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Jeff Moon Data & Government Information Librarian Academic Director, Queen’s Research Data Centre

Research Data Management. Jeff Moon Data & Government Information Librarian Academic Director, Queen’s Research Data Centre. Research Data Management.

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Jeff Moon Data & Government Information Librarian Academic Director, Queen’s Research Data Centre

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  1. Research Data Management Jeff Moon Data & Government Information Librarian Academic Director, Queen’s Research Data Centre

  2. Research Data Management Data management: encompasses the entire data life cycle, including data collection, organization, storage, retrieval, and preservation over time.

  3. The Data Life Cycle Source: http://www.ucl.ac.uk/ich/research-ich/mrc-cech/images/data/life-cycle/research-data-life-cycle.jpg?hires

  4. Research Data: “That which is collected, observed, or created in a digital form, for purposes of analysing to produce original research results” http://www.ed.ac.uk/schools-departments/information-services/services/research-support/data-library/data-repository/definitions

  5. The Data Access Continuum Real-Time Remote Access (RTRA) Desktop analysis of unabridged Master files Potential for more detailed tables AUTOMATIC table vetting Statistics Canada charges annual fee for access $$$ (this service is under consideration) Research Data Centre (RDC) Controlled access to unabridged Master files Potential for more detailed tables & analysis Tables vetted by Statistical Analyst for anonymity No charge to researchers Microdata Public-Use Microdata Files (PUMFs) Responses of individuals Anonymity of respondents is assured Generally free Under license from Statistics Canada (DLI) Custom Tabulations Generated on request by Statistics Canada using unabridged Master files Potential for more detailed tables Tables vetted for anonymity Cost recovery from Statistics Canada $$$ Statistics Tables, charts, graphs… Open to the world ODESI Dataverse QSpace Queen’s Nesstar Discipline-based archives A lot of research data fits in here… but other discipline-based archives exist

  6. Why manage & share your data? • Promotes higher quality research and peer review • Opens the door to further research • Demonstrates effective stewardship of publicly- funded data • Ensures long-term preservation of and access to data • Builds in procedures to ensure anonymity/privacy

  7. Other factors to consider… • Some scientific publications require that data be available for the scientific community before the article is published • A growing number of funding agencies require that data be deposited in a public archive • Future researchers can go to the ‘archive’ for your data… rather than trying to find you

  8. OK, but where do I turn? • There are many resources related to • research data management • Queen’s University Library has pulled selected resources together into a guide…

  9. Research Data Management http://guides.library.queensu.ca/rdm

  10. Topics covered… • Overview • Writing a Data Management Plan • Funding Agency Guidelines • Metadata • Data Repositories & Archives • Citing Data • Best Practices in Data Management • Library as Data Partner • QUL Research Data Archive

  11. Data Management Workflow

  12. The Library as Data Partner Citing Data QUL Research Data Archive Data Repositories & Archives Metadata Best Practices in Data Management Writing a Data Management Plan Funding Agency Guidelines

  13. Key things the Library can help you with… • Developing a Data Management Plan (DMP) • Data assessment and refinement • Data conversion to appropriate format(s) • Finding appropriate data archive(s) • Storing/backing up your data • Documenting your data using established standards

  14. External influences… • Recent Tri-Council consultation papers • October 2013 • Toward a Policy Framework for Advancing Digital Scholarship in Canada • & • Draft Tri-Agency Open Access Policy – Consultation Document • http://www.sshrc-crsh.gc.ca/news_room-salle_de_presse/latest_news-nouvelles_recentes/big_data_consultation-donnees_massives_consultation-eng.aspx • http://www.nserc-crsng.gc.ca/_doc/Policies-Politiques/Tri-OA-Policy-Politique-LA-Trois_eng.pdf

  15. Capitalizing on Big Data… Toward a Policy Framework for Advancing Digital Scholarship in Canada… 3 main goals: Establishing a culture of stewardship Coordination of stakeholder engagement Developing capacity and future funding parameters

  16. Establishing a Culture of Stewardship a. Require that all grant applications include specific data management plans including costs of data collection, analysis, and preservation b. Definition of specific elements of data plans that will be considered by reviewers in the assessment of funding applications; c. Guidelines indicating which data must be preserved and in what formats; and for selecting suitable data repositories; d. Consolidated open access policies and guidelines

  17. Coordination of stakeholder engagement • Ensure involvement of all stakeholders in the development of a national digital infrastructure ecosystem for research

  18. Developing capacity and future funding parameters Evaluate funding parameters Balance the roles of national, provincial and institutional stakeholders Collaborate in the development a number of world-class centres specializing in data management Enhance networks and infrastructure Support skills development and graduate and researcher training

  19. Tri-Agency Open Access Policy The three funding agencies have “a fundamental interest in ensuring that the results of publicly-funded research are broadly disseminated, enabling other researchers as well as policy-makers, private sector, not-for-profit organizations, and the public to use and build on this knowledge”

  20. Data Management Planning • The TAKEAWAY MESSAGE is: • The Library can help with this!

  21. Data Assessment Data Verification: check dataset integrity, variable names/labels/groups, coding, missing data, etc. Disclosure Risk Assessment: check for identifying variables, detailed geography (e.g. Postal Codes), etc. File Formats: Assess file formats delivered, alternative formats, and conversion options

  22. Finding the right data archive(s) for your data Discipline-based archives

  23. QSpace https://qspace.library.queensu.ca/jspui/handle/1974/7652

  24. QSpace

  25. QSpace – data file

  26. Scholars Portal Dataverse http://dataverse.scholarsportal.info/dvn/dv/qulrda;jsessionid=5b8f9a4f624b2549d43ad0651500

  27. ODESI – Data Portal http://odesi.ca

  28. ODESI

  29. ODESI

  30. How do YOUstore or backup your data? http://win-win-elec.com/product.asp?classid=13 http://www.forbes.com/sites/benkerschberg/2012/02/15/federal-court-orders-kpmg-to-preserve-2500-hard-drives/ www.google.com http://www.colourbox.com/image/an-image-of-treasure-chest-on-white-background-image-3343371

  31. Metadata “Data about data” • Documentation in standardizedand structuredform • Ideally computer-ready • Explains your data: origin, purpose, time reference, geographic location, creator, access conditions and terms of use of a data collection. You as the researcher are the best person to answer questions about your data! http://www.dataenthusiast.com/wp-content/uploads/2011/10/meta_data_standard_transmission1.jpg

  32. Metadata Standards

  33. Examples of archived data http://guides.library.queensu.ca/content.php?pid=437556&sid=3637637

  34. Some early examples… Baldwin-Green Study - Canada-US Census of Industry 1867-1940 Historical Canadian Macroeconomic Dataset 1871 - 1994 1994 2001

  35. The Globalization of Personal Data Project Studied implications of surveillance and personal data in nine countries: Canada, U.S.A., France, Spain, Hungary, Mexico, Brazil, China, and Japan. Key element of success was a ‘data manager’ on the project. ODESI QSpace Dataverse

  36. Cranial Nonmetric Trait Database Used “R” to stack the files. 27 separate databases in Borland Paradox format on an older vintage PC Reviewed, refined, & enriched coding scheme Reviewed, refined, & enriched documentation QSpace Dataverse

  37. Ideally, however… We’d like to catch you early… http://www.actbucks.org.uk/images/research.jpg

  38. The Data Life Cycle Source: http://www.ucl.ac.uk/ich/research-ich/mrc-cech/images/data/life-cycle/research-data-life-cycle.jpg?hires

  39. If you have data, or are starting a research project, CONTACT US. We can help you develop and implement your data management plan.

  40. Contact information Erin Forward – Geospatial Data Librarian erin.forward@queensu.ca Ext. 36952 Jeff Moon – Data and Government Information Librarian Academic Director, Queen’s Research Data Centre moonj@queensu.ca Ext. 77992 AlexCooper– Data and Web Support Assistant coopera@queensu.ca Ext. 77481

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