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Metadata, Ontologies, and the Interoperability Continuum

Jane Greenberg, Ph.D.

Professor and Director of the Metadata Research Center, Drexel University

NSF/OAC 1940239, and #2118201

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Overview

  1. Offer some definitions
  2. Offer a rationale of why we seek interoperability
  3. Raise questions
    • Are we approaching metadata interoperability goals the right way?
    • What is good, bad, and… perhaps even worse?
    • Should we modify our approach to interoperability? If so, how?
  4. Wrap-up, any concrete next steps/action items?

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Interoperability

  • The ability of different types of computers, networks, operating systems, and applications to work together effectively, without prior communication, in order to exchange information in a useful and meaningful manner.
    • Three aspects: semantic, structural and syntactical

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(DCMI Glossary: http://dublincore.org/documents/usageguide/glossary.shtml)

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An Interoperability Model

Semantic Interoperability

    • Feature: Definition/meaning, vocabulary
    • Facilitated by: Metadata registries, application profiles, Crosswalks

Structural Interoperability

    • Feature: Modeling/frameworks, packaging
    • Facilitated by: RDF, DCAM/DCAP, DCAT, Schema.org, …

Syntactical Interoperability

    • Feature: Encoding
    • Facilitated by: X/HTML, XML, MARC, BibTeX, JSON-LD

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Another model

Zeng, Marcia, 2019: https://www.isko.org/cyclo/interoperability

Exchange of data through networks, computers, web services …system protocols… transportation

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Why interoperability?  

The exchange of data/information among users, applications, and systems can help advance research, lead to new discoveries.  

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Question 1: Are we metadata approaching interoperability goals the right way?

Answer: Yes and No

YES

NO (maybe not?)

  • Building bridges among various communities
  • Collaboration is good

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  • Extremely, extremely time consuming (but good work takes time?)
  • Interoperability for the sake of interoperability without a clear goal of the scientific question

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Question 1: What is good, bad, and… perhaps even worse?�

Good

Bad

Worse

  • Many wonderful, interoperable repositories supporting data discovery
  • OAI, EML, DDI, Schema.org RDF/Linked Data, etc.
  • Keith’s effort! ☺

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  • Competing and overlapping metadata standards
  • Dumbing down to achieve interoperability
  • Multiple competing standards, e.g., MLA, APA, Chicago… indicative of the future…
  • Still a prevailing not-invented-here attitude
  • Adoption of existing standard/s doesn’t always support the science, waste of time and money

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Questions 3: Should we modify our approach to interoperability? If so, how?�

    • What is (might be) the role of AI in supporting the interoperability continuum?
    • Where should we start our interoperability quest?
    • What questions should be asked first?
    • Should interoperability be system driven or science driven, and are these two goals at odds?

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Overview

  1. Offer some definitions
  2. Offer a rationale of why we seek interoperability
  3. Raise questions
    • Are we approaching interoperability goals the right way?
    • What is good, bad, and… perhaps even worse?
    • Should we modify our approach to interoperability? If so, how?
  4. Wrap-up, any concrete next steps/

action items?