Today my Director sent me a link to the latest EDUCAUSE survey of IT use by academics [1]. This has a strong focus on teaching and learning, but is still very much of interest to those of us involved in research support.

More than 17,000 responses from academics in 13 countries were received and the results are great reading. One of the report's key findings is that

The majority of faculty rely on the institution’s help desk for technology support.

According to the report, nearly three quarters of academics  go to the help desk for tech support, 

followed by the crowd-sourced “Hey, Joe!” approach of asking peers or colleagues (57%) and the do-it-yourself method of just Googling solutions (45%).

A couple of weeks ago, I was invited to speak to an Australian National Data Service data intensive for staff from regional and teaching-intensive universities about change management in the context of research data support. I talked a bit about the work that I have been doing to get my university prepared for the launch of our new research data storage service. At one point I asked the attendees in the room - a mix of librarians, IT and research managers - to think about what advice a researcher in their institution would get if they called up the university's IT helpdesk to ask for research data management help.

The reason I asked this is because, although I have worked supporting research data management for the past seven years, it is only in the last three months that I have ever actively worked with my organisation's helpdesk team to ensure that they are aware of a new service and are fully equipped with the information they need to be able to resolve basic queries and make referrals to the correct people where a query is more complex.

This work has been part of the process of developing an operational support plan that makes the roles and responsibility for the different tiers of support (from self-help materials through to consultation and technical troubleshooting) very clear. A significant amount of effort has been involved in this, including:

• A briefing meeting with the manager of the help desk and the team leader of the staff that answer queries
• Developing a new category for research storage within our service desk software and ensuring that automated queries from the Contact Us form were routed correctly 
• Completing a handover checklist document, which outlined 
• the purpose of the new service
• details for how to resolve common queries that might come through
• how to make a referral for a query that could not be resolved by the help desk
• Discussing training needs with the team leader and then providing four information sessions to staff from the helpdesk team
• Providing information regularly to the team leader about updates to the service and associated changes to the documentation (FAQs and user manual) that the helpdesk staff need to be aware of. 

All of this work was new to me, and it has been a real eye-opener. As data librarians or eResearch support professionals, many of us seem to be seeking to establish ourselves as the "single point of contact" for data management inquiries. Particularly for librarians, there is a push to be the friendly face of data management support in our institutions. It's true that librarians have networks that enable us to make serious inroads in terms of advocacy and I think the attempt to become the single point of contact for research data advice is being done in good faith; we hope this will prevent researchers from getting bounced from pillar to post as they try to find the right person to help them.

But really, shouldn't we also make the best use we can of the single point of contact that already exists and is used by the majority of our researchers right at the point when they decide they have a problem? Don't miss out, as I now realise I have for the last seven years, on the opportunity to partner with the people who are probably most likely to receive that call for help.

References

Dahlstrom, E. & Brooks, D.C., 2014. ECAR Study of Faculty and Information Technology, 2014., EDUCAUSE Center for Analysis and Research. Available at:
http://net.educause.edu/ir/library/pdf/ecar_so/ers/ers1407/ers1407.pdf. (subscriber-only for the first five months after publication)

Well, it's the last day of June and that means no more #blogjune after today. It's been great to be a part of #blogjune and thanks again to Con Weibrands (@flexnib) for organising this and all the other participants for inspiration along the way.

I managed to post every day during the month, which I feel really proud about. I now have ten times more posts on this blog than I did before! There were definitely some factors that helped with this, such as my partner being away which meant lots of quiet evenings at home without things like Game of Thrones and Scrabble for distraction!

I also spent more time reading blogs than I ever have before. My RSS reader was pretty empty before #blogjune; it's become a regular part of my day to read blog posts on my morning commute and I think that will continue and probably grow.

I've learned quite a lot about blogging and about myself through this process. In no order whatsover, the things I have found out are:

I'm a nightowl

I did already know this but it's interesting to observe it while doing something as intense as #blogjune. I tried to write a couple of posts during the daytime but mostly I posted after 10pm. I've always found late at night to be my most productive time for creative endeavours. Had I not had to go to work I'm sure that I would have been blogging even later and posting at 2am!

Lots of other people aren't nightowls

Just because I post at midnight doesn't mean that's when I should send the tweet out about it! I realised that if there was a post I really wanted people to read that I needed to wait until they were actually awake to notify them about it. It was a good prompt to learn how to schedule tweets anyway.

All my traffic comes from Twitter

I have plenty of things to write about

Before #blogjune I started gathering a list of possible topics so that I would never be faced by the blank screen. I did look at this list seven times during the month, when I was stumped for something to write about. The rest of the time I had no trouble coming up with something to write about based on what was happening around me at that particular time. In fact, there were a number of topics that I really wanted to write about that I didn't get around to!

Some things are more interesting than others

A data management post with a slightly provocative title (for me) got by far the most views, re-tweets and comments. I had been nervous about writing this one, but I'm glad that I did because it seemed to strike a chord.

After that though, the posts that were most of interest to other people were on more generic topics to do with professional development; the posts were about librarians as internal consultants, project-based careers and pathways into data management. A post reflecting on my use of Twitter for professional networking was also pretty popular.

Writing and reading together make for good reflection

The thing I have enjoyed most about #blogjune is that it has provided me with a way to reflect on what I have been reading. I feel like this month I read things more deeply and through writing about them I made more explicit connections with my own professional practice. Although I probably think of myself as a reflective practitioner, the acts of adding an article or report to Zotero and then writing something about it have shown me that my reflection is usually pretty shallow, consisting of skim reading, sending a Tweet and filing it somewhere at the back of my head. If nothing else, I hope that I will continue to use my blog as a way of engaging more critically with the articles and reports that I am reading.

I prefer building an argument to stating an opinion

I've been trained to write scholarly pieces that make reference to other people's works. I'm comfortable with that mode and find it hard to simply express an opinion without backing it up. I don't think this is a problem but I do wonder if blog posts with references are just silly, and if this actually means I need to spend more time writing some journal articles!

Short and sharp (no, not so much)

I wrote about 18,000 words over the month, with a lot of posts coming in around the 700-800 word mark. I don't think this is a bad length for a post, and I don't think they were particularly waffly, but I am wondering if the theme that I have applied to my blog might not be the best for posts of this length.

The other thing is that I am slooooooow. Many posts took me a couple of hours to write which would not really be sustainable on a daily basis without having to sacrifice other important things like sleep, exercise or time with my partner.

I'm not a visual thinker

Yes, I already knew this one too, but #blogjune certainly highlighted it. I really have to force myself to think about whether there is an image or two that could be added to a post for the poor people that aren't completely text-oriented like me.

I respond well to external constraints and deadlines

Which is why I will definitely see you next year for #blogjune!

Here in Australia, we often look to the UK and the US as sources of inspiration about data management initiatives. I wonder why we don't look more to other countries. There is some great work happening in Canada at the moment that I think is worthy of more attention.

I am especially impressed at the level of library collaboration that is going in to building staff capability. In Australia, efforts to raise awareness and skills have been largely led by the Australian National Data Service through a program of webinars, regional 'roundtables,' and workshops, not all of which are targeted at librarians. While these are well-organised and well-attended, a more community-driven model in which everyone contributes to and benefits from programs more or less equally as a set of 'members' rather than as 'ANDS partners' (with the division between the hub and spokes that phrase implies) might look quite different. If that is the case, it will be interesting to observe how the development of data management services in Canadian research libraries progresses.

It seems that Canada's research funding councils currently do not ask for a formal data plan as part of the grant applications process; however many of them require (rather than just encourage, as the Australian Research Council does) data to be deposited in a repository at the end of a project [1]. There are signs that this is changing. As described by Michael Steeleworthy (Data Librarian at Wilfrid Laurier University), in 2013 a group of Canadian funding councils published a consultation paper that 

ask[ed] the nation’s scholarly community to develop a collaborative framework that encourages data sharing and invests in digital infrastructure... They also made three recommendations for RDM stakeholders that underscore the need for a holistic view of RDM’s people, processes, and technology: establish a culture of research data stewardship based on existing structures and practices at Canadian and international institutions; coordinate stakeholder engagement among all research partners, including libraries; and develop funding and resource capacity. [3]

In the absence of a centrally funded agency driving infrastructure development and providing project grants (such as ANDS here in Australia and Jisc in the UK), Canadian organisations seem to be building their data management capacity and capability more from the ground up. In the quotation above, the phrase "based on existing structures and practices" really jumps out at me as a key difference between what is happening in Australia and what is happening in Canada. While Canadian organisations are being asked to collectively develop the plans and funding models to achieve good stewardship of research data within the existing system, the establishment of ANDS in Australia has led to the development of a model in which large amounts of capability (in terms of staff with data management expertise) are located in a new lead agency, which partner organisations look to for vision, advice, training and community development. Neither model is more 'correct' than the other but they are certainly different approaches and must each come with benefits and drawbacks. 

Research Data Canada is described as "a stakeholder driven and supported organization dedicated to advancing the vision for research data in Canada." Individuals and members are encouraged to contribute, both financially where possible (though there is no membership fee) and through in-kind participation in working groups, projects and events programs. A very broad range of organisations is involved, not just as stakeholders who are consulted as required by a lead agency, but as active contributors to committees and working groups. This includes funding agencies, research infrastructure providers (for compute and academic networks), technology providers from industry, universities, government research organisations and a range of other government departments. 

Libraries also seem to be collaborating effectively by using existing channels for cooperation such as the Canadian Association for Research Libraries (CARL), rather than by devolving responsibility for capability building. Governance  is provided by the CARL Data Management Subcommittee (along with the the Research Data Canada Education & Training Subcommittee). As Steelworthy notes, data management competencies were made explicit by CARL in 2010, "including knowledge of data management and institutional repositories within scholarly communication, developing partnerships and collaborations with stakeholders, and understanding leading practices for digital curation and preservation". Recently a Canadian Community of Practice for Research Data Management in Libraries was established; this seems to be a real community effort that is sponsored by CARL and is being facilitated by seventeen staff across a range of institutions. This community emerged from a 2013 CARL training workshop in research data management services which invited institutions to send two participants to a four-day workshop. The course was co-developed by staff from seven organisations and was delivered by these staff as well as invited guests. The goal of the course was for participants to take back to their organisations an action plan for research data service development. 

A new project (Project ARC) started in March 2014 will build on these activities. The goal of this project is to build "a library-based research data management network" in Canada. Again, this project has been initiated from within the library sector by CARL. In the latest update for this project, Kathleen Shearer has described the design and population of a national information resource for data management planning and an automated data management planning tool that can help researchers create their data management plans. The project also plans to deliver a version of the MANTRA research data management training tutorial developed by the University of Edinburgh. [4]

To an outsider at least, it seems that existing library structures for cooperation are being used effectively in Canada to build research data management capability. Bottom-up initiatives that are developed and delivered within the community and for the community are the norm, and seem to be gaining great buy-in from the member organisations and the staff within them. There could be valuable lessons here for Australian research libraries and the agencies that support cooperation between them, such as the Council for Australian University Librarians (CAUL) and regional groups such as the Queensland University Libraries Office for Cooperation (QULOC).

References

[1] Steve Marks, Amber Leahey. 2014. Guides. Resarch Data Repositories. Data Management Plans. http://guides.scholarsportal.info/researchdatamanagement.

[2] Steeleworthy, Michael. 2014. “Research Data Management and the Canadian Academic Library: An Organizational Consideration of Data Management and Data Stewardship.” Partnership: The Canadian Journal of Library and Information Practice and Research 9 (1) (June). https://journal.lib.uoguelph.ca/index.php/perj/article/view/2990.

[3] CARL Library Education Working Group and the Building Capacity Subcommittee. 2010. Core Competencies for 21st Century CARL Librarians. Canadian Association of Research Libraries. http://www.carl-abrc.ca/uploads/pdfs/core_comp_profile-e.pdf.

[4] Shearer, Kathleen. 2014. “ARC Project Update.” Canadian Community of Practice for Research Data Management in Libraries. http://data-carl-abrc.ca/2014/06/24/project-arc-update/.