Successfully reported this slideshow.
Enriching Scholarship
May 6, 2014
Natsuko Nicholls, UM Libraries
Elizabeth Moss, ICPSR
NIH (2003) Data Sharing Policy that all funding
applications of $500,000 or more per year are
expected to address data-sha...
International Mandates
Aug 2011… “expectation that all our funded
researchers should maximise access to
their research dat...
Journal Mandates
Dec 2013 . . .“We ask you to make available the data
underlying the findings in the paper, which would be...
Questions
 Sharing data—how does it happen?
 What is data publishing?
 Is data archiving the same?
 How can we find da...
Paradigm Shift
The nature of research has become…
 More quantitative/data-intensive
 More funder-driven
 More interdisc...
The focus of scholarly communication
has changed…
From:
 Preserve publications
 Preserve data
 Preserve both (at least ...
Publishing and Archiving
Scholarly
Communication
Availability Citability Validation
Scholarly
Publishing Data Archiving
Sc...
Data Dissemination Methods Indicated in
DMPs Written by UM Engineering Faculty
journal
publication
42%
faculty/
project we...
Data Dissemination Methods
 Submitted with journal article
 Appear in journal article upon publication
 Supplemental ma...
Repository Directory Lists
 IR
 OpenDOAR (over 2600 academic open access repositories
listed)
 Deep Blue (University of...
Disciplinary Data Repositories:
What to Look for?
 Subject/Discipline focus
 Hosted by…
 Access to data: open vs. restr...
More on Persistent IDs
 A DOI is a system for persistently identifying and locating digital objects;
Originally designed ...
Data Repositories
Let’s take a closer look at this example!
Data Papers: Going beyond Appendices and
Supplements
Data Journals
 Number of ‘Data Journals’
As of today, 70+ data journals*
 Journal host
a) Authors
b) Journals
c) Publish...
Data Journal Example
Geoscience Data Journal by Wiley
 Launched in Fall 2012
 Published on behalf of Royal Meteorologica...
Data Journal Example (continued)
Data centers/repositories approved by Geoscience Data Journal
 3TU.Datacentrum
 British...
Data Journal Example (continued)
Data Publisher Examples
 Wiley
 Geoscience Data Journal
 Ubiquity Press
 Journal of Open Archaeology Data
 Journal of...
Data Journal Examples (to name only a
few): Some Feature Comparison
Publisher Journal OA?
Publication
Fee per Article
Publ...
Located on U of M Campus
www.icpsr.umich.edu ICPSR: Inter-university Consortium for Political and Social Research
Signs of a Trusted Repository
 A unit of ISR, ICPSR is governed by a Counsel representing
over 700 member institutions, i...
Rich Metadata for Better Access,
Discovery, Context, and Reuse
 ICPSR formats, organizes and enhances deposited raw
resea...
Replication Datasets
http://www.icpsr.umich.edu/icpsrweb/deposit/pra/index.jsp
Open Sharing for DMP Proposals
http://openicpsr.org/
Top 10 Data Downloads (last six months)
(non-anonymous, distinct users downloading one or more files)
Title Archive # Down...
Who uses these shared data?
How are they used?
With what impact?
The ICPSR Bibliography of
Data-related Literature
 Link research data to the scholarly literature about it
 Aid students...
Linking the Data to the Literature
Altmetrics for research data
 Easier to access and analyze much more
research data online
 New focus on sharing that res...
Publishers
 Springer
 Elsevier
 Wiley
 Cambridge
Journals
 BMJ Journals
 Nature
Publish
Group
 PLoS
Altmetrics
Aggr...
Impact Story:
Product-level Metric
 “New ways to measure the research impact . . . of
emerging products like blog posts, ...
Artifact-level Metric
Source: http://www.plumanalytics.com/metrics.html
Integration with Web of Science All
Databases: Research data is equal
to research literature
Articles linked to underlying data.
Increased data discovery.
Reward for data citation.
Potential for automated tracking.
Elsevier Connect
 “Elsevier is collaborating with a rapidly growing number of
external data set repositories to optimize ...
Source: http://www.slideshare.net/ElsevierConnect/columbia-27feb13v2ext
For Better Metrics on Research
Data Impact
 Need more aggregator and repository data to be
exposed for altmetric harveste...
Formal Citation, in the References,
with the DOI
doi:10.3886/ICPSR21240
http://www.flickr.com/photos/papertrix/38028138/
Some Challenges
No Common Practice of Formal
Data Citation
 Abstract?
 Acknowledgements?
 Charts and Tables?
 Appendices?
 Discussion...
Examples of Bad Data Citation
Poorly described and cited data
+
Excessive human search effort, extensive collection
knowle...
Examples of Good Data Citation
Formal data
Citing with
a DOI
+
Minimal human search effort
=
High hit accuracy for the cos...
Basic Data Citation Format
Creator (Year) Title. Publisher. Identifier
(For datasets that have DOIs, DataCite and CrossRef...
Additional Elements
Location / Availability: The web address of the dataset is essential
when the identifier can’t be used...
Data Citation Examples
Deschenes, Elizabeth Piper, Susan Turner, and Joan Petersilia.
Intensive Community Supervision in M...
Joint Declaration of Data
Citation Principles
1. Future Of Research Communication and
E-Scholarship (FORCE11)
2. Committee...
Eight Principles
1. Importance--Data should be considered
legitimate, citable products of research. Data
citations should ...
Eight Principles
3. Evidence—In scholarly literature, whenever and
wherever a claim relies upon data, the
corresponding da...
Eight Principles
5. Access—Data citations should facilitate access to
the data themselves and to such associated
metadata,...
Eight Principles
7. Specificity and Verifiability—Data citations
should facilitate identification of, access to, and
verif...
Eight Principles
8. Interoperability and flexibility—Data citation
methods should be sufficiently flexible to
accommodate ...
Make Your Data Count
 If it’s not cited, it can’t be counted
 Without counting data use, there is no
accurate way to mea...
Questions Answered?
 Sharing data—how does it happen?
 What is data publishing?
 Is data archiving the same?
 How can ...
Thank you!
Natsuko Nicholls
hayashin@umich.edu
Elizabeth Moss
eammoss@umich.edu
Enriching Scholarship 2014 Beyond the Journal Article: Publishing and Citing the Underlying Data
Enriching Scholarship 2014 Beyond the Journal Article: Publishing and Citing the Underlying Data
Enriching Scholarship 2014 Beyond the Journal Article: Publishing and Citing the Underlying Data
Enriching Scholarship 2014 Beyond the Journal Article: Publishing and Citing the Underlying Data
Enriching Scholarship 2014 Beyond the Journal Article: Publishing and Citing the Underlying Data
Enriching Scholarship 2014 Beyond the Journal Article: Publishing and Citing the Underlying Data
Enriching Scholarship 2014 Beyond the Journal Article: Publishing and Citing the Underlying Data
Enriching Scholarship 2014 Beyond the Journal Article: Publishing and Citing the Underlying Data
Enriching Scholarship 2014 Beyond the Journal Article: Publishing and Citing the Underlying Data
Enriching Scholarship 2014 Beyond the Journal Article: Publishing and Citing the Underlying Data
Enriching Scholarship 2014 Beyond the Journal Article: Publishing and Citing the Underlying Data
Enriching Scholarship 2014 Beyond the Journal Article: Publishing and Citing the Underlying Data
Enriching Scholarship 2014 Beyond the Journal Article: Publishing and Citing the Underlying Data
Enriching Scholarship 2014 Beyond the Journal Article: Publishing and Citing the Underlying Data
Enriching Scholarship 2014 Beyond the Journal Article: Publishing and Citing the Underlying Data
Enriching Scholarship 2014 Beyond the Journal Article: Publishing and Citing the Underlying Data
Enriching Scholarship 2014 Beyond the Journal Article: Publishing and Citing the Underlying Data
Enriching Scholarship 2014 Beyond the Journal Article: Publishing and Citing the Underlying Data
Enriching Scholarship 2014 Beyond the Journal Article: Publishing and Citing the Underlying Data
Upcoming SlideShare
Loading in …5
×

Enriching Scholarship 2014 Beyond the Journal Article: Publishing and Citing the Underlying Data

549 views

Published on

Published in: Data & Analytics, Technology
  • Be the first to comment

  • Be the first to like this

Enriching Scholarship 2014 Beyond the Journal Article: Publishing and Citing the Underlying Data

  1. 1. Enriching Scholarship May 6, 2014 Natsuko Nicholls, UM Libraries Elizabeth Moss, ICPSR
  2. 2. NIH (2003) Data Sharing Policy that all funding applications of $500,000 or more per year are expected to address data-sharing in their application. NSF (2011) All funding proposals submitted on or after January 18, 2011, must include a “Data Management Plan” describing how the proposal will conform to NSF policy on the dissemination and sharing of research results. US Federal Funding Mandates
  3. 3. International Mandates Aug 2011… “expectation that all our funded researchers should maximise access to their research data with as few restrictions as possible. …. submit a data management and sharing plan as part of the application process.” 2007… “Researchers are to retain research data and primary materials, manage storage of research data and primary materials, maintain confidentiality of research data and primary materials.”
  4. 4. Journal Mandates Dec 2013 . . .“We ask you to make available the data underlying the findings in the paper, which would be needed by someone wishing to understand, validate or replicate the work. Our policy has not changed in this regard. What has changed is that we now ask you to say where the data can be found. As the PLOS data policy applies to all fields in which we publish, we recognize that we’ll need to work closely with authors in some subject areas to ensure adherence to the new policy. Some fields have very well established standards and practices around data, while others are still evolving, and we would like to work with any field that is developing data standards. We are aiming to ensure transparency about data availability.”
  5. 5. Questions  Sharing data—how does it happen?  What is data publishing?  Is data archiving the same?  How can we find data, access it, and reuse it?  How can we measure the impact of sharing data?  What’s the common denominator?
  6. 6. Paradigm Shift The nature of research has become…  More quantitative/data-intensive  More funder-driven  More interdisciplinary/collaborative  More transparent  More complicated in terms of cross-linking  More diverse in terms of citable scholarly outputs
  7. 7. The focus of scholarly communication has changed… From:  Preserve publications  Preserve data  Preserve both (at least separately) To:  Preserve publications and data ‘together’  Preserve the ‘relationships’ among them Paradigm Shift
  8. 8. Publishing and Archiving Scholarly Communication Availability Citability Validation Scholarly Publishing Data Archiving Scholarly Publishing that includes ‘Data Publication’
  9. 9. Data Dissemination Methods Indicated in DMPs Written by UM Engineering Faculty journal publication 42% faculty/ project website 36% conference presentation 11% "upon request" 11% NSF Engineering Data Management Plan Analysis, N=156
  10. 10. Data Dissemination Methods  Submitted with journal article  Appear in journal article upon publication  Supplemental materials (including codebooks)  Websites (prior/post publication)  Institutional repositories (prior/post publication)  Data archive per discipline’s culture of sharing  Data repository (may be assigned by journal publishers)  Data papers in data journals (may be independent of the journal article)  “Data upon request” via email (some/all)
  11. 11. Repository Directory Lists  IR  OpenDOAR (over 2600 academic open access repositories listed)  Deep Blue (University of Michigan Library)  DR  NIH Data Sharing Repositories (57 repositories)  Thomson Reuters Data Citation Index (174 repositories)  Databib (975 repositories listed)  re3Data.org (609 repositories listed) DataCite, re3data.org, and Databib announced collaboration towards one service under the auspices of DataCite by 2015
  12. 12. Disciplinary Data Repositories: What to Look for?  Subject/Discipline focus  Hosted by…  Access to data: open vs. restricted  Deposit of data: open vs. restricted  Deposit fee  Persistent identifiers (DOI, hdl)  Sustainability & preservation policy  (Non-) Proprietary file formats  Amount of data description/metadata (data package level, file level, data item level)  Associated code/software
  13. 13. More on Persistent IDs  A DOI is a system for persistently identifying and locating digital objects; Originally designed and developed for “journal articles”; ISO 26324 since 2012  DOI can be assigned by only DOI registration agencies: e.g. DataCite, CrossRef  Assigning DOI is not free (e.g. Costing ~$1 per DOI via CrossRef in 2013)  DOI: prefix + suffix • e.g. DOI for a dataset http://doi.org/10.3886/ICPSR27282.v1  DOI prefix is unique to each publisher/repository • ICPSR: 10.3886 • UK Data Service: 10.5255 • Figshare: 10.6084 • PANGAEA: 10.1594 • Dyad: 10.5061  Very similar to ‘handles’ in terms of persistency • e.g. U of M IR Deep Blue: e.g. http://hdl.handle.net/2027.42/106575  Moving towards “Data with DOI” just as any scholarly articles
  14. 14. Data Repositories Let’s take a closer look at this example!
  15. 15. Data Papers: Going beyond Appendices and Supplements
  16. 16. Data Journals  Number of ‘Data Journals’ As of today, 70+ data journals*  Journal host a) Authors b) Journals c) Publisher data repositories d) Data repositories (IR/DR)  Data journal article structure a) Intro/Overview b) Methods c) Dataset description d) Reuse potential Source: K. Akers and J. Green. Data Sharing and Publication, Presented at the Cyberinfrastructure (CI) Days Event, University of Michigan, Ann Arbor, MI, November 13-14, 2013. UP *Note: To see a full list of data journals that currently exist, see K. Akers’ blog post at: http://mlibrarydata.wordpress.com/2014/05/09/data-journals/
  17. 17. Data Journal Example Geoscience Data Journal by Wiley  Launched in Fall 2012  Published on behalf of Royal Meteorological Society  OA with author-pay model ($1,500 per article)  Publishes short data papers cross-linked to (and citing) datasets that have been deposited in approved data centers/repositories and awarded DOIs.  A data article describes a dataset, giving details of its collection, processing, file formats etc., but does not go into detail of any scientific analysis of the dataset or draw conclusions from that data.  The data paper should allow the reader to understand the when, why and how the data was collected, and what the data is.
  18. 18. Data Journal Example (continued) Data centers/repositories approved by Geoscience Data Journal  3TU.Datacentrum  British Atmospheric Data Centre (BADC)  British Oceanographic Data Centre (BODC)  CISL Research Data Archive  CSIRO Data Access Portal  Environmental Information Data Centre (EIDC)  Figshare  IEDA:EarthChem  IEDA:MGDS  National Center for Atmospheric Research (NCAR), USA  Earth Observing Lab (EOL), observational and supporting data from atmospheric science field experiments and arctic research  Research Data Archive (RDA), reference datasets for weather and climate research  National Geoscience Data Centre (NGDC)  NERC Earth Observation Data Centre (NEODC)  NOAA National Climatic Data Center (NCDC)  NOAA National Oceanographic Data Center (NODC)  NOAA National Geophysical Data Center (NGDC)  PANGAEA  Polar Data Centre (PDC)  Zenodo
  19. 19. Data Journal Example (continued)
  20. 20. Data Publisher Examples  Wiley  Geoscience Data Journal  Ubiquity Press  Journal of Open Archaeology Data  Journal of Open Psychology Data  Open Health Data  Journal of Open Research Software  Nature  Scientific Data
  21. 21. Data Journal Examples (to name only a few): Some Feature Comparison Publisher Journal OA? Publication Fee per Article Publisher hosts data? Approved data center/ repositories recommended for data deposit? How is the article called? DOI? Wiley Geoscience Data Journal Yes $1,500 No Yes ‘Data Paper’ Yes Ubiquity Press Open Archeology Data Yes $40 No Yes ‘Data Paper’ Yes Nature Publishing Group Scientific Data Yes $700 No Yes ‘Data Descriptor’ Yes
  22. 22. Located on U of M Campus www.icpsr.umich.edu ICPSR: Inter-university Consortium for Political and Social Research
  23. 23. Signs of a Trusted Repository  A unit of ISR, ICPSR is governed by a Counsel representing over 700 member institutions, including U of M  Long-term sustainability: “publishing” data for 52 years  Largest social science data repository in US with a catalog of over 8,000 studies containing thousands of files  Awarded the Data Seal of Approval from DANS  Federal agencies’ archives are housed at ICPSR and fully integrated with ICPSR’s collection  Data preservation standards followed for data long-term, guarding against deterioration, accidental loss, and digital obsolescence  Data are screened for confidentiality and privacy concerns. Stringent protections are in place for securing and distributing sensitive data.  Physical and virtual data enclaves for analyzing restricted- use data
  24. 24. Rich Metadata for Better Access, Discovery, Context, and Reuse  ICPSR formats, organizes and enhances deposited raw research data with meaningful metadata and documentation to make it complete, self-explanatory, and usable for future researchers  Study metadata and codebooks are generated according to the Data Documentation Initiative (DDI) XML standard  Search and filter online catalog with fielded metadata records to enhance discovery; side-by-side comparison using structured variable-level documentation in XML, tagged according to the DDI standard  All studies are registered with a unique identifier—DOIs from DataCite. ICPSR has been providing citations to its data since 1990 and started assigning DOIs in 2008
  25. 25. Replication Datasets http://www.icpsr.umich.edu/icpsrweb/deposit/pra/index.jsp
  26. 26. Open Sharing for DMP Proposals http://openicpsr.org/
  27. 27. Top 10 Data Downloads (last six months) (non-anonymous, distinct users downloading one or more files) Title Archive # Downloads National Longitudinal Study of Adolescent Health (Add Health), 1994-2008 DSDR 1,188 General Social Survey, 1972-2012 [Cumulative File] ICPSR 737 Chinese Household Income Project, 2002 DSDR 720 India Human Development Survey (IHDS), 2005 SAMHDA 445 Collaborative Psychiatric Epidemiology Surveys (CPES), 2001-2003 [United States] CPES 407 National Survey on Drug Use and Health, 2012 SAMHDA 314 Children of Immigrants Longitudinal Study (CILS), 1991-2006 DSDR 289 National Crime Victimization Survey, 2012 NACJD 260 National Prisoner Statistics, 1978-2011 NACJD 249 Historical, Demographic, Economic, and Social Data: The United States, 1790-2002 ICPSR 245
  28. 28. Who uses these shared data? How are they used? With what impact?
  29. 29. The ICPSR Bibliography of Data-related Literature  Link research data to the scholarly literature about it  Aid students, instructors, researchers, and funders to discover and understand data use  A searchable database currently containing over 65,000 citations of known published and unpublished works resulting from analyses of data archived at ICPSR  It generates study bibliographies linking each study with the literature about it, and out to the full text
  30. 30. Linking the Data to the Literature
  31. 31. Altmetrics for research data  Easier to access and analyze much more research data online  New focus on sharing that research data  Increasing use of social media to discuss, via tweets, likes and blog posts  More online tools to download, collaborate and share, like Mendeley, Figshare, SlideShare, Dryad and ResearchGate, DeepBlue, openICPSR  Dependent on good citation practice
  32. 32. Publishers  Springer  Elsevier  Wiley  Cambridge Journals  BMJ Journals  Nature Publish Group  PLoS Altmetrics Aggregators • Altmetric • ImpactStory • Plum Analytics Funders • NSF • Sloan Foundation** • MacMillan • EBSCO **The Alfred P. Sloan Foundation helps fund ImpactStory, and is now funding the National Information Standards Organization (NISO) to develop standards and recommended best practices for altmetrics.
  33. 33. Impact Story: Product-level Metric  “New ways to measure the research impact . . . of emerging products like blog posts, datasets, and software . . . to build a new scholarly reward system that values and encourages web-native scholarship.”  Open metrics, with context, using diverse products to provide researchers with a “comprehensive impact report” of their research output Source: https://impactstory.org/about
  34. 34. Artifact-level Metric Source: http://www.plumanalytics.com/metrics.html
  35. 35. Integration with Web of Science All Databases: Research data is equal to research literature
  36. 36. Articles linked to underlying data. Increased data discovery. Reward for data citation. Potential for automated tracking.
  37. 37. Elsevier Connect  “Elsevier is collaborating with a rapidly growing number of external data set repositories to optimize interoperability between their data sets and research articles on ScienceDirect. As part of the Article of the Future project, this reciprocal linking aims to expand the availability of research data and improve the researcher workflow.”  “Elsevier encourages authors to submit their data sets to external repositories. . . But not all authors know how or where to submit their data, and not all authors are aware of the possibilities that data linking offers. . .The recent agreement with Dryad Digital Repository marked the 35th data linking partnership Elsevier has established. . .” Source: http://www.elsevier.com/connect/bringing-data-to-life-with-data-linking
  38. 38. Source: http://www.slideshare.net/ElsevierConnect/columbia-27feb13v2ext
  39. 39. For Better Metrics on Research Data Impact  Need more aggregator and repository data to be exposed for altmetric harvesters like ImpactStory  More integrated efforts among libraries, publishers, archives, and funders. For example:  The Data Conservancy, IEEE, and Portico receive Alfred P. Sloan Foundation grant to connect publications and their linked data
  40. 40. Formal Citation, in the References, with the DOI doi:10.3886/ICPSR21240
  41. 41. http://www.flickr.com/photos/papertrix/38028138/ Some Challenges
  42. 42. No Common Practice of Formal Data Citation  Abstract?  Acknowledgements?  Charts and Tables?  Appendices?  Discussion?  Footnotes?  Sample?  Methods? References!  Without an explicit citation, reader must infer or be out of luck  No attribution—no credit  No access—no reuse  No discernible impact!
  43. 43. Examples of Bad Data Citation Poorly described and cited data + Excessive human search effort, extensive collection knowledge = Too costly, too questionable for confident measure of impact
  44. 44. Examples of Good Data Citation Formal data Citing with a DOI + Minimal human search effort = High hit accuracy for the cost, and better confidence of impact measures
  45. 45. Basic Data Citation Format Creator (Year) Title. Publisher. Identifier (For datasets that have DOIs, DataCite and CrossRef provide a citation formatter to generate a citation in various journal styles.) Core Elements Creator(s): Individual(s) or organization responsible for creating the dataset. Year: Year the dataset was published, not necessarily created. Title: Should be as descriptive as possible Publisher: Organization that provides access to the dataset (e.g. Dryad, Zenodo) Identifier: Persistent, unique identifier (e.g. a DOI) Source: http://datapub.cdlib.org/datacitation/ How to Cite Data
  46. 46. Additional Elements Location / Availability: The web address of the dataset is essential when the identifier can’t be used to reach the dataset. Version / Edition: Version of the dataset used in the present publication. Needed to reproduce analysis of versioned dynamic datasets. Access Date: Date of access for analysis in the present publication. Needed to reproduce analysis of continuously updated dynamic datasets. Format / Material Designator: e.g., database, CD-ROM. Feature Name: A description of the subset of the dataset used. May be a formal title or a list of variables (e.g., concentration, optical density). Verifier: Used to confirm that two datasets are identical. Most commonly a UNF or MD5 checksum. Series: Used if the dataset is part of series of releases (e.g., monthly) Contributor: e.g., editor, compiler Source: http://datapub.cdlib.org/datacitation/ How to Cite Data
  47. 47. Data Citation Examples Deschenes, Elizabeth Piper, Susan Turner, and Joan Petersilia. Intensive Community Supervision in Minnesota, 1990-1992: A Dual Experiment in Prison Diversion and Enhanced Supervised Release. ICPSR06849-v1. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2000. doi:10.3886/ICPSR06849.v1 Esther Duflo; Rohini Pande, 2006, "Dams, Poverty, Public Goods and Malaria Incidence in India", http://hdl.handle.net/1902.1/IOJHHXOOLZ UNF:5:obNHHq1gtV400a4T+Xrp9g== Murray Research Archive [Distributor] V2 [Version] Sidlauskas B (2007) Data from: Testing for unequal rates of morphological diversification in the absence of a detailed phylogeny: a case study from characiform fishes. Dryad Digital Repository. doi:10.5061/dryad.20
  48. 48. Joint Declaration of Data Citation Principles 1. Future Of Research Communication and E-Scholarship (FORCE11) 2. Committee on Data for Science and Technology (CODATA) 3. Digital Curation Centre (DCC) Source: https://www.force11.org/datacitation
  49. 49. Eight Principles 1. Importance--Data should be considered legitimate, citable products of research. Data citations should be accorded the same importance in the scholarly record as citations of other research objects, such as publications. 2.Credit and Attribution--Data citations should facilitate giving scholarly credit and normative and legal attribution to all contributors to the data, recognizing that a single style or mechanism of attribution may not be applicable to all data.
  50. 50. Eight Principles 3. Evidence—In scholarly literature, whenever and wherever a claim relies upon data, the corresponding data should be cited. 4. Unique Identification—A data citation should include a persistent method for identification that is machine actionable, globally unique, and widely used by a community.
  51. 51. Eight Principles 5. Access—Data citations should facilitate access to the data themselves and to such associated metadata, documentation, code, and other materials, as are necessary for both humans and machines to make informed use of the referenced data. 6.Persistence—Unique identifiers, and metadata describing the data, and its disposition, should persist -- even beyond the lifespan of the data they describe.
  52. 52. Eight Principles 7. Specificity and Verifiability—Data citations should facilitate identification of, access to, and verification of the specific data that support a claim. Citations or citation metadata should include information about provenance and fixity sufficient to facilitate verifying that the specific timeslice, version and/or granular portion of data retrieved subsequently is the same as was originally cited.
  53. 53. Eight Principles 8. Interoperability and flexibility—Data citation methods should be sufficiently flexible to accommodate the variant practices among communities, but should not differ so much that they compromise interoperability of data citation practices across communities.
  54. 54. Make Your Data Count  If it’s not cited, it can’t be counted  Without counting data use, there is no accurate way to measure the impact of your shared data  Without a well-formed citation, your data cannot take advantage of the potential of linked scholarly publishing  Store your data where citations are unique and persistent  Cite your own data and others’ in your publications
  55. 55. Questions Answered?  Sharing data—how does it happen?  What is data publishing?  Is data archiving the same?  How can we find data, access it, and reuse it?  How can we measure the impact of sharing data?  What’s the common denominator?
  56. 56. Thank you! Natsuko Nicholls hayashin@umich.edu Elizabeth Moss eammoss@umich.edu

×