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Collaboration

Collaboration. Finding Partners in the World of Research Data Management. What is Collaboration?. A process where two or more people or organizations work together to realize shared goals (Wikipedia) To work together, especially in a joint intellectual effort (Free Online Dictionary)

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Collaboration

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  1. Collaboration Finding Partners in the World of Research Data Management

  2. What is Collaboration? A process where two or more people or organizations work together to realize shared goals (Wikipedia) To work together, especially in a joint intellectual effort (Free Online Dictionary) To cooperate with an agency or instrumentality with which one is not immediately connected (Merriam-Webster)

  3. Why Collaborate? • Research data management is a complex set of activities; no one entity can do it alone • Partners can bring a diverse set of skills • Share the benefits (as well as the risks) • Without collaboration, it won’t get done • Libraries have a history of collaboration • Data Liberation Initiative • This workshop • Collaboration provides benefits to all partners

  4. Potential Partners • On campus • In the Library • Systems/IT • Subject specialists • Research Office • Graduate Studies • Computing Services • Ethics boards • Research institutes

  5. Inter-library Partners • Other CARL institutions • Regional library associations and their members • COPPUL • OCUL • CREPUQ • APLA • Specialised libraries (eg. Parliament) • Archives (municipal, provincial and federal) • Library service providers

  6. External Partners • Funding agencies • SSHRC, CIHR, NSERC • Provincial government bodies • Foundations and other sources of financial assistance • International Data organizations • ICPSR, CESSDA, IFDO, UKDA, DANS, DCC • All provide training materials • Existing data storage centres • (eg. Physics, Astronomy, Genomics)

  7. Examples of External Partnerships • Standards groups – provide guidance for metadata • NISO • Data Documentation Initiative (DDI) • Consultative Committee for Space Data Systems (CCSDS) • Open Biological and Biomedical Ontology (OBO) • Consortia Advancing Standards in Research Administration Information (CASRAI) • Research Data Canada – providing a collaborative venue for RDM • Granting councils • CANARIE – Canada’s high-speed internet provider • CISTI – Canda’s national science library (National Research Council) • CFI – Canadian Foundation for Innovation • CUCCIO – Canadian University Council of Chief Information Officers

  8. Informal Collaborations • Other data colleagues • Use them to discuss new projects • Form informal partnerships and share ideas and tasks • IASSIST - (International Association for Social Science Information and Technology) • Community of practice for data professionals • Excellent sounding boards, source of support • Great source of ideas • Wonderful membership

  9. IASSIST 2014: Toronto Great opportunity to broaden your network beyond our borders Kevin, Berenica and Walter will be hosting Chuck is the program chair Something for everyone at every level

  10. Planning Collaborative Activities Think of the 4 service areas from Exercise 1 and your local data landscape Think of your 3-year plan Is there one activity or set of activities that stands out with which you need a collaborator? Use the template as a guide

  11. Data Liberation as an Example of a Successful Collaboration • Lessons learned • Have a clear vision of what you want to accomplish: make sure there is a need • Choose your partners wisely: SSFC was instrumental in the lobbying (helped that they represented 25,000 SS researchers); had internal support from Statistics Canada senior manager (Ernie Boyko) and Carleton’s CCS Director • Be willing to modify the procedures, NOT the vision • Do as much proof of concept as possible beforehand: anticipate arguments (prepare like you’re defending a thesis) • Be patient: it took 49 months from the first paper to acceptance of DLI as a partnership between the academics and Statistics Canada • Conduct periodic, systematic evaluations once the project is underway

  12. CARL Research Data Management Services Example Collaboration Template

  13. Deconstructing the Template Need should be well-defined and articulated University partners should not be limited to your campus Non-university partners should have a well-defined stake in the project Benefits should be real and concrete for all parties Your library’s contribution should be substantial Desired outcome must be achieveable

  14. Questions?

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