved yet, though RepoMMan comes close; even the SWORD protocol is much too complicated for this. But solving this is not optional, because you can’t curate what you don’t have. This is a fundamental truth that the IR experience should have taught us: if our systems don’t invite deposits—even sloppy ones, even unfinished ones, even bad ones by any measurement—and if they don’t do it as early as possible in the research process, so that researchers don’t get fixated on some other software system, there’s no point to having research-data repositories at all. I know this goes against the grain, hundreds of years of library perfectionism, but I’m afraid that’s just too bad! If we’re playing in this space, we have to be ready to make some mud pies.

I’ve always, always loved the RepoMMan project for this reason, and I also really like what the California Digital Library is building. They’re starting with the good old filesystem, which we all know and more or less love, and they’re enhancing it into a curation system. It’s an approach I think will bear fruit, and that’s because they’re starting from the right place: where people actually do their work.

Now, to end on a positive note, I love the Solr app, and I think it’s a marvelous example of the kind of lightweight tool that does really heavyweight things. The beauty of Solr is that once I’ve solved the intellectual problem of “what metadata do I want to expose for search and browse?” Solr makes expressing that in a crosswalk just stunningly, beautifully trivial—and then I never have to worry about it again for that flavor of metadata. There is complexity under the hood, but our experience at Wisconsin has so far been that you don’t encounter that complexity until you actually need it, which is just perfect.

So that’s what I have to tell you. If I’ve helped you see some of these problems in a new way, if I’ve expressed them usefully, such that they get solved, perhaps I’ll get to stop being Cassandra—and instead become the Clio of data curation. Here’s hoping. Thank you!


Grab a bucket! Introduction

This talk was originally given for Canada’s Access Conference in 2009. I horribly overwrote it, such that I had to skip past a good fifth of it. This reconstruction includes the section I had to gloss over. I made myself stop overwriting talks after this!

In 2009, what I had to say here came across as a daring challenge to conventional wisdom. That nearly all of it is essentially commonplace in 2015 is not my doing, but I am not at all displeased at it.

This talk was distilled into the Ariadne article “Retooling Libraries for the Data Challenge.” Unfortunately, I did the distillation in rather a hurry, so the article does not hold together as well as I think the talk does. It’s for that reason I present revised talk notes here, rather than the article.


The Purple Squirrel (and other damaging technology myths)

So my name is Dorothea Salo and my job is making more of what Jason Scott called “angry archivists” yesterday! No, but really, the reason I’m here is I teach technology, among other things, in a professional school: library school instead of law school, but I think we’ll find we have a lot in common.

One thing I know our professions have in common is a lot of swirling anxiety about technology and technology education. Am I right? And sometimes that fuels great things like this very conference, but speaking as an educator, I find that it also fuels a lot of miscommunication and weird expectations. And that frustrates me. Maybe you too? I think part of the problem is some cultural myths about technology that we’re all struggling with. So I want to talk about those myths and the damage they do, and I want to push back on them, and I want to suggest some ways that all of us—educators, technologists, professionals, and students—can start to move past them.

And I want to start with the Myth of the Purple Squirrel.

So what in the world is a Purple Squirrel, you may well ask. Some of you may know it as a “purple unicorn” instead, but “purple squirrel” is actually a thing; it’s mostly recruiters and human-resources people who use it. It’s got a Wikipedia entry and if you look on Amazon there’s a book about it, so I ran with it. A Purple Squirrel, for purposes of this talk, is the perfect technology hire you see in really bad job ads: the one person who can do everything imaginable with technology so nobody else ever has to touch a keyboard, the brilliant polymath who knows everything about every technology since forever and never, ever, ever makes a tech mistake.

In other words, hiring a Purple Squirrel into a library or a law firm lets technology be Somebody Else’s Problem, as Douglas Adams would have put it.
Let me just say—this is probably not news to anybody but let me get it out there anyway—this is not a healthy way to think about technology, in libraries or in law firms.

If you haven’t seen the Purple Squirrel in job ads, I do know a place you have seen him, and that’s in technology competency lists. Now, the library school I work at is currently in the middle of an accreditation cycle, so let me say this with feeling: there are a lot of technology competency lists.

Now, my sincerest apologies to the competency-list compilers yesterday, because I know the intention here is often good, but… are you kidding me with these things? Are you kidding me? You could spend a lifetime learning technology and not be competent according to these lists! The only conceivable competent person is a Purple Squirrel! Competency lists as they currently exist are complete Purple Squirrelsville.

How do you detect a purple-squirrel job ad or competency list in the wild? There are some classic warning signs to look for.

First, look for a demand for more years of experience in something than are actually possible. So, in honor of yesterday’s keynoter, the amazing Jason Scott, I’ll use this hypothetical example: three years of experience working with JSON-LD. For our purposes it doesn’t even matter what JSON-LD is, but if you were at the Legal Information Institute lunch session or the value-added repository session yesterday, you heard a little bit about the Semantic Web and linked data. So JSON-LD is a web-developer-friendly way to write linked data. But that doesn’t matter; we don’t care what JSON-LD is. What we care about today is that this requirement for three years of JSON-LD looks fine until we discover that JSON-LD didn’t even officially exist until early this year! (I would not actually be surprised to find that this job ad exists. I didn’t look, don’t sue me!)

Another classic sign of Purple Squirrelishness is asking for every tech skill in every tech book in every tech library everywhere. So you want somebody who knows databases and SQL, and web design, so HTML and CSS, and programs in at least six different programming languages, and is a systems and network administrator, and can do desktop tech support for everybody else in the office, and is a gadget hound who can develop mobile apps, and is a total social-media whiz—because you have to keep those Likes coming—and and and

… and a floor wax and a dessert topping, what in the world, people? Are you kidding me here? Are you kidding me? But I keep seeing these job ads and competency lists and nobody calls them out on their total absurdity, because we have this notion, this Purple Squirrel myth, that tech-savvy people are automatically omnicapable. And if this is your notion, or if you don’t really understand how all the things I’ve put on this slide are different from each other? You’ve probably written a job ad for a purple squirrel. And heaven help you, you probably pitched it at entry-level. And if you’ve done that, I’d love it if you stopped. Please stop.

Because True Confession pulp bestseller time here: I was a Purple Squirrel.
Purple Squirrel faux book cover

(Does today’s extremely purple look make sense now? I hope so; I wouldn’t want you thinking I’m eccentric or something. Also, yes, I know the Latin on the back cover is wrong. Pulp book, right? Verisimilitude!) When I got out of library school, I knew just enough about a whole lot of different tech things to be dangerous, so I got hired into academic libraries to do all the tech stuff—and all the other stuff—relating to scholarly communication. And let me tell you, being a Purple Squirrel made me want to write this book! (I haven’t. I hired the brilliant Tommy Jonq to fake up this book cover for me. But I admit, I do wish this book existed.)

But at this point you may be saying, okay, this purple squirrel myth, it’s a thing, so what? Does it actually matter? How much damage can a myth really do?
Well, one thing is that there are people who lie about being purple squirrels and still get hired, because nobody doing the hire knows enough to call them on it—I’m sure you can tell as many horror stories as I can.

There are also people like me who can fake purple squirrelishness well enough to get hired, and we do our level best, but the expectations are kind of ridiculous. And I know what happens to those people, I was one! You probably know too. Spoiler: it’s not anything good. We become targets. Any workplace tech-impoverished enough to try to hire a Purple Squirrel isn’t really into technology in the first place. Actually, that is an understatement: a lot of people in that workplace hate and fear technology, I guarantee it, and in my experience and that of my students, they have no scruples about displacing that hate and fear onto a Purple Squirrel hire, not to mention using organizational and budgetary power—“soft power” if you will—to make sure the Purple Squirrel can’t get anything done.

And as someone who teaches technology to future librarians, this really bothers me. I don’t want my best, most tech-savvy people graduating just to become targets! How is it even ethical to ask me to train people up for that? I really want our professions, law and librarianship, to welcome the tech-savvy better than this, and I want this partly because the whole work-displacement and dismissive-treatment thing has some really skeevy gross echoes in law as well as librarianship:

  • “That’s paraprofessional/paralegal work.” Wincing yet? Let me make it worse.
  • “That? The Girl does that.” How about now?

Both our professions have a history of shoving off work we don’t want to do on other people, sometimes in creepy gross gendered and racialized and class-bound ways. And that is not acceptable. That is damage that the Purple Squirrel myth actually perpetuates, because whoever Purple Squirrels are, they’re not “us,” not us professionals, whoever we are.

Here’s one that actually happened to me! “We don’t need to be running all that fancy digital stuff. We need to hire some real librarians.” I overheard this shortly after starting my very first job as a librarian, and it just goes to show, right? Whatever technology is in law or in librarianship, it’s not actually real law or real librarianship. What is this? What is this divide? And why do some of us seem to think it’s okay to remain technology-ignorant, as though technology somehow isn’t part of the profession’s regular praxis?

Because—I’m sure this is not news—tech ignorance hurts. For one thing, tech ignorance is how law firms, libraries, governments embarrass themselves and hurt other people. There are a million examples, right? Here’s just a few, all from the last year or so.

  • A law professor didn’t encrypt his laptop or hard drive storage, and had a bunch of really sensitive data stolen along with it. Ouch. And if that law professor is you? I’m sorry, this must be painful, and I intentionally didn’t use your name. If you’d like a consultation about how not to have this happen again, research-data management is a thing I teach and consult on, so I’m here for you!
  • The nation’s security establishment, utterly owned with a simple garden-variety web crawler!
  • Everybody is laughing at the Federal Register, which apparently can only accept digital documents on three-and-a-half-inch floppies.
  • This one’s great! Maybe you heard it already. A huge court case was lost because the plaintiff’s lawyers didn’t realize their client was faking emails entered into evidence.
  • And if that’s not enough, you can get yelled at from the federal bench for screwing up technology! Not your Purple Squirrel, they’re not being yelled at; you are.

And I didn’t even have to resort to talking about failed redaction here. If I talked about failed redaction, we would be here all day.

Now, I additionally want to suggest that bad tech hires are also serious damage caused by the Purple Squirrel myth, and it’s damage that goes on to cause even more damage. Purple Squirrel job ads mean that law firms and libraries and governments do not get the tech hires they need. I only took a Purple Squirrel job because I was young and stupid. Tech-savvy people who’ve been around the block a few times can recognize a Purple Squirrel ad from miles away, and they do not apply, because nobody wants to be the workplace target for technology hate and discontent.

So it seems people who want Purple Squirrels can’t hire them. If you’re having trouble hiring one, what do you do? All the educators in this room know what the answer to that is: it must be a professional education problem! This is my life now, teaching technology in library school. I’m blamed for everything you can imagine. Ask any practicing librarian or archivist; they’ll tell you I’m doing everything wrong and basically I suck, because all educators suck, and I’m an educator!

I’m betting I’m not the only tech educator in this room who’s feeling this. Everybody wants you to graduate the Purple Squirrel Lawyer. Everybody wants me to graduate the Purple Squirrelbrarian, and everybody yells at us constantly like we’re not smart enough to have figured out that’s what everybody wants. Well, I know that’s what you want! You don’t have to yell at me any more about it, I know, I promise I know!

{In the voice of the character Hal 9000 from the film 2001: A Space Odyssey} But I’m sorry, Dave, I’m afraid I can’t do that. It’s not that I don’t want to, Dave, it’s not that I wouldn’t if I could, Dave. It’s that given the time and resources I have, Dave, the students I’m working with, Dave, I’m afraid I can’t do that. And I will make bold to say that if you stood in my purple shoes? You couldn’t do that either. Dave.

Now, I’m indebted to UK law librarian Pete Smith for how I’m about to explain why not. Most students entering library school are the technology equivalent of couch potatoes. They haven’t much experience with technology beyond the basic consumer level; they’re not used to it and they haven’t been taught about it. And I’ve asked around: is it just our students? maybe we’re admitting the wrong people? And what I hear back every single time is no, it’s everybody, every library school is dealing with that. And I’ll go out on a limb here and say it’s probably true of law schools as well. Law-school students mostly start out as technology couch potatoes.

And we educators? We’ve got two or three years, assuming a full-time student, to do something about that. And not even two or three full years—we’ve got two or three years where they’re doing lots of other things and technology instructors see them for one to three courses and that’s it.

So in those two or three years, those one to three courses, I’ve found that students can do the rough technology equivalent of a couch-to-5K run. It turns out that in physical exercise terms, couch-to-5K is a thing that a fair few people can realistically do. So there are great materials that show people step-by-step (so to speak) how to get from being a couch potato to running a 5K race without injuring themselves or giving up, and there’s lots of help and encouragement and equipment recommendations and all that good stuff.

And I flatter myself that I do pretty well at couch-to-5K technology training. A lot of other people do too. So couch-to-5K is already happening in library professional education—I certainly have no plans to stop!—and the sense I get is that law is working toward it too.

The problem is that the library world—and I’m guessing the law world too—isn’t happy with couch-to-5K. What they want is couch to amazing long- distance Olympic gold medalist Mo Farah! So, couch to Mo Farah! In three years, max! Get to it, you lazy good-for-nothing educators you! Well, I think Mo Farah’s dubious face says it all, but just to reiterate… {HAL 9000 voice again} I’m sorry, Dave, I’m afraid I can’t do that. You can’t do that either. Dave.

(Any Daves in here? I apologize, it’s not about you. I couldn’t resist the HAL 9000 joke.)

And part of the reason this is impossible gets back to the bizarre breadth of expectation, right? In what universe does anybody, anybody at all, start from being a Microsoft Office and Facebook jockey, which is where most of my students start, and go on to learn all the technologies I mentioned earlier to Purple Squirrel levels in two or three years? Write all the competency lists you want, I’m telling you, it doesn’t matter. Students can’t master those lists in two or three years. I mean, be honest, could you? If you don’t think you could do it, what makes you think my students can?

Ah, but wait. It’s not supposed to be hard to teach technology to law-school and library school students, is it? Especially if they’re fresh out of undergrad. Because people that age are all—say it with me here—digital natives. Right? Isn’t that how it goes?

Well, “digital natives” is the second myth I’m talking about today. It’s a myth, all a myth. The whole thing started from lousy question-begging analysis of scanty biased data from the richest county in the entire United States that has been debunked all over the place! The truth is that young people are not digital natives. They are not, in other words, readymade Purple Squirrels!

And can we just talk about this phrase “digital natives” for a moment? I feel nasty just saying it! I didn’t even try to illustrate it, because what image could I possibly put on this slide that would not be a grossly objectionable stereotype or cultural appropriation? The word “native” in the mouth of a white European-heritage person like me has centuries of horrific abuse and destruction and discrimination to answer for. So let me see if I get this: we’re going to refer to supposedly tech-savvy younger people with a term that has a long history of being used to dehumanize people, and we’re okay with that? I am not okay with that, and I apologize to everyone here that I couldn’t find a way to talk about this myth without using this term. If you’re as grossed-out by it as I am, or even if you’re not, I really recommend the Bayne and Ross article on the subject, which you can find as a draft online. So what I’ll try to do for the rest of this talk is use “baby Purple Squirrels” instead of “digital natives.” If I slip, I’m sorry.

Can’t we get over this baby Purple Squirrel thing already? Well, no, no we can’t, because it figures so prominently still in talk about technology and technology education—and why is that? No, seriously, why? Why won’t this sketchy, false, dehumanizing myth go away?

Well, part of it is the usual dumb “Kids! I dunno what’s wrong with these kids today” generational friction that’s been around since ancient times, and it’s really stupid, but I can’t make it stop with one lousy keynote address. Truthfully, though, I think it’s more than that. There’s got to be something attractive, something that’s useful to somebody, in this myth that young people are baby Purple Squirrels who know everything about technology and never have to be taught about it ever and don’t need any actual time or opportunity to learn. What might that attractive thing be?

To get at it, I want to introduce the flipside of the baby-Purple-Squirrel myth. This is, of course, another myth, and another really nasty repellent myth at that. It’s the “One Funeral at a Time” myth, illustrated as a pulp mystery-book cover by the amazing Tommy Jonq:

One Funeral at a Time faux book cover

According to this myth, people who are too old to be baby Purple Squirrels—and for the sake of argument I’ll define that as “anyone over 30” because that number has cultural resonance for some of us—absolutely cannot learn anything ever about technology, so all they do is get in technology’s way. The only way that will ever change is for those incompetent incapable oldsters to retire or die.

Well, yesterday’s conference kickoff gave the lie to the whole “old people don’t know tech” thing, but in case you need more evidence, it so happens that starting next Monday my age will be equal to Douglas Adams’s answer to life, the universe, and everything: 42. I am way too old to be a baby Purple Squirrel! But this old lady, in addition to rocking the purple, is rocking the technology and she is not at all retiring! One funeral at a time? If you want my funeral, you’ll have to engineer it.

But again, I have to ask, what is attractive or useful in this pair of myths? Why don’t more people push back on One Funeral at a Time? Nobody wants people rooting for them to die! And to answer that, I keep coming back around to that knowledge-ignorance dichotomy that the myths exemplify. We oldsters, we’re tech-ignorant, while those youngsters, well, they just automagically know everything about technology. Both these myths construct knowledge as innate: you either got it or you don’t. You either have infinite technology knowledge essentially from birth, if you’re a Purple Squirrel, or you don’t know anything about technology and never will, if we’re waiting for your Funeral. Nothing to be done about it either way, it’s just the way we are, right?

And that is what is attractive to a subset of established professionals in both our professions! It lets them get away with what I call being “ignorant like a fox,” the kind of person who just loves Purple Squirrels so much because technology is so hard and they just don’t understand it and they never will either because it’s so hard so it’s so great there are Purple Squirrels to do that scary hard tech stuff for them! Or the person who blusters, “well, I’m far too important to do that icky tech stuff, go hire a Purple Squirrel for that.”

These people are not myths. I know some. I’m betting you do too. And it’s not everybody, but it’s enough people to do real damage! Put another way, some established professionals cynically buy into One Funeral at a Time, grossly insulting and wrong though it is, because it’s a Get Out of Technology Free card. Or, if we want to think about this as educators, a Get Out of Learning Technology Free card.

Remember the skeevy gross echoes of workplace mistreatment I was talking about? It’s the ignorant-like-a-fox folks who do ninety percent of the damage here, I really believe that! Ignorant-like-a-fox folks will write job ads for Purple Squirrels, and they’ll hire them because they need them, but it’s exactly these ignorant-like-a-fox folks who have a way of not thinking of Purple Squirrels as fellow professionals, much less colleagues. They’ll talk smack about Purple Squirrels behind their backs because hey, Purple Squirrels are not Real Lawyers or Real Librarians, right?

That’s the gross, skeevy, insidious thing about this. A thing foxes refuse to do, often because they don’t know how and refuse to learn, they also refuse to respect or reward other people for doing. Take social media. A fox might “dabble” in social media, and then write snide editorials about it. Someone the fox respects might be “engaged” with social media. Purple Squirrels? What’s the word in those snide editorials? Yes, I’m hearing it: “obsessed.” I dabble, you engage—they’re obsessed.

And that’s how Purple Squirrels, and tech-savvy people generally, end up as workplace targets. This is not acceptable and it’s got to stop.

So granting that these myths are a problem, what do we do? How do we shatter the myth of the Purple Squirrel and replace it with healthier technology behaviors and attitudes? I think a couple of very simple ideas will do the job, if—if—we can push them as hard as everyone else is pushing Purple Squirrels and One Funeral at a Time, and if we are willing to live with the consequences of those ideas.

Here’s one such idea: knowledge of technology is not innate, but learned. Whether it’s learned through experience or instruction or both, technology knowledge is learned. Simple, right? True, right? And it blows up the Purple Squirrel myth on the spot. Old people, young people, nobody’s born knowing how to develop mobile apps or troubleshoot Excel. We all learn how.

Here’s another idea: you don’t learn tech once and you’re done, any more than you learn law or librarianship and you’re done. None of these is a fixed body of knowledge; they’re all changing, so we’ve always got to be learning and relearning. All of us. And I’m preaching to the choir here, I know that, so what we here have to do is spread the word. If that means we’re knocked off our Infallible Know-it-all Purple Squirrel pedestals, it’s worth the price, because the emphasis on continuous learning is what gets the ignorant-like-a-foxes in the gut. If everybody has to learn, then so do they. There is no more get-out-of-tech-free card.

But, you know, we’re not going to be able to turn our ignorant-like-a-fox folks into Purple Squirrels. You know, I know, we all know that’s not going to happen. And anyway, Purple Squirrels don’t actually exist, so we need another symbol for an acceptable professional level of technology knowledge.

So how about a nice gray squirrel? Let’s envision technology education for law and librarianship as the cultivation of regular, ordinary gray squirrels. Gray squirrels are actually pretty amazing creatures in their own right. First of all, they’re real—they actually exist! And those of us with birdfeeders aside, we have tolerably warm and fuzzy feelings toward gray squirrels; we think they’re fun to watch, even cute. Even more importantly, gray squirrels are ubiquitous, absolutely everywhere; they fit into a lot of environments, and they are absolute masters at adapting themselves to what they find. That’s what we ultimately want from professionals with respect to technology, right? We want them to adapt to what they find. We want them to fit in technologically wherever they happen to land. We want them to survive just about anything the changeable technology world can throw at them. And we want everybody to feel empathy and respect toward gray squirrels doing technology work, which is a lot easier if everybody feels that we’re all basically climbing the same tree with regard to technology.

I want to close with some suggestions about how all of us, educators and working professionals, can make more gray squirrels.

The first thing our professions need to do is commit, commit one hundred percent, to this goal: every professional a gray squirrel! Every lawyer, every librarian. Not after a billion funerals, either—now, today, or at least as soon as we can make it happen. Ink still wet on your diploma? You need to be a gray squirrel. Had your diploma hanging in your office so long that the dust on it’s an inch thick? Guess what? You, too, need to be a gray squirrel.

Now, that’s easy for me to say; it’s much, much harder to do! But I do think that even if this goal turns out to be mythical, keeping it as a mission statement is useful, because it will kick us out of some of the bad habits of thought that led to the myths I’ve debunked today. An example of such a bad habit is the “curricular rigor in the degree” kick some people are on, this idea that we’ll graduate a whole lot more Purple Squirrels if we just make everything really really difficult. I really need people to get off this, at least with respect to technology education. If you think I’m saying this to make my life as a technology educator in a degree program easier—well, yes, and then again, no.

Yes, because asking me for “rigor” in my technology teaching boils down to the same old “hey, where are all those Purple Squirrels? You’ve got three years, where are those Mo Farahs you promised us?” I’ve been hearing all along. And it totally ignores everybody who’s done with their degree, which lets them play the ignorant-like-a-fox game. If that’s not enough, here’s one more reason the rigor kick isn’t cool: we know that technology knowledge, even technology access, is conditioned by societal disadvantage accruing to certain demographic groups. Digital divides are emphatically not a myth. The notion that tech is some kind of meritocracy that’s open to everybody equally, that is the myth.

So if what people mean by “rigor”—and it does seem to be—is weeding students out because they don’t achieve Mo Farah levels of tech knowledge in two or three years, these people are asking me to contribute to disadvantaging women, people of color, the non-wealthy, first-generation students, rural residents who can’t get broadband, and others. These people are telling me that such students can’t be part of our professions, and it’s my job to make sure they don’t become part. And I refuse. I flatly refuse to do that. It is wrong and I refuse.

Will I take on the job of making people who have been disadvantaged for whatever reasons into gray squirrels, rather than purple ones? Sure! I think I can do it, and I think it’s what both they and our professions need a lot more than they need “rigor,” whatever that is when it’s not being exclusionary. So yes, a gray-squirrel approach to technology would make my life as an educator in a degree program easier.

But then again, no, a gray-squirrel approach to tech knowledge will not make my life easier, because it means we educators will seriously have to step up our continuing-education game! Both our professions have to get profoundly serious about true lifelong learning in a way I know they’re not right now! That scares the daylights out of me, because it will be so hard: hard to pay for, hard to deliver, hard to work out the right pedagogies for, hard to lead the horses to water and make them drink (as long as I’m on the animal-metaphor kick), just really, really hard. While I do not want to minimize those difficulties one bit, I still believe with all my heart that the gray-squirrel approach will get better results than the blame-the-degree, blame-the-educators quagmire we’re stuck in right now. I think whatever progress we can make will be worth it!

Another thing we’re going to have to do to make gray squirrels is calibrate our expectations properly. And for me, that means going from competency laundry lists, which as I said tend to be total Purple Squirrel fantasylands, to competency roadmaps, the Open Street Map of competency development. Roadmaps acknowledge where people start, as well as where we want them to end up, and roadmaps give them actual directions for how to get to where we want them to end up. They even take into account how people are travelling—if you’re driving, you’ll get a different route than if you’re walking. Learning works the same way. People start from different places and they have different needs, and a roadmap approach can account for that where a competency list can’t. There’s just a lot more embedded advice, a lot more usable wisdom, in a map than in a list—and let me tell you, the number of people I’ve seen in library continuing education who desperately need some advising and some direction because they don’t really know what they’re doing or where they’re going? I won’t tell stories on people because that’s super-hurtful, but I am telling you, it’s scary.

So sure, it’s a heck of a lot easier to just make that gigantic Purple Squirrel competency wishlist, but it’s not nearly so helpful, and it’s not grounded in professional reality.

The third thing we need to do is bust yet one more myth, one that is a real barrier for long-time professionals who are not where we wish they were in their technology knowledge. The myth is a broken syllogism, thus Aristotle here with his terrifyingly guilt-inducing empty eyes, and it goes like this:

  1. Smart people know technology.
  2. I am a smart person.

And that’s where the syllogism breaks, because they don’t know technology. This hits my students pretty hard sometimes; I’ve seen it. They feel guilt. They feel shame. They feel the kind of I’m-just-a-fraud inadequacy that research calls Impostor Syndrome. I can only imagine it’s worse for longtime professionals, and the worst thing about that is that these feelings keep them from learning! So if we’re seriously planning to deal with the low level of tech knowledge in our fields, we must acknowledge and then deal with this broken syllogism, both in our degree programs and in continuing education.

And that brings me back around to the couch-to-5K idea. If you look at the very best how-tos for doing a couch-to-5K, you’ll notice that there’s no blame-and- shame in them, there’s no fat-shaming or fitness-policing or anything like that, and no one makes assumptions about why you’re doing it. You want to do a 5K? Great, here are the clearest, most specific instructions we can make for how to get there from wherever you happen to be. And rah rah you for doing it!

We need that in continuing technology education, in both our professions. I’m thinking it will unfortunately take some strategic pushing, maybe even sometimes a little blame, to get the ignorant-like-a-fox folks past that broken syllogism to seek training, never mind people who have been systematically disadvantaged or who are just afraid. But once they’ve taken that step? No blame. Ever. No shame. Ever. No judgment. Ever. We meet them wherever they’re at, and we help. That means a lot of us who pride ourselves on our Purple Squirrelishness will need to check our dismissive attitudes at the classroom door.

So this is the vision that I hope to see some strategy work on, right here at this conference: how to turn every single professional in both our professions into a capable, adaptable gray squirrel with a whole lot of gray-squirrel friends. I want this because… well, let me just end this with a shout-out to CALI’s own delightful Sarah Glassmeyer—I am so done with this creepy-ass mofo of a Purple Squirrel here!

Thank you very much, thanks to John and Sarah for inviting me, and Jason Scott for handing me that great opening line on a silver platter, and now let’s CALI on!