This week’s map visualizes Canada’s unemployment rates for October 2014, which were announced last week:
I coded this map with trepidation since comparing unemployment rates across provinces isn’t always as important as considering one province’s current rate against its own historic numbers. For example, this map shows us that Ontario’s unemployment rate still lags behind Alberta’s. No surprise there. What the map cannot do, though, is show that Ontario’s unemployment rate for this month – 6.5% – has finally recovered since the Sept 2008 crash. The last time Ontario’s unemployment rate was this low was in October 2008. To best visualize the province’s unemployment trend back to pre-recession numbers, one should simply chart the data, or even just give the real numbers in tabular format. The best way to do this on the web is with charts.js, which seems to be some of the easiest coding I’ve ever seen. That will be my project for later this week.
This week, I’ve taken the same population density variable I used last week and plotted it for Brantford, Ontario. I’ll be speaking about open StatCan data to our journalism students in Brantford in a few days’ time, so it was only fair to plot the same variable for our students in this city, too.
One of my sidebar projects this fall has been to get back into mapping socio-economic data. This is something I used to do quite a bit four years ago (these maps have sadly succumbed to linkrot and plugin abandonment). Projecting numeric data onto maps is easier than most people think, and ever since I moved to a new city in 2013, I planned to pick up this skill again to learn a few things about my new town. And as a data librarian, I know where to find and work with census data, so it was easy to kickstart things into gear once more.
The interesting thing about this map isn’t so much its colorful polygons, (based on statistics anyone can download here) but the tools I used to build it. When I was creating maps in 2010, the average person who wanted to hack something out was limited largely to using Arc on his or her campus, or using the open source (and still maturing) variant, QGIS, or working with Google Maps. These days, QGIS is very mature and has a strong developer community, GMaps is still going strong, and users can use services such as Mapbox’s TileMill. The options to choose from are stronger, and there is an option that can meet your background, whatever it may be.
As an example, I’m linking over to Mita Williams’s recent work mapping population change in Windsor, Ontario, as well as making the case for electoral change in her hometown. Mita is a UX librarian and far more of a coder than I’ll ever be, so her recent work with maps shows a freer hand at hacking out java to make things go, while I use plugins within QGIS to automate some of the coding for me, which frees up my time to spend on analysis.
At the end of the day, our maps are projected with the same code and with data from the same datasets, so our endpoint is the same, but the tools we’ve chosen to use may be better suited to our own particular abilities. That is something I didn’t see in 2010 as much as I see today. And that change is a good thing. Getting these datasets into the hands of the masses, and then making them usable and understandable for everyone, is crucial to the precepts of openness – open access, open government, open data – that we espouse as librarians. One can have completely open access to data, but its value is lessened when it cannot be used or understood by all of society. Yes, open data is a crucial part of today’s citizen-to-citizen and citizen-to-government relationships, but the more tools people have to work with that data, the better.
This week, my article on research data management and collaboration inside and outside the academic library was published in Partnership. And here’s my shameless plug: you should go read it now. The article examines the different facets of research data management – collection, access, use, and preservation – and it locates them within the different part of the academic library. It is also advocates for real collaboration with our peers and stakeholders across the entire university, such as our colleagues in Research Offices and Research Ethics Boards (IRBs for our American friends).
The article also examines the current policy gap regarding RDM in Canada, as well as ongoing efforts by different groups to develop RDM provisions in our granting formulas, and to provide resources and share expertise in order to ensure that we don’t create a paper tiger. What’s needed is not just policy but action, and both must be considered in the same breath.
Here’s the article’s abstract:
Research data management (RDM) has become a professional imperative for Canada’s academic librarians. Recent policy considerations by our national research funding agencies that address the ability of Canadian universities to effectively manage the massive amounts of research data they now create has helped library and university administrators recognize this gap in the research enterprise and identify RDM as a solution. RDM is not new to libraries, though. Rather, it draws on existing and evolving organizational functions in order to improve data collection, access, use, and preservation. A successful research data management service requires the skills and knowledge found in a library’s research liaisons, collections experts, policy analysts, IT experts, archivists and preservationists. Like the library, research data management is not singular but multi-faceted. It requires collaboration, technology and policy analysis skills, and project management acumen.
This paper examines research data management as a vital information, technical, and policy service in academic libraries today. It situates RDM not only as actions and services but also as a suite of responsibilities that require a high level of planning, collaboration, and judgment, thereby binding people to practice. It shows how RDM aligns with the skill sets and competencies of librarianship and illustrates how RDM spans the library’s organizational structure and intersects with campus stakeholders allied in the research enterprise.
For what it’s worth, collaboration has been a real buzzword at IASSIST40 and I’ve already been to a few presentations that share similar arguments as mine, and which definitely have the same spirit. I hope we’re all on to something with this, and I hope that we in Canada can get up to speed with our counterparts in other countries.
Finally, this paper began in part from an Introduction to RDM session that I co-presented with Jeff Moon of Queen’s University at OLA in January 2014 (details here). Jeff has also written a great article on research data management, and it appears in the same issue of Partnership. He is on the forefront of RDM in Canada and knows how to get things done, so be sure to read his work, too.
(n.b.: This post about my RDM co-presentation at the 2014 OLA SuperConference is very, very late. I had decided to let it go in February and not publish it. However, now that the term is winding down and I’m finding time to look back on the past three months, I’ve noticed that the event still sticks out in my mind, so I’ve decided to present the slides to everyone. -m.)
In January 2014, I co-presented a session, Research Data Management: an Introduction, at the OLA SuperConference in Toronto. Working with Jeff Moon of the Queen’s University Library, we led a thorough session on RDM basics to the crowd. Jeff, always the great teacher that he is, spoke first by introducing RDM – what it means in terms of stewardship and infrastructure, its place within Canadian librarianship, how it is implemented, etc. The Queen’s Library has developed a great model for RDM through the work of Jeff and Alex Cooper: it is scalable, it is built on local and consortial resources, and it develops in-house knowledge. It is one of several RDM units that Canadian librarians should investigate when considering RDM, in my opinion.
I followed Jeff by discussing RDM within the organizational context of the library and the university. In many ways, RDM touches upon all the “traditional” library functions: acquisitions and collections, access, reference and research, preservation, IT, etc., and I firmly believe that an RDM programme can’t fully succeed without engendering collaboration with colleagues from all these areas. Not all of our libraries have a wealth of resources to develop our RDM programmes, but we certainly aren’t going to get good mileage if we can’t bring together all library functions to develop our data collection infrastructure and use our information management expertise to serve this pressing need within the Canadian research enterprise.
There were two other major points I touched on in the presentation, which I want to reiterate in text. First, a strong RDM programme is going to require buy-in from your entire team of librarians, including liaison librarians. As others have noted (e.g.: Witt, Hswe and Holt;, Gabridge,) liaisons are our colleagues with subject expertise and with developed networks within their departments. Furthermore, when RDM eventually becomes a Tri-Council obligation (as I expect it to become), we are going to require help from liaisons to make sure that we don’t drown in a deluge of work. Secondly, make sure you reach out to your campus Office of Research Services, your IT Services, and to your Research Ethics Boards. These groups are allies, they are valued stakeholders on campus, and they have a wealth of expertise in the research enterprise. Research Data Management is not the domain only of librarians, and we can’t forget that. RDM requires our colleagues across campus, both in the faculties and in administrative units. I hope to write more on this during the spring since I’m working on this particular area at the moment myself.
You can find slides from our presentation at this link, under Session 413, and I’ve embedded mine below. (And yes, it was a damn fine cup of coffee.)
I’m stating the obvious by telling you that September is a busy month in academics. The start of the school calendar changes the mood, tempo, and pulse of a university campus, and it shifts things at the library into full gear as we roll out all programming and services. Here are a few of the things I’ve been contributing to lately, which has kept me busy in a good way (as opposed to the bad kind of busy).
Changing liaison duties
I’ve taken on liaison duties in Sociology and Social Work while a colleague is on sabbatical this year, and I’m also part of a group that is expanding the Library’s services to the University’s students who are cross-registered at the Balsillie School of International Affairs. This has already translated to a large increase in my in-class instruction, especially for Social Work, which is its own Faculty and has its own small library. Taking on these subject-based duties has been a great opportunity since they’ve given me greater everyday contact with faculty and researchers whose work touches on socio-economic data or would benefit from research data management support and consultation. Simply put, it’s a lot easier to push data management planning when you already have a built-in relationship with the researcher, so I expect my subject-based work in Sociology and Social Work to benefit our RDM programme.
Outreach to Faculty and Students
This term, I’m offering a full slate of seminars on research data management, bibliometrics, and data access through the library. I developed these seminars with a graduate student/faculty audience in mind, partly to help the Library increase its presence within graduate programming and in the university’s research enterprise. While I don’t expect large numbers because this is the first time in a few terms that we developed a suite of seminars with graduate or faculty research in mind, I do hope they begin to build on our growing profile as a center of research facilitation on campus. (This could be a blog post in its own right; I may have to write more on it in the future.)
Our Library has taken a close look at RefWorks and has also considered what kinds of citation management systems our users use. What we’ve known all along is that many people use RefWorks and many people do not. We asked ourselves why we commit our support only to one service when our users will always work with their personal preferences in mind, and we decided that giving information and advice on RefWorks alone just doesn’t cut it. If we are to support or know something about citation management and research management, then we shouldn’t limit ourselves to only one tool. Going forward, our library is now supporting RefWorks, Zotero, and Mendeley by offering instructional sessions, consultation, and in some cases, even research collaboration between the researcher and the librarian through these tools
Data and Statistics
Don’t think that this project or the next (RDM) are subordinated to the others I’ve mentioned because they’re at the bottom of this list. That’s far from the truth as both areas have seen significant change in the past few months. On the Data and Stats side alone, data librarians in Canada are busy dealing with a new EULA for Canada Post postal code products (e.g., the PCCF) and what it means for researcher access and use. This issue alone has eaten up probably half of my time in the past two weeks since the new EULA changes long-standing practices for researchers who use these products, and the library, which administers licences on their behalf. A lot of time has been given to consultation within the data community and within the library to produce new practices, and I’m now rolling out a PR and education campaign. If you are Laurier faculty and use postal code products, be on the look out for more news on this very shortly. If you’re faculty at another university in Canada, you may want to contact your own data librarian.
Research data management
RDM has been the largest part of my work at Laurier. We’ve been developing a research data management programme, based largely on consultative support that helps researchers and research groups learn about and then develop flexible data management plans that speak to their current and future research needs. Next month, I’ll be attending CASRAI’s ReConnect2013 conference to build upon my current knowledge and to see and learn what others are doing in this area across Canada and in other jurisdictions. We have a couple of RDM projects on the go already, and I would like to increase that number on campus since the service the Library provides offers clear benefits to the researchers in terms of meeting funding obligations, providing research management planning, and improving access to and citation of produced work after the research has ended. Laurier researchers: let’s chat.
It’s that time of year when more and more students are asking about accessing datasets for their research through our local Research Data Centre. And a couple times now, I’ve found myself having to explain that one does not simply walk into an RDC…
Happy Spring! We’re almost there, people, I promise.
I’m beginning this post with that statement since it recalls an entry I wrote last year about taking on a limited term appointment as Wilfrid Laurier University’s Government Information Librarian. It was a rather productive year as the GovInfo Librarian, and I loved my time in the job. Moving to Ontario gave me the opportunity to meet many colleagues in Canadian LIS who I would otherwise only get the briefest introductions to at national conferences. It also meant shifting “consortial cultures” as I moved from a CAUL province to an OCUL province and had to learn a brand new vocabulary of committee names and acronyms. And it also meant having to re-learn what “hot, hazy, and humid” means, let alone the value of central air.
But I digress, it was a pretty good year. The past 12 months has been full of new colleagues and friends, introductions to new scholarly resources, publishing and speaking opportunities, and a chance to “make a difference” at the workplace. Sometimes, you leave the office later in the day than you intended, but you leave later because you really do enjoy your work. And that’s a good thing.
Like February of 2012, February of 2013 was a month of changes, and March 2013 is a month of announcements. I’ve now accepted an appointment as the Laurier Library’s Data Librarian. Needless to say, I’m quite excited by this news and can’t wait to get the ball rolling. One of my main responsibilities in this portfolio is to help develop the Library’s research data management infrastructure and to facilitate research data access, usage, and collection on campus and in the communities we serve. There are some big steps involved, but my plan is to leverage the knowledge gained at CARL’s RDMI summit in January 2013 as we roll out services and resources to students, staff, and faculty on at Laurier.
Reports will follow, as they have in the past. (I’ve thought about starting a brand new blog to collect my thoughts on data management together in one place. I’ll post a link here if I do.) In the mean time, I’ll leave you first with a link to the photoblog my spouse and I maintained while work forced us to live in different provinces for an entire year – check it out: I must say we did an awesome job. And I’m also going to leave you with some YouTube clips. It’s impossible to talk about being a data librarian without making a Star Trek reference:
And also this one. When talking about living in Waterloo, ABBA will sooner or later be mentioned. Without fail..
1. Research Data Management, Data Lifecycles, and Research Data Lifecycles
What is research data management? I won’t go into textbook-detail suffice to say we’re talking about systematic practices that govern how research data are defined, organized, collected, used and conserved before, during, and after the research process. That sentence is a mouthful and it covers a lot of ground, so I suggest you look to Chuck Humphrey’s Research Data Management Infrastructure (RDMI) site for a more focused definition. Chuck is hailed in Canada for his data management expertise, and he led many sessions at the workshop. He explains that:
Research data management involves the practices and activities across the research lifecycle that involve the operational support of data through design, production, processing, documentation, analysis, preservation, discovery and reuse. Collectively, these data-related activities span the stages of project-based research as well as the extended stages that tend to be institutionally based. The activities are about the “what” and “how” of research data. (source)
Chuck’s website is a great introduction to the existing RDM gap in Canada, and we referred to it several times in the course. It neatly summarizes key information such as the shaky progress and history of RDM in Canada, where the Canadian RDM community stands in the world today, the differences between data management and data stewardship, and why the Canadian research community should focus its attention on building infrastructure to support RDM as opposed to building a national institution to guide it.
Beyond talking about what RDM is and isn’t, we spent a lot of time studying where RDM sits within the research lifecycle. Many people are familiar with the data lifecycle model since it introduces us to the many facets of data management, however, the CARL course proposed that we instead examine data management practices as an integral part of the larger research lifecycle. Rather than focusing only on data at the expense of the larger research project, the course facilitators asked us to apply RDM within the entire research process, using the following model from the University of Virginia:
The salient point is that research data management isn’t limited to only the data life cycle; it affects the entire research process. (A simple example: data management strategies should be discussed well before data are created or collected.). Furthermore, if we want to develop sound RDM practices, we need to think like the researcher, understand the researcher’s needs, and include our work within their processes. If you’re not working with the researcher, then your RDM plan isn’t working.
2. Local RDM Drivers and Activities
If understanding what research data management is and where it affects the research process was one takeaway of the course, analyzing our local data environments was another:
RDM drivers, such as your library’s consortial collaborations, number of staff, existing IT relationships, administrative support, etc., are the parameters that shape and support your local RDM programme.
The activities in your RDM programme, meanwhile can be broadly categorized into the four areas: collection, access, use, and preservation (note: activities can fall into more than one category, and the order is not linear).
Discussing the things that affect our data landscapes and the activities we could perform helped us understand what is possible at our own libraries. I think a lot of us found this useful because all of our unique circumstances (e.g., library and university sizes, existing infrastructure and knowledge, etc.) can make RDM a bit nebulous at times. Although our focus is the same – RDM – our individual goals and aims might be different – are we building our technical capability, or are we designing soft systems that focus on relationships? Are we only collecting new locally created data, or will we also gather existing, completed projects? The answers are going to depend on your local situation.
The course facilitators were careful to help participants understand RDM as a necessarily scalable enterprise. Don’t create a monster RDM plan. Instead, contextualize your local RDM drivers and your library’s capabilities and desires so that you can mitigate the risks of creating an RDM plan that doesn’t fit your organization. The aim is to create a system and process that brings clear benefits to the researchers.
3. Planning… and Doing
The final takeway from the CARL RDM course, which you may have noticed I’ve been building up to, was straight-up, no-nonsense, get’er-done planning. The course facilitators built opportunities for real action into the course, which is probably one of the best parts of the week. Generally speaking, the academic enterprise undertakes a lot of talk and high-level planning before things happen. This is often a good thing (read: I demand critical inquiry), but it can also stifle action (read: I despise institutional inertia). However, this CARL course found a way to bring together discussion and action. It gave us theory, but it demanded practice. Before the week was out, we had all talked about 3-year planning, considered how such a plan might look locally, and started to write one. Of course, these drafts aren’t ready for prime time, but my point is that before I came back to the office on Monday, I already had written the skeleton of a research data management plan that shows my library’s potential RDM activities and stakeholders, outlines activities and scopes, and offers timelines and deliverables. It didn’t make me an expert (and neither do I claim to be one), but it did offer some tools to help the library step out and make positive change.
So was the CARL RDM course money well spent? It sure was. It’s not too often you come back from an event with a new community of practice, insight on a vital part of the research enterprise, and a plan to put everything in action. Hat’s off to the course facilitators for putting on such a great week – I think you’ve started something necessary, and good, for Canadian research.
(And some time next week, I’ll start gathering up some of the key readings from some of the bibliographies they presented us… I’ll try not to turn the next post into a lit review, but it may come close to it.)