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Emerging Standards: Data and Data Exchange in Scholarly Publishing - Jay Henry at CSE 2016


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Ringgold is one of several organizations that are putting forth ideas to standardize data and data exchange throughout scholarly publishing. This session discussed new initiatives that address such challenges as standardizing conflict of interest reporting, easily identifying funding sources, clarifying contributor roles for research papers, and managing institution disambiguation.

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Emerging Standards: Data and Data Exchange in Scholarly Publishing - Jay Henry at CSE 2016

  1. 1. Jay Henry Chief Marketing Officer
  2. 2. DOI ISSN Author ORCID Author Affiliations (ISNIs or RING IDs) Title Year Published Subjects Circulation Data Abstract
  3. 3. *This means data that can be linked together through unambiguous identification and exchanged with others Governed Trusted Transparent And contain appropriate metadata In order to be effective, identifiers must be:
  4. 4. Persistent numeric or alpha-numeric designations associated with a single entity Entities can be an institution, person, or piece of content (People, Places, & Things) 1. Disambiguate, aka enforce uniqueness 2. Enable linking, aka data integration and interoperability In other words, they provide a simple basis for data governance
  5. 5. ◦ Break down silos ◦ Keep data current and synchronised ◦ Enable staff to interact with data more effectively ◦ Simplify data exchange ◦ Improve overall data quality Institutional Identifiers CRM Electronic document storage Usage statistics Author Database Fulfilment system Membersh ip system License Validation Manuscript Submission System
  6. 6. • Resources & personnel required to join existing records to IDs or an authority file • Build customized solutions mapping systems together • Improve data capture to require an ID upon record creation • Manual vs programmatic cost-benefit questions • Design new reporting and analysis tools to leverage newly linked datasets
  7. 7. Researchers – create Current Research Information Systems (CRIS) – one portal to figure out how to best conduct research, who to work with, who will fund it, what else has been contributed to the subject thus far, where is the best equipment to help further the research. Funders – Want to track areas of interest, identify worthwhile pursuits, and see where their money goes. Institutions – Demonstrate research output more accurately and precisely describe the institution’s contribution and who is affiliated with that work. Publishers – Facilitate transactions of all types from content discovery to delivery of author royalties. Improved market analysis and targeted advertising.
  8. 8.  ISO Standard 27729  ISNI is designed to be a “bridge identifier”  Covers any type of entity ISNI Number ISNI Number Party ID 2Party ID 1 Proprietary Information and/or Metadata Proprietary Information and/or Metadata
  9. 9. In cooperation with ProQuest, OCLC, and other public and commercial entities, Ringgold has been working to map ISNIs to deeper datasets for the past two years. It’s taken time due to the problems with the raw source data, and the policies for assignment of the unique ISNI identifier.
  10. 10. At the same time ISNI records are loaded to the Ringgold Identify Database we will being issuing ISNIs for institutions. ProQuest (Bowker) is a Registration Agency as well, focusing on individuals.
  11. 11. ISNI (OCLC tech) Third Parties M E M E B E R S M E M E B E R S M E M E B E R S M E M E B E R S M E M E B E R S M E M E B E R S Proprietary Databases Members submit data to RAGs: a. auto-match b. audit match c. RAG assigns new ISNIs d. RAGs synch w/ ISNI e. ISNI used as bridge via Public Data Members can access “full” ISNI information but cannot provide or assign numbers to 3rd parties-- ISNI data can be used w/in internal systems (e.g. library may assign ISNIs to all individuals and departments within their institution
  12. 12. It was a desire to “help” authors differentiate and disambiguate themselves that got ISNI started. Along the way, a lot has been learned. A specific example, that often doesn’t get a lot of attention, is the need for privacy protection whenever there is an Identification process underway… this holds true for individuals and institutions. Our industry spends a great deal of time discussing “open data”, but there are many times when that data should not (or cannot) be made public (physicist romance author, animal tester, military applications, etc….)
  13. 13. The Semantic Web cannot exist without well structured data Things take on a life of their own Vastness Vagueness Uncertainty Inconsistency Deceit The challenges to creating a world of content tagged with meaning: Standard Identifiers can help with the middle three – Artificial Intelligence will handle Vastness and Deceit
  14. 14. Thank you Jay Henry Chief Marketing Officer