1. SAVING AND STORING YOUR RESEARCH DATA : TIPS AND TOOLS Jane Fry Wendy Watkins Carleton University Library Data Centre and the Carleton Scholar Program February 23, 2015

2. A GENDA Definition of Research Data Why are Research Data important? What do we mean by Sharing your Research Data? Why are we concentrating on this now? Tri-Council Consultation 2013-14 Benefits of Sharing your Research Data What are metadata and why are they important? Metadata standards by discipline How do we start? Elements of a Research Data Management Plan DMP Tool and Dataverse: Tools to Aid in Data Sharing Research Data Management with MANTRA Video Questions and discussion 2

3. D EFINITION OF RESEARCH DATA  Research data are digital information, structured through methodology for the purpose of producing new knowledge.  Not all digital information is research data, but all have the potential to become research data.  Digital Information + Methodology = Research Data  used to produce new knowledge 3

4. W HY ARE R ESEARCH D ATA I MPORTANT ?  They support the original research.  They are a deterrent to research fraud.  They increase in value if they can be repurposed and shared. 4

5. W HAT DO WE MEAN BY S HARING YOUR RESEARCH DATA ?  Research data can be shared in a number of ways:  informally, from researcher to researcher;  deposited in a self-archiving system;  deposited in a specialist data centre - dedicated to archiving, preserving and disseminating digital data; and  deposited in an institutional repository. 5

6. W HAT DO YOU NEED TO DO TO SHARE YOUR RESEARCH DATA ?  Need to apply sound practices in the creation of data for current and future purposes  AKA “data curation” or the preservation and maintenance of digital assets  AKA “data stewardship” for the lifecycle of the research project  Starts with a Research Data Management Plan (RDMP) 6

7. W HY ARE WE CONCENTRATING ON THIS NOW ? Many international funders already require this Tri-Council (SSHRC, CIHR and NSERC) + CFI and others are working on a policy requiring Research Data Management Plans on all funding applications Genome Canada requires this now We should be ahead of the curve in this If we get our ducks in order first, they will adopt our protocols Establishing good practices now will pay off in the future 7

8. T RI C OUNCIL C ONSULTATION 2013/2014 Capitalizing on Big Data: Toward a Policy Framework for Advancing Digital Scholarship in Canada See http://www.sshrc-crsh.gc.ca/about- au_sujet/publications/digital_scholarship_consultation_e.pdfhttp://www.sshrc-crsh.gc.ca/about- au_sujet/publications/digital_scholarship_consultation_e.pdf Likely outcome: a requirement that all grant applications include specific data sharing plans including identified costs of data collection/analysis and preservation of results and associated datasets 8

9. B ENEFITS OF SHARING Y OUR R ESEARCH D ATA  Confirmation of original findings  They are essential for you to defend your research  Further research  Teaching  Planning follow-up studies  Conducting trend analyses 9

10. What are Metadata?  “Data about data”  The key to research data re-use  Documentation in standardized and structured form  Ideally computer-ready  Why are they important?  They explain your data  You, as the researcher, are the best person to answer questions about your data! Thanks to Jeff Moon, Queen’s University Library http://www.dataenthusiast.com/wp-content/uploads/2011/10/meta_data_standard_transmission1.jpg 10

11. Metadata Standards – Vary by Discipline Thanks to Jeff Moon, Queen’s University Library 11

12. H OW D O W E S TART ?  Key is to produce a Data Management Plan A data management plan is a formal document that outlines how you will handle your data both during your research, and after the project is completed. [1] The goal of a data management plan is to consider the many aspects of data management, metadata generation, data preservation, and analysis before the project begins; this ensures that data are well- managed in the present, and prepared for preservation in the future. [1]data managementmetadata Source: http://en.wikipedia.org/wiki/Data_management_plan http://en.wikipedia.org/wiki/Data_management_plan 12

13. H OW DO WE START ? Research Data Management lifecycle http://www.data-archive.ac.uk/create-manage/life-cycle 13

14. E LEMENTS OF A R ESEARCH D ATA M ANAGEMENT P LAN (RDMP) Funder and Data Description Data Collection Documentation and Metadata Storage and Backup Preservation Data Sharing and Re-use Responsibilities and Resources This template is taken from the University of Alberta’s Data Management Plan Builder (https://dmp.library.ualberta.ca/projects/my-project- university-of-alberta-template--130?show_form=yes)https://dmp.library.ualberta.ca/projects/my-project- university-of-alberta-template--130?show_form=yes 14

15. F UNDER AND D ATA D ESCRIPTION Different funders have slightly different requirements for the content of Data Management Plans The DMP Builder (one of the tools) will provide the proper template, depending on the funder’s requirements The data description is a brief summary of the overall project It is not necessary in every case Details are provided in the following sections 15

16. D ATA C OLLECTION What types of data will you collect, create, acquire and/or record? What file formats will your data be collected in? How will you will securely store and transfer the data? Estimate how much storage space you will require (in megabytes, gigabytes, terabytes) and growth of the project over time Are there are any existing data that you can re-use? If so, explain how you will obtain that data and integrate it into your research project. What conventions and procedures will you use to structure, name and version control your files to ensure that your data is well-organized? 16

17. D OCUMENTATION AND METADATA What documentation will be needed for the data to be read and interpreted correctly in the future? study-level documentation data-level description any other contextual information required to make the data usable by other researchers List the metadata standard and tools you will use to document and describe your data. If there is not an appropriate standard, how will you ensure consistency in your documentation? How will you make sure that documentation is created or captured consistently throughout your project? 17

18. S TORAGE AND B ACKUP How will your data be stored and backed up during your research project? How will you ensure that sensitive data is stored securely and only accessible to the research team during the research project? What sort of encryption will you use? Will you use a data repository with security? 18

19. P RESERVATION Data selected for preservation and access depend on different factors It may be feasible to preserve all versions of the data e.g. raw, processed, analyzed, final It may be preferable to only keep only selected data e.g. transcripts instead of audio interviews At the end of your research project, where will you deposit your data for long-term preservation and access? 19

20. D ATA SHARING AND REUSE What data will you be sharing and in what form? e.g. raw, processed, analyzed, final Which data may need to be shared in order to meet institutional or funding requirements? Which data may be restricted because of confidentiality/privacy issues? How will you be sharing your data? Include a brief description of any resources needed to share your data (equipment, systems, expertise, etc.). Describe whether there will be any restrictions placed on your data when they are made available and who may access them. 20

21. R ESPONSIBILITIES AND R ESOURCES Who will be responsible for data management during the lifecycle of the project? What will happen when personnel changes occur or if the principal investigator leaves the institution before the project has concluded? Who will be responsible for data sharing and preservation after the project has concluded? What resources will you require to implement your plan? How much will this cost (estimation)? 21

22. DMP B UILDER AND D ATAVERSE : T OOLS TO AID IN DATA SHARING DMP Builder Located at the University of Alberta at present Will become part of the National Research Data Infrastructure in the near future Provides step-by-step guidance to developing a plan Dataverse Located at Scholars Portal Provides safe and secure storage for your research data Allows you to set limits on level of access for your team 22

23. R ESEARCH D ATA M ANAGEMENT WITH MANTRA MANTRA is a free online course designed for researchers or others who manage digital data as part of a research project. See more at: http://datalib.edina.ac.uk/mantra/#sthash.kTnRXTdV.dpuf http://datalib.edina.ac.uk/mantra/#sthash.kTnRXTdV.dpuf 23

24. V IDEO Data Management and Sharing http://www.youtube.com/watch?v=N2zK3sAtr-4#t=17 24