Low Expectations Distributed: Yet Another Institutional Repository Collection Development Workflow

Anyone who has worked on an institutional repository for even a short time knows  that collecting faculty scholarship is not a straightforward process, no matter how nice your workflow looks on paper or how dedicated you are. Keeping expectations for the process manageable (not necessarily low, as in my clickbaity title) and constant simplification and automation can make your process more manageable, however, and therefore work better. I’ve written before about some ways in which I’ve automated my process for faculty collection development, as well as how I’ve used lightweight project management tools to streamline processes. My newest technique for faculty scholarship collection development brings together pieces of all those to greatly improve our productivity.

Allocating Your Human and Machine Resources

First, here is the personnel situation we have for the institutional repository I manage. Your own circumstances will certainly vary, but I think institutions of all sizes will have some version of this distribution. I manage our repository as approximately half my position, and I have one graduate student assistant who works about 10-15 hours a week. From week to week we only average about 30-40 hours total to devote to all aspects of the repository, of which faculty collection development is only a part. We have 12 librarians who are liaisons with departments and do the majority of the outreach to faculty and promotion of the repository, but a limited amount of the collection development except for specific parts of the process. While they are certainly welcome to do more, in reality, they have so much else to do that it doesn’t make sense for them to spend their time on data entry unless they want to (and some of them do). The breakdown of work is roughly that the liaisons promote the repository to the faculty and answer basic questions; I answer more complex questions, develop procedures, train staff, make interpretations of publishing agreements, and verify metadata; and my GA does the simple research and data entry. From time to time we have additional graduate or undergraduate student help in the form of faculty research assistants, and we have a group of students available for digitization if needed.

Those are our human resources. The tools that we use for the day-to-day work include Digital Measures (our faculty activity system), Excel, OpenRefine, Box, and Asana. I’ll say a bit about what each of these are and how we use them below. By far the most important innovation for our faculty collection development workflow has been integration with the Faculty Activity System, which is how we refer to Digital Measures on our campus. Many colleges and universities have some type of faculty activity system or are in the process of implementing one. These generally are adopted for purposes of annual reports, retention, promotion, and tenure reviews. I have been at two different universities working on adopting such systems, and as you might imagine, it’s a slow process with varying levels of participation across departments. Faculty do not always like these systems for a variety of reasons, and so there may be hesitation to complete profiles even when required. Nevertheless, we felt in the library that this was a great source of faculty publication information that we could use for collection development for the repository and the collection in general.

We now have a required question about including the item in the repository on every item the faculty member enters in the Faculty Activity System. If a faculty member is saying they published an article, they also have to say whether it should be included in the repository. We started this in late 2014, and it revolutionized our ability to reach faculty and departments who never had participated in the repository before, as well as simplify the lives of faculty who were eager participants but now only had to enter data in one place. Of course, there are still a number of people whom we are missing, but this is part of keeping your expectation low–if you can’t reach everyone, focus your efforts on the people you can. And anyway, we are now so swamped with submissions that we can’t keep up with them, which is a good if unusual problem to have in this realm. Note that the process I describe below is basically the same as when we analyze a faculty member’s CV (which I described in my OpenRefine post), but we spend relatively little time doing that these days since it’s easier for most people to just enter their material in Digital Measures and select that they want to include it in the repository.

The ease of integration between your own institution’s faculty activity system (assuming it exists) and your repository certainly will vary, but in most cases it should be possible for the library to get access to the data. It’s a great selling point for the faculty to participate in the system for your Office of Institutional Research or similar office who administers it, since it gives faculty a reason to keep it up to date when they may be in between review cycles. If your institution does not yet have such a system, you might still discuss a partnership with that office, since your repository may hold extremely useful information for them about research activity of which they are not aware.

The Workflow

We get reports from the Faculty Activity System on roughly a quarterly basis. Faculty member data entry tends to bunch around certain dates, so we focus on end of semesters as the times to get the reports. The reports come by email as Excel files with information about the person, their department, contact information, and the like, as well as information about each publication. We do some initial processing in Excel to clean them up, remove duplicates from prior reports, and remove irrelevant information.  It is amazing how many people see a field like “Journal Title” as a chance to ask a question rather than provide information. We focus our efforts on items that have actually been published, since the vast majority of people have no interest in posting pre-prints and those that do prefer to post them in arXiv or similar. The few people who do know about pre-prints and don’t have a subject archive generally submit their items directly. This is another way to lower expectations of what can be done through the process. I’ve already described how I use OpenRefine for creating reports from faculty CVs using the SHERPA/RoMEO API, and we follow a similar but much simplified process since we already have the data in the correct columns. Of course, following this process doesn’t tell us what we can do with every item. The journal title may be entered incorrectly so the API call didn’t pick it up, or the journal may not be in SHERPA/RoMEO. My graduate student assistant fills in what he is able to determine, and I work on the complex cases. As we are doing this, the Excel spreadsheet is saved in Box so we have the change history tracked and can easily add collaborators.

Screen Capture from Asana Setup
A view of how we use Asana for managing faculty collection development workflows.

At this point, we are ready to move to Asana, which is a lightweight project management tool ideal for several people working on a group of related projects. Asana is far more fun and easy to work with than Excel spreadsheets, and this helps us work together better to manage workload and see where we are with all our on-going projects. For each report (or faculty member CV), we create a new project in Asana with several sections. While it doesn’t always happen in practice, in theory each citation is a task that moves between sections as it is completed, and finally checked off when it is either posted or moved off into some other fate not as glamorous as being archived as open access full text. The sections generally cover posting the publisher’s PDF, contacting publishers, reminders for followup, posting author’s manuscripts, or posting to SelectedWorks, which is our faculty profile service that is related to our repository but mainly holds citations rather than full text. Again, as part of the low expectations, we focus on posting final PDFs of articles or book chapters. We add books to a faculty book list, and don’t even attempt to include full text for these unless someone wants to make special arrangements with their publisher–this is rare, but again the people who really care make it happen. If we already know that the author’s manuscript is permitted, we don’t add these to Asana, but keep them in the spreadsheet until we are ready for them.

We contact publishers in batches, trying to group citations by journal and publisher to increase efficiency so we can send one letter to cover many articles or chapters. We note to follow up with a reminder in one month, and then again in a month after that. Usually the second notice is enough to catch the attention of the publisher. As they respond, we move the citation to either posting publisher’s PDF section or to author’s manuscript section, or if it’s not permitted at all to the post to SelectedWorks section. While we’ve tried several different procedures, I’ve determined it’s best for the liaison librarians to ask just for author’s accepted manuscripts for items after we’ve verified that no other version may be posted. And if we don’t ever get them, we don’t worry about it too much.


I hope you’ve gotten some ideas from this post about your own procedures and new tools you might try. Even more, I hope you’ll think about which pieces of your procedures are really working for you, and discard those that aren’t working any more. Your own situation will dictate which those are, but let’s all stop beating ourselves up about not achieving perfection. Make sure to let your repository stakeholders know what works and what doesn’t, and if something that isn’t working is still important, work collaboratively to figure out a way around that obstacle. That type of collaboration is what led to our partnership with the Office of Institutional Research to use the Digital Measures platform for our collection development, and that in turn has  led to other collaborative opportunities.