![Preservation and Sharing data
• Some options for preserving and sharing data
– Self-archive
– Institutional repository
– Open data repository
– National or international data archive or
repository
By Florian Hirzinger - www.fh-ap.com (Own work (Florian Hirzinger)) [CC BY-SA 3.0 (http://creativecommons.org/licenses/by-sa/3.0) or GFDL (http://www.gnu.org/copyleft/fdl.html)], via Wikimedia Commons](https://image.slidesharecdn.com/2016rrf-160921204001/85/Introduction-to-data-management-52-320.jpg)
Introduction to data management
- 1. Introduction to Data Management Cunera Buys RRF 2016 https://www.flickr.com/photos/hellocatfood/7957989238/ (CC BY-NC-SA 2.0)
- 2. • Background on data management • Why data management is important • Intro to best practices for data management • Library resources for data management. Photo by Carl Vogtmann
- 3. Data Snafu Data Sharing and Management Snafu in 3 Short Acts https://www.youtube.com/watch?v=N2zK3sAtr-4
- 4. What are data? ://www.flickr.com/photos/rh2ox/9990024683/ (CC BY-SA 2.0)
- 5. Data- Some Definitions Digital Curation Center (UK): “Data, any information in binary digital form, is at the centre of the Curation Lifecycle.” Office of Management and Budget: “Research data means the recorded factual material commonly accepted in the scientific community as necessary to validate research findings” The Oxford English Dictionary (OED)defines “data” as: Related items of (chiefly numerical) information considered collectively, typically obtained by scientific work and used for reference, analysis, or calculation. Data can be both analogue and digital materials.
- 6. Data in the Sciences and Humanities BICEP2 (South Pole telescope) Performativity, Place, Space Burgess and Hamming, 2011BICEP2 Collaboration, 2014
- 7. Every discipline has data! Types of data include: • observational data • laboratory experimental data • computer simulation • textual analysis • physical artifacts or relics Examples of data include: • Audio and video files • Code or scripts • Digital text • Lab notebooks • Geospatial images • Instrumental data • Photographs • Rock samples • Survey results • Scanned documents • Spreadsheets • Video games https://www.flickr.com/photos/23165290@N00/9338136777/(CC BY-SA 2.0)
- 8. Why do funders and broader science community want to share and preserve data? https://www.flickr.com/photos/uwe_schubert/3931638785/ (CC BY-SA 2.0)
- 9. Brief History of Federal Data Sharing Requirements • February 26, 2003 - NIH requires a Data Sharing Policy for projects above $500K. • January 18, 2011- NSF requires Data Management Plans (DMPs) to be submitted with all new grant proposals. • February 22, 2013- Memo issued by White House Office of Science and Technology Policy (OSTP). http://www.whitehouse.gov/sites/default/files/microsites/ostp/ost p_public_access_memo_2013.pdf
- 10. Funding agency responses • Require Data Management Plans (DMPs) • Publications to be available to public within 12 months (Open Access) • Data supporting publications must be available in a public repository
- 11. Journal Requirements PLOS journals require authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception.
- 13. Reproducibility
- 17. Recognition Chapter II.C.2.f(i)(c), Biographical Sketch(es), has been revised to rename the “Publications” section to “Products” and amend terminology and instructions accordingly. This change makes clear that products may include, but are not limited to, publications, data sets, software, patents, and copyrights.
- 18. Benefits of Sharing Data • Clearly documents and provides evidence for research in conjunction with published results. • Meet copyright and ethical compliance (i.e. HIPAA). • Increases the impact of research through data citation. • Preserves data for long-term access and prevents loss of data. • Describes and shares data with others to further new discoveries and research. • Prevent duplication of research. • Accelerates the pace of research. • Promotes reproducibility of research.
- 19. Data reuse success story # 1
- 20. Data reuse success story # 2
- 21. • Background on data management • Why data management is important • Intro to best practices for data management • Library resources for data management. Photo by Carl Vogtmann
- 22. Data Management • Managing data effectively across the data lifecycle is critical for the success of a research project – Make a data management plan • Data management refers to all aspects of creating, housing, delivering, maintaining, and archiving and preserving data • It is one of the essential areas of responsible conduct of research • All subject areas (humanities, social science, and hard sciences) engage with data in many formats. • Absence of data documentation and management will limit the potential use of that data.
- 23. From: Fary, Michael and Owen, Kim, Developing an Institutional Research Data Management Plan Service, Educause ACTI white paper, January 2013, http://net.educause.edu/ir/library/pdf/ACTI1301.pdf Common Data Lifecycle Stages
- 26. Aspects of Research Data Management •DMPs/Planning •File organization & naming •Documentation & metadata •Storage & backup •Legal/ethical considerations •Sharing & reuse •Preservation & Archiving
- 27. Start with a plan…
- 28. • Types of data to be produced. • Standards or descriptions that would be used with the data (metadata). • How these data will be accessed and shared. • Policies and provisions for data sharing and reuse. • Provisions for archiving and preservation. https://flickr.com/photos/inl/5097547405 (CC BY 2.0) Points to address in your Data Management Plan (DMP)
- 35. Aspects of Research Data Management •DMPs/Planning •File organization & naming •Documentation & metadata •Storage & backup •Legal/ethical considerations •Sharing & reuse •Preservation & Archiving
- 36. Thoughts on naming stuff and why you should care… • Find your files easier • Creates uniformity • Allows for sorting • Understand what is “under the hood” • Allows for versioning
- 37. Directories • Folders should be major functions/activities • Subfolders by year • Make folder names explanatory • Avoid personal names • Avoid duplication • Simple and simplistic Source: http://bentley.umich.edu/dchome/resources/filenaming.php
- 38. Some good data practices File organization and naming • Label and define the content of your data files in a systematic way • Use descriptive file names – For example not- FIAGC (Fluffy is a great cat) but age, blood pressure etc. • Use consistent date formatting ( e.g. YYYYMMDD) • Keep file names short (no more than 25 characters) • Don’t use special characters • Use underscores instead of blank spaces • Keep track of versions • Don’t use confusing labels ( e.g. Pete’s data, final, final2, really final, really really final)
- 39. Aspects of Research Data Management •DMPs/Planning •File organization & naming •Documentation & metadata •Storage & backup •Legal/ethical considerations •Sharing & reuse •Preservation & Archiving
- 40. Description and Documentation (Metadata) • Commonly defined as “data about data” • It is information that describes the data • It gives you the ability to explain to your research to somebody that knows nothing about it • Provides information about one or more aspects of the data, such as: – Means of creation of the data – Purpose of the data – Time and date of creation – Creator or author of the data – Location on a computer network where the data were created – Standards used https://www.flickr.com/photos/musebrarian/3289649684/ (CC BY-NC-SA 2.0)
- 41. Metadata according to ICPSR… • A number of elements should be included in metadata, including, but not limited to: • Principal investigator • Funding sources • Data collector/producer • Project description • Sample and sampling procedures • Weighting • Substantive, temporal, and geographic coverage of the data collection • Data source(s) • Unit(s) of analysis/observation • Variables • Technical information on files • Data collection instruments
- 42. Aspects of Research Data Management •DMPs/Planning •File organization & naming •Documentation & metadata •Storage & backup •Legal/ethical considerations •Sharing & reuse •Preservation & Archiving
- 43. Data nightmares
- 44. Data nightmares Tweeted in 2012 by Gail Steinhart, Head of Research Services, Mann Library, Cornell University
- 45. Data nightmares
- 46. Toy Story 2 How Toy Story 2 Almost Got Deleted: Stories From Pixar Animation: ENTV https://www.youtube.com/watch?v=8dhp_20j0Ys
- 47. Storage, back up and securing data • Have at least 3 copies of your data- 2 local and 1 distant if possible • Don’t use your personal computer, data sticks or CDs if you can avoid it – They break, get lost, lose data over time • Use a hard drive if you can • Use cloud storage if you can (but be aware of sensitive data) flickr.com/photos/s_w_ellis/3877534599 (CC By 2.0)
- 49. Aspects of Research Data Management •DMPs/Planning •File organization & naming •Documentation & metadata •Storage & backup •Legal/ethical considerations •Sharing & reuse •Preservation & Archiving
- 50. Legal Concerns • Intellectual property rights • Copyright- see the NU policy on copyright http://invo.northwestern.edu/policies/copyright-policy • Patents • Trade secrets • Licensing • Creative Commons • Monetary charges for data usage • Open source versus proprietary software • Data retention
- 51. Aspects of Research Data Management •DMPs/Planning •File organization & naming •Documentation & metadata •Storage & backup •Legal/ethical considerations •Sharing & reuse •Preservation & Archiving
- 52. Preservation and Sharing data • Some options for preserving and sharing data – Self-archive – Institutional repository – Open data repository – National or international data archive or repository By Florian Hirzinger - www.fh-ap.com (Own work (Florian Hirzinger)) [CC BY-SA 3.0 (http://creativecommons.org/licenses/by-sa/3.0) or GFDL (http://www.gnu.org/copyleft/fdl.html)], via Wikimedia Commons
- 56. NU’s Repositories • The ARCH- Gateway to discovery – https://arch.library.northwestern.edu – COMING SOON • Digital Hub- Galter Health Sciences Library – https://digitalhub.northwestern.edu/
- 61. • Background on data management • Why data management is important • Intro to best practices for data management • Library resources for data management. Photo by Carl Vogtmann
- 62. Aspects of Research Data Management •DMPs/Planning •File organization & naming •Documentation & metadata •Storage & backup •Legal/ethical considerations •Sharing & reuse •Preservation & Archiving
- 63. RESOURCES: Northwestern University Library Data Management LibGuide: http://libguides.northwestern.edu/datamanagement DMPTool: https://dmp.org/ Northwestern University's Research Data: Ownership, Retention and Access Policy: http://www.research.northwestern.edu/policies/documents/research_data.pdf Cunera Buys- Data mangement librarian: c-buys@northwestern.edu