Data Management and Data Management Planning Boston College OSP Briefing -- Nov. 21, 2017

Transcription

1 Data Management and Data Management Planning Boston College OSP Briefing -- Nov. 21, 2017 Enid Karr, Sr. Bibliographer for Biology, Earth & Environmental Sciences, Environmental Studies Barbara Mento, Data/GIS Librarian, Sr. Bibliographer for Computer Science, Economics, Mathematics Sally Wyman, Sr. Bibliographer for Chemistry, Physics, Environmental Studies

2 Why Have a Data Management Plan ( DMP )? Fits into responsible conduct of research compliance Risk of data loss to researcher and to University Facilitates fulfillment of requests from others to see individual researcher data Preserves understanding of details for later Shared data ( open access ) higher citation rate!

3 Most federal grants now require this: NSF all grants since Jan. 18, 2011 require 2-page DMP Directorate of Mathematics and Physical Sciences, Directorate of Chemistry (CHE) NIH all grants since Oct. 1, 2003 require data sharing DOE all grants since Oct. 1, 2014 require DMP that describes how sharing/preservation will enable validation of results (or statement that describes how these goals will be met without sharing/preservation) Many more agencies now require some level of sharing or DMP -- since Feb. 22, 2013 OSTP memorandum

4 Many grants now require this, but it s bigger than that: More scholarly publishers do, too, now: American Economic Association journals, Nature, Science, PNAS, PLoS, etc. require or encourage that data be clearly documented available for sharing detailed enough to permit replication of analysis Data journals are now published Nature Publishing Group s Scientific Data provides a place for curated descriptions of scientifically valuable datasets to foster sharing and reuse of data. There are indexes that focus on data Data Citation Index

5 What is data? From the NSF FAQ on Data Management Plans: DMP covers recorded factual material commonly accepted in the [specific] scientific community as necessary to validate research findings. May include, but is not limited to: Data Publications Samples Physical collections Software and models But not: preliminary analyses, drafts of scientific papers, plans for future research, peer reviews, or communications with colleagues. (Office of Management and Budget (OMB) Circular A-110 )

6 1-2 pages describing the project and how data will be: Elements of a Typical Data Management Plan (DMP) Collected (including formats, size, etc.) Secured Analyzed Shared Preserved Details about access/sharing Potential audience(s) for the data How access will be provided and how others will find it: Access (freely-available) vs. Sharing (by request) Stipulations for privacy, confidentiality, IP or other rights Allowed re-use of the data, derivative products Metadata standards to be used How long data will be retained -- archiving, long-term preservation and format migration

7 Boston College Libraries Data Management Plan Research Guide Guidance on content Templates/examples Additional resources DMPTool Dataverse (More later in session) To arrange a consultation with a subject specialist

8 Key DMP Concepts 1. A Read me file or Code Book 2. Use of open (non-proprietary) file formats 3. Consistent naming practices for all files 4. Metadata 5. Back up plan 6. Long-term storage strategy 7. Data sharing 8. Plan for true archiving

9 Key DMP Concept #1 A Readme file or Code Book This file (or document) describes the research process for collecting data, how it is stored, how it is backed-up and file formats chosen and more, as described, below.

10 Key DMP Concept #2 Use of open file formats, avoiding proprietary formats Whenever possible, researchers should save data using open standards. Some examples: TXT, PDF/PDF Archival, not Word (doc, docx) ASCII, not Excel (xls, xlsx) MPEG-4, not Quicktime (qtff) TIFF or JPEG2000, not GIF or JPG XML or RDF, not RDBMS Ideally, files are saved in both original format AND one of the preferred ones listed above.

11 Key DMP Concept #3 Consistent naming practices for all files File names should be brief and unique, and might contain: Project acronyms, research initials, file type information, version, date, file status, like this one: Internet Usage Study version 2, Sept. 2011, final draft, in csv format: IUS_v02_092011_final.csv Evidence of maintenance of both archival (unmodified) and updated versioned files (clearly labelled)

12 Organization of Files Directory Structure Use folders! Possible ways to organize: By types of data fmri, interview, video By experiment/study By collection method Image: digitalart / FreeDigitalPhotos.net Choose option that works best for your research group it should be understandable to others

13 Version Control of Files Keep an archival (unmodified) version, and updated versions (clearly labelled) Use ordinal numbers (1, 2, 3) for major changes and decimals for minor changes (V1.1, V1.2 ) Version control software can help, and some software has this built-in especially instrument software

14 Key DMP Concept #4 Metadata It s data about the research data This data (subject-based terminology) helps others discover your data (more about this, shortly), helps YOU remember, and may be needed for later journal publication/data deposit Metadata standards exist per discipline per type of data (.cif for crystallographic data, for example) Per individual repository (ICPSR, GenBank, etc.) Metadata is recorded in the readme file or code book

15 Data Documentation ( Metadata ) Metadata captures the most critical information about a particular project. Best when captured early on helps jog memories later It helps others discover the research being shared. Metadata may be required for journal publication/data deposit. For help, contact your Subject Librarian ISO suggested Minimum Data Elements o Title o Creator (Principal Investigators) o Date Created (also versions) o Instrument and model o Format (and software required) o Subject o Unique Identifier o Description of the specific data resource o Coverage of the data (spatial or temporal) o Publishing Organization o Type of Resource o Rights o Funding or Grant

16 Data Documentation What do you do with it once you have it? Record it in a readme.txt file In some fields, codebooks are used to record methodology and other data management notes (e.g. IRB compliance statements, etc.) Consider including a data dictionary Inserted with deposited data these files facilitate discovery of your data on the Web

17 Key DMP Concept #5 Back up Strategy Regular, scheduled back up protects against loss Back up strategy will depend on your needs, collection volume, update frequency, etc.: Back up all versions of the files or certain ones? How often to back up files? Listing at least two back up locations (so, 3 copies) Internal (researcher computer) External (i.e. the BC Research Data Archive or departmental servers) Assign responsibility for backing up

18 Key DMP Concept #6 Long-term Storage Strategy Plan should describe how data will be stored in the safest long-term locations (not a laptop or flash-drive!) Local (lab computer, flash-drive): convenient, but much less secure Centralized ITS Servers, departmental servers, BC ELN server Remote BC Dataverse, disciplinary servers (GenBank, ICPSR, etc.) most tailored to disciplinary needs, but may be open (and that may be problematic for some researchers) Grants can sometimes cover cost of long-term storage.

19 Key DMP Concept #7 Data Sharing the ultimate goal of DMPs Options include: personal website but researchers can do better: Journal supplementary materials (ACS, etc.) now in figshare Institutional repository, e.g. BC Dataverse Disciplinary (or multidisciplinary) repository e.g. Cambridge Structure Database Or, a combination: journal-designated repository ( Nature or Review of Economics and Statistics Dataverse, for two examples)

20 Examples of Subject Repositories Biomedicine: GenBank* -- sequence data RSCB Protein DataBank* -- biomolecule crystal structure coordinates, etc. Chemistry: Cambridge Structural Database (CSD)* PubChem (Part of NCBI Entrez, covering biological activities of small molecules) Social Sciences ICPSR (Inter-university Consortium for Political and Social Research) IQSS (The Institute for Quantitative Social Science) Multidisciplinary: figshare.com (Open, Free) Finding Aid: -- search for repositories in all disciplines *A few of the data repositories that fulfill Science magazine requirements for data deposition

21 Key DMP Concept #8 Archiving Plans Archiving data means not just preserving the data in the original format but also in a format that is non-platform reliant, using a standard that ensures that the data can be re-used in the future.

22 Additional Essential Elements in the DMP: Ethics/privacy Data Ownership Intellectual Property/Technology Transfer

23 Ethics and Privacy Sensitive data should be redacted before depositing in a public archive or repository. Access to data may be embargoed (access limited for a time) for confidentiality, legal, patentability or other reasons. Dark archives ensure permanent protection of confidentiality. Where human subjects/privacy is involved, BC s Institutional Review Board (IRB) must approve. Image: digitalart / FreeDigitalPhotos.net

24 Good DMP, then What Happens? Data is Shared, then Cited Data Citation Why is proper data citation important? Ensures that original producers of the data are credited in citation indexes* Allows researchers to locate research data used in an article May be required by the archive that stores the data to be repurposed *Piwowar HA, Day RS, Fridsma DB (2007) Sharing Detailed Research Data Is Associated with Increased Citation Rate. PLoS ONE 2(3): e308.doi: /journal.pone

25 Citing Data Sets Essential citation elements; style will vary: author or creator title or description year of publication publisher and/or the database/archive from which it was retrieved the URL or DOI if the data set is online Pitt-Catsouphes, Marcie, and Steven Sweet. Talent Management Study: U.S. Workplaces In Today's Business Environment, ICPSR34836-v1. Ann Arbor, MI: Interuniversity Consortium for Political and Social Research [distributor], Hitchcock, Colleen; Manning, Deirdre; Keegan, Kevin; Utsun, Ekin, 2016, "Boston College tree inventory data archive", Harvard Dataverse, V1

26 Questions?

27 Library Tools and Resources to Help Barbara, Enid and Sally! We are here to help. Research Guide for Data Management Plans The BC DMP Tool Dataverse ORCID at BC unique researcher identifier

28 Other Library Services Digital Humanities Team Data Visualization and Analysis Team

29 DMPTool Template Example:

30 Dataverse Map created with data deposited in Dataverse. Visualization of inventories, species and health of trees to determine BC carbon footprint in Data is being repurposed in BC Ecology and Evolution class

31 Dataverse version 5 will include DataTags for confidential data. Coming December 2017 From presentation IRODS Meeting, Dataverse DataTags: Sharing Data You Can t Share. Merce Crosas, Ph.D. Director of Data Science, IQSS, Harvard University, 2014

32

33 is our institutional repository Faculty can deposit scholarly work including Working papers, published articles, teaching materials, conference presentations, posters Reasons to deposit: Compliance with funder mandates for open access Global visibility and readership Search engine harvesting Eliminates economic barriers to knowledge Increase citation counts Get a permanent URL for the CV Long-term preservation Link your data to accompanying publications

34 What is ORCID Unique, persistent identifier for researchers & scholars Follows you wherever you go Constant through life events and name changes Benefits Improves visibility in field Self-updating CV Eliminates name ambiguity Less than 60 seconds to sign up bc.edu/orcid

35 Faculty Annual Report ORCID at BC Import citations to Faculty Annual Report Display on work in Display on faculty profiles Use in grant and manuscript submissions Faculty Profiles Manuscript submission bc.edu/orcid Professional Orgs Grant applications

36 More Ways We Can Help: Librarians are expert searchers Need information on the broader impacts or applications of the proposed work? May call for a more comprehensive literature search -- particularly into literature outside of the immediate field ask your subject specialist librarian. Who else is doing similar research? The Scopus database can make this more visible. See next slide. Who is funding similar work? Scopus and Web of Science both report funder sources and both allow searching by funder to find funded work. Where to publish/how to best disseminate the work? JCR Database use it to find journal Impact Factors (IF) Scopus use to find CiteScore, SJR, SNIP alternatives to IF

37 Scopus Data Visualization: key journals for the topic

38 Scopus Data Visualization: key authors for the topic

39 Scopus Data Visualization: key institutions for the topic

40 Any More Questions?