Overview of Research Data Management

1. Overview of Research Data Management Created By: Andrew Creamer, UMass Medical School Donna Kafel, UMass Medical School Elaine Martin, UMass Medical School Regina Raboin, Tufts University CC BY-NC

2. Learning Objectives • Recognize what research data is and what data management entails • Recognize why managing data is important for your research career • Identify common data management issues • Learn best practices and resources for managing these issues • Learn about how the library can help you identify data management resources, tools, and best practices Module 1: Overview of Research Data Management

3. What is Research Data? “Research data, unlike other types of information, is collected, observed, or created, for purposes of analysis to produce original research results” (University of Edinburgh). “The recorded factual material commonly accepted in the research community as necessary to validate research findings” (Excerpted from OMB Circular A-110 36.d.2.i). Module 1: Overview of Research Data Management

4. Types of Research Data • Observational • Experimental • Simulation • Derived or compiled Module 1: Overview of Research Data Management

5. Research Data Examples • Documents • Lab notebooks, field notebooks, diaries • Questionnaires, transcripts, codebooks • Survey responses • Health indicators (blood pressure, white blood cell count) • Audio and video recordings • Images (digital and hard copy) • Protein and genetic sequences • Bones • Spectra • Slides, artifacts, specimens, samples • Database contents • Models, algorithms, scripts, software code • Methodologies and workflows • SOPs and protocols • What else can you think of? Module 1: Overview of Research Data Management

6. Why Manage Data? “…data is the currency of science, even if publications are still the currency of tenure. To be able to exchange data, communicate it, mine it, reuse it, and review it is essential to scientific productivity, collaboration, and to discovery itself.” (Gold, 2007). Module 1: Overview of Research Data Management

7. UT’s Research Data Policy Read UT’s Research Data Policy (in your handouts), and answer the following questions: • What are the two most important points you pick up from this document? • According to this policy, what are the incentives to take Research Data Management seriously? Module 1: Overview of Research Data Management

8. 3 Good Reasons for Managing Your Data • Transparency & Integrity Module 1: Overview of Research Data Management

9. 3 Good Reasons for Managing Your Data • Transparency & Integrity • Compliance Module 1: Overview of Research Data Management

10. Emerging Federal Requirements “The Administration is committed to ensuring that…the direct results of federally funded scientific research are made available to and useful for the public, industry, and the scientific community. Such results include peer-reviewed publications and digital data” (Holdren 2013). Module 1: Overview of Research Data Management

11. Project Open Data Module 1: Overview of Research Data Management

12. Joint Data Archiving Policy

13. 3 Good Reasons for Managing Your Data • Transparency & integrity • Compliance • Personal benefits Module 1: Overview of Research Data Management

14. Personal Benefits • Eliminate duplication of effort • Save time, energy, resources • Locate and share data easily • Analyze and publish data with confidence • Other researchers can use it • You get credit Module 1: Overview of Research Data Management

15. Why is Data Management Important? http://www.youtube.com/watch?v=N2zK3sAtr-4 Module 1: Overview of Research Data Management

16. Data Management Issues • Lack of responsibility • Lack of data management plan • Poor records management • Lack of metadata and data dictionary • Data files not backed up and are insecure • Undetermined ownership • Undetermined data retention requirements • Lack of long term plan

17. Issue #1: Responsibility Challenges of Team Science Challenges Managing Laboratory Notebooks Challenges with Rotating Lab Personnel Module 1: Overview of Research Data Management

18. Best Practices • Define roles and assign responsibilities for data management • For each task identified in your data management plan, identify the skills needed to perform the task • Match skills needed to available staff and identify gaps • Develop training plans for continuity • Assign responsible parties and monitor results Module 1: Overview of Research Data Management

19. Resources @ UT • Contact the library for assistance, resources, and tools to better manage the information in your paper and/or electronic laboratory notebooks. • Librarians can also help you to catalog, organize, preserve and archive your laboratory notebooks. Module 1: Overview of Research Data Management

20. Issue #2: Data Management Plans (DMPs) • What types of data will be created? • Who will own, have access to, and be responsible for managing these data? • What equipment and methods will be used to capture and process data? • What metadata will make these data make sense to others? • Where will data be stored during and after? Module 1: Overview of Research Data Management

21. Funder DMP vsthe Life Cycle of a Project Module 1: Overview of Research Data Management

22. The DataONEData Life Cycle Module 1: Overview of Research Data Management

23. Module 1: Overview of Research Data Management

24. Resources @ UT Librarians can help you with: • Writing a data management plan for a grant proposal. • Finding and using online tools and resources to create your data management plan (i.e. DMPTool) • Identifying institutional resources for annotating, storing, and sharing your data to include in the plan. Module 1: Overview of Research Data Management

25. Issue #3: Records Management • inconsistently labeled files • in multiple versions… • inside poorly structured folders… • stored on multiple media… • in multiple locations… • and in various formats… Module 1: Overview of Research Data Management

26. Slide Credit: Jen Ferguson 2013

27. Best Practices Avoid special characters in a file name. Use capitals or underscores instead of periods or spaces. Use 25 or fewer characters. Use documented & standardized descriptive information about the project/experiment. Use date format ISO 8601:YYYYMMDD. Include a version number. Module 1: Overview of Research Data Management

28. Slide Credit: Gaudette 2013

29. Slide Credit: Gaudette 2013

30. Resources @ UT Librarians can help you with best practices, resources, and tools for: • Creating file naming conventions • Creating directory structure naming conventions • Versioning your files • Choosing appropriate file formats for preserving and sharing your data files Module 1: Overview of Research Data Management

31. Activity Develop a file naming scheme for data set files that you could use in your research. Module 1: Overview of Research Data Management

32. Issue #4: Metadata • How will I label, document, describe, and contextualize my data during my project so I know what I am collecting? • How will someone else make sense of my data during and after the project (e.g. field names, terminology, values, parameters, etc.)? • How can you describe a data set to make it discoverable by others? Module 1: Overview of Research Data Management

33. Types of Metadata • Descriptive • Structural • Administrative Module 1: Overview of Research Data Management

34. Example Metadata Record

35. Resources @ UT Librarians can help you locate disciplinary and general metadata standards and resources for annotating and describing your data and data files, such as DDI, used in population research, or Dublin Core, which is a general standard that is widely used. Module 1: Overview of Research Data Management

36. Issue #5: Backing Up and Securing Data • How often should data be backed up? • How many copies of data should you have? • Where can you store your data? • How much server space can I get? Module 1: Overview of Research Data Management

37. Best Practices • Make 3 copies (original + external/local + external/remote) • Have them geographically distributed (local vs. remote) • Use a Hard drive (e.g. Vista backup, Mac Timeline, UNIX rsync) or Tape backup system • Cloud Storage - some examples of private sector storage resources include: (Amazon S3, Elephant Drive, Jungle Disk, Mozy, Carbonite) • Unencrypted is ideal for storing your data because it will make it most easily read by you and others in the future…but if you do need to encrypt your data because of human subjects then: • Keep passwords and keys on paper (2 copies), and in a PGP (pretty good privacy) encrypted digital file • Uncompressed is also ideal for storage, but if you need to do so to conserve space, limit compression to your 3rd backup copy Module 1: Overview of Research Data Management

38. Resources @ UT UT's Office of Information Technology provides you with services to help ensure the safety and security of you research data. The following services can be utilized by all UTK researchers: • Vault: share large amount of data and send messages to project collaborators securely. (vault.utk.edu) • TrueCrypt: Free on-the-fly software and file encryption. • Identify Finder: Prevent identity fraud by ensuring sensitive information is not easily accessible. • 2-Factor Authentication • Crashplan: cloud-based backup service Contact Bob Hillhouse for more information on the preceding services at bob@utk.edu or 865-974-8445 . Module 1: Overview of Research Data Management

39. Issue #6: Ownership and Retention • Intellectual Property Policy • IRB data retention policy • Funders’ data retention policy • Publishers’ data retention policy • Federal and State laws Module 1: Overview of Research Data Management

40. Module 1: Overview of Research Data Management

41. Issue#7: Long-Term Planning • What will happen to my data after my project ends? • How can I appraise the value of my data? • What are my options for archiving and preserving my data? • What are my options for publishing and sharing data? Module 1: Overview of Research Data Management

42. Resources @ UT Librarians can help you to appraise your data and plan for the long-term preservation of your research data, including: • Creating a DOI for maximizing discoverability of your data and measuring its citation impact • Locating file formats suitable for long-term preservation • Locating and submitting data to a suitable data repository • Choosing metadata standards for increased discoverability • Help with publishing and sharing your data Module 1: Overview of Research Data Management

43. Recap: Librarians Can Help With • Metadata (locating and creating) • Licensing • Data repositories (locating and submitting) • Archiving and preservation • Finding data for your research • Complying with funder requirements • Citing data • Publishing data • Obtaining DOIs for data sets • Writing a Data Management Plan Module 1: Overview of Research Data Management

44. Questions? Module 1: Overview of Research Data Management