Plans for Data Management or Mobilisation?

December 10, 2014 1 Comment

I had a recent conversation with a researcher who had just been informed that her letter of intent for a major grant competition had been accepted and that she was invited to submit a full application. As she started this process, she organised a committee to provide her advice on a knowledge mobilisation plan. Such a plan is a requirement of the funding agency to which she is applying. One person she asked to serve on her committee inquired if she had also thought about preparing a data management plan (DMP). Because Canada’s three major federal funding councils have yet to institute DMP policies, she was unfamiliar with such plans and was referred to me to learn more about them.

When we met to discuss her research, I discovered that the project consisted of an international team with data from several countries. The data will be a mix of qualitative and quantitative information, some of which will be collected by the project and some of which will be obtained from national agencies. We reviewed the types of consent required from her research participants that would enable sharing these data with other researchers and preserving it for long-term access. We talked about the technical options for making the data safely accessible to the researchers on her team from other countries. We spoke about developing a data charter for the project that addresses governance issues around the use of the data by everyone within the project. As we went through these and other data topics, she paused and said, “I now understand that I will need a data mobilisation plan as well as a knowledge mobilisation plan.” This observation struck me that the “M” in DMP should possibly be mobilisation instead of management.

Data Mobilisation Plans

For most funding councils, the administrative purpose of data management plans is to learn the steps that researchers will apply to share the data from their projects. One way to frame this data-sharing goal is to address expectations around data stewardship. In taking this direction, I believe that mobilisation is a more appropriate concept than management.

  • First, management is about controlling or administering activities and resources, while mobilisation is about organising or preparing something for use (see remarks in the previous blog entry about organising versus managing). From the perspective of data stewardship, the planning steps for sharing data have more to do with organising the custodial care of data across the lifecycle than with controlling the details of data management.

    Mark Parsons, Secretary General for the Research Data Alliance, illustrated this point in a comment that he made during the CASRAI Reconnect 2014 Conference. He noted that when his staff at the National Snow and Ice Data Centre at the University of Colorado helped researchers prepare DMPs for U.S. funding agencies, the researchers had difficulty describing in advance the details around how they would manage their data. Such decisions often come later in the project and depend on the technology available at that time. My response was that assuming DMPs to be statements about the nuts and bolts of managing data misses the policy intent of the plan to elicit how the data will be shared. Instead of small details, these plans should be about the strategies that researchers will follow throughout their project around managing their data.

    Preparing strategies in a DMP should draw upon the data stewards with whom solutions might be formulated. For example, if a DMP asks a researcher to identify the data repository with which she or he will deposit the project’s data, one answer might be to discuss with a liaison librarian the identity of an appropriate domain or campus data repository. Another strategy might be to contact a curator from a data repository about her or his involvement in the project from its beginning. A DMP consisting of strategies for finding solutions that can be implemented during a project directs the researcher’s focus toward mobilising data stewards and services to deal with data management requirements as they arise.

  • Second, knowledge mobilisation plans are a funding agency requirement already known to many Canadian researchers, although some agencies may identify them as knowledge transfer or translation plans. Researchers see the value of these plans, which chart the dissemination activities of research findings. The rewards of having such plans are well understood by researchers. These statements identify pathways to influence other researchers, policy makers, and practitioners that will increase the likelihood of a larger readership of the researcher’s findings and potentially more citations of the researcher’s work. These valued outcomes translate into increased prestige and greater promotion opportunities.

    Data mobilisation plans may benefit from the widely recognised value already attributed to knowledge mobilisation plans. We may soon see rewards structured around data sharing, especially if data citation takes root and the linkage between data and research articles becomes universally adopted through the use of persistent digital identifiers. The more incentives are associated with data sharing, the more data mobilisation plans will be linked to researcher rewards.

  • Third, one should not lose sight of the role that a DMP plays as an administrative tool to promote research practices supportive of an organisation’s data policy. This connection between data policy and a DMP is fundamental to its function. Whether the data policy is directed at data stewardship, data sharing, reproducible research, or a combination of these, the DMP should elicit responses that are expressive of the policy’s values. The level of abstraction called for in this context is more directed at organising than managing things. As a policy instrument, the goal of DMPs keeps our attention more centred on mobilising than managing resources.

Filed under Data Management Plans, Data Mobilisation Plans, DMP

Data: a rose by any other name (part 2)

December 6, 2014 1 Comment

In an earlier blog entry, I spoke about the importance of having a technical language that allows data curators to talk within their profession about the details of their work. The words they use may be part of society’s everyday vocabulary but carry a meaning specific to data curation. Confusion can arise during conversations between data curators and others outside the profession when a term is used that carries different meanings for each group. For example, I was in a meeting recently with people from a variety of technical backgrounds, including librarians and research administrators. One librarian spoke about sharing resources across libraries. For the librarian, resources meant information tools, such as, library guides, while the administrator assumed that resources referred to money. The administrator was confused about why libraries would be exchanging money.

Communication problems can also arise within a campus’ research community. We encountered this with humanities researchers on our campus earlier in the year when our library hosted a week of workshops and talks on research data management. Speakers at this event consisted of researchers from all areas on the campus, including two prominent researchers from the digital humanities. One of the humanists said in reference to the title of the event, Research Data Management Week, that researchers in the humanities don’t see their research involving data. Rather, they see data as something belonging to the sciences. When the other humanist spoke, she commented on management in the event’s title, saying that in the humanities, management is seen as a topic for discussion in the business school. Of the four words in the event’s title, only research and week were acceptable concepts in the eyes of these humanists.

Subsequent to this event, a few of us in research data management services met with a humanities researcher who has a unique collection of digital video recordings of live musical performances from a Middle East country. His immediate concern was about the survival of the digital content. In addition to his copy of these recordings, only one other person on the globe has a set. As we worked through the options for making secure copies of his research content, I realized that we were talking primarily about organising his research materials, which happen to be in digital format.

Those of us providing research data management services learned an important lesson from these encounters. When talking with researchers from the humanities, we need to talk about organising their digital research materials rather than managing their data. A meeting with the liaison librarians in the humanities library later confirmed this approach. As data curators, we will continue to talk about managing data with most of the researchers on our campus, but with humanists, we have a new way of talking with them that lowers communication barriers when discussing their digital research content.

Filed under Data Concepts, Research Data Vocabulary Tagged with

Are Libraries Organized to Provide Research Data Management Services?

December 4, 2014 Leave a comment

Where do research data management services fit into today’s organisational charts for academic libraries? I have had this discussion several times in the past couple of months with librarians from different institutions. Each of these conversations has been independent of the other, suggesting that this is becoming a topic of interest as academic libraries move to offer research data management services. To address this question, it is helpful to start with the organisation of data services already being offered in libraries and then to consider how these service areas might work together.

Over the past twenty-five years, many North American academic libraries established outstanding services for students and researchers to help them access data produced by organisations or agencies outside their institution. The staff of these services often assist with locating data, interpreting data documentation, retrieving data files, and providing the data in a format that can be directly loaded into analytic software. Data distributors typically require a licence to be signed before granting use of their data on a campus. Therefore, these services also manage data licences, educate patrons about the terms around which data may be used, and monitor these activities.

Organisationally, these data services have been located, for the most part, in a subject library associated with a particular data type, for example, social survey microdata are in the social sciences library while company and market data are in the business library. Those using these secondary data resources are often regular patrons of the subject library in which the service is located. Familiarity with the subject library has proven to be important to these services because elsewhere on the campus, awareness of their existence tends to be low. These services struggle to increase their visibility on campus and to promote the value of their service to a larger user community.

With the emergence of research data management as a service area, one obvious question is whether it should simply be amalgamated with existing data services. After all, a common skill set around providing access to data is shared by both service areas. On the other hand, existing data services are only part of the wider mandate of research data management services, which covers all stages of the research data lifecycle and applies to all research on campus. With such a widespread mandate, should a new vertical service division be created in the library to house both research data management and existing data services? Or should existing data services remain in their current organisational location but be coordinated in conjunction with a larger research data management service?

While there are undoubtedly many successful ways of organising research data management services in a library, the following list raises some important considerations about the location of these services.

Research Data Management Services and Organisational Factors

  1. Research data management involves horizontal activities that cut across the vertical organisational structure of today’s academic library.
    • Research data management touches on almost all operations of the library. Whether organised around facility, function, domain, or some combination of these, research data will span these organisational divisions.
    • Because of its ubiquitous nature, research data management needs to be part of the library’s mission and service culture.
    • The vast majority of librarians must embrace research data management as part of their responsibilities.
  2. Research data management requires personnel practices that will support flexible work assignments for both horizontal and vertical activities.
    • The mandate for research data management is large and draws upon a range of skills and knowledge. The professionals with these talents are spread across the vertical divisions of the library, requiring the need to call upon staff from the whole organisation.
    • To work horizontally in a vertical structure, flexible work assignments must be accommodated by the system.
    • To operate within a vertical reporting structure, management methods are needed to pool staff from across the library. One method that has proven successful is the use of teams that are formed on the basis of a charter defining a fixed set of objectives. Once the team completes its work, the team is disbanded.
  3. Research data management must be intentionally coordinated across the vertical organisational structure of the library.
    • Research data management requires a full-time coordinator who has been granted authority to organise this service’s activities across the vertical divisions of the library.
    • The coordinator position needs to be high enough on the organisational structure to work effectively with fellow managers.
    • The coordinator should be supported as an ambassador for research data management on campus.
  4. Through coordinated supervision, the functions supporting research data management service can be distributed across the library system.
    • An existing data service with an identity well established within a specific subject library should be allowed to stay in its location. The staff will likely be called to participate on team projects but this in itself does not require an organisational relocation.
    • Liaison and subject librarians need to incorporate research data management materials into the portfolio of resources that they maintain for students and researchers.
    • When drawing upon library system resources and services, research data management services must be given the priority attention it needs to ensure the delivery of systemwide support for its services.

Filed under Library Organisational Charts, Research data management services Tagged with