Successfully reported this slideshow.
Your SlideShare is downloading. ×

Illusions of Grandeur: Trust and Belief in Cultural Heritage Linked Open Data

Illusions of Grandeur: Trust and Belief in Cultural Heritage Linked Open Data

Download to read offline

What is the notion of trust, when it comes to publishing linked open data in the cultural heritage sector? This presentation discusses some aspects with relation to three primary questions: How do we trust what was said, trust that the institution said it, and trust what it means?

What is the notion of trust, when it comes to publishing linked open data in the cultural heritage sector? This presentation discusses some aspects with relation to three primary questions: How do we trust what was said, trust that the institution said it, and trust what it means?

More Related Content

Related Books

Free with a 30 day trial from Scribd

See all

Related Audiobooks

Free with a 30 day trial from Scribd

See all

Illusions of Grandeur: Trust and Belief in Cultural Heritage Linked Open Data

  1. 1. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Illusions of Grandeur: Trust and Belief in Cultural Heritage Linked Open Data University of Birmingham & Trinity College Dublin Digital Humanities Network Lecture Series: Trust and Authority in the Digital Age Tuesday 25th of May, 2021 Robert Sanderson Director for Cultural Heritage Metadata Yale University
  2. 2. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Overview • Linked Open Data? • Trust what was said? • Sustainability, Diversity, Usability • Trust it was said? • Digital Signatures, Web Archiving • Trust what it means? • Ontologies, Vocabularies and Profiles, oh my! • Conclusion: Trust is SHARED
  3. 3. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Disclaimers! • Not a sociologist or psychologist • Not a cryptographer This talk is: • Reflections on observed behavior • In the context of information theory and practice
  4. 4. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Disclaimers! • Not a sociologist or psychologist • Not a cryptographer This talk is: • Reflections on observed behavior • In the context of information theory and practice • And probably all wrong :)
  5. 5. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 So … Linked Open Data? • The Web of Data • Institutions publish data on the web, just like web pages • At URLs under their domain name • The data uses shared standards • We’ll come back to these at the end • The data has references to other bits of data • … Published by the same institution • … Published by other institutions
  6. 6. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Linked Data: Who is Involved? • Researcher (user / data consumer) • Client Software Engineer • Publisher (institution making data available) • Content Specialist • Data Modeler • Software/Data Engineer • Standards Publishing Institutions • Editors & Contributors
  7. 7. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Basic Interaction Model
  8. 8. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 “Trust” in the Data? • Accuracy: Does the data correctly represent the state of the real world for the things it describes? (Objective) • Certainty: Belief of the Publisher as to the extent of the accuracy of the data. (Subjective) • Utility: Belief of the Researcher that the data is useful for fulfilling their current information need. (Subjective, time- specific)
  9. 9. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Data Accuracy, Certainty and Utility
  10. 10. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Uncertain, Accurate, Useful https://artgallery.yale.edu/collections/objects/76913
  11. 11. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Certain, Inaccurate, Not Useful https://search.library.yale.edu/catalog/1781761 (now corrected)
  12. 12. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Certain, Inaccurate, Not Useful Image from https://en.wikipedia.org/wiki/Blake_Edwards
  13. 13. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Relations between Actors • Confidence: Belief of the consumer in the current and past competence of the publisher (accuracy of data) • Trust: Belief of the consumer in the current and future benevolence of the publisher (availability of accurate data) • Dependence: When one actor relies on another for the successful outcome of a critical function
  14. 14. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Confidence and Trust
  15. 15. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Certainty of … Institution? ?
  16. 16. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Certainty of Content Specialists
  17. 17. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Data Published by Technical Specialists
  18. 18. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Personal or Institutional Trust? • Trust: From the reputation of the Institution including by considering confidence over time • Data: Created by actions & expressing the beliefs of many Individuals over time Linked Open Data is relatively new Our trust in the institution likely predates the LOD Should our trust be in the People, not the Institution?
  19. 19. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Trust: Availability of the Data Benevolence: Continuing to make accurate data openly available Sustainability: • Data must be a Product, not a Project • Needs continued investment in people and tech • Data must have Internal and External Impact • Must be demonstrably useful to the organization • And to others
  20. 20. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Persistence requires Sustainability • Institutional Longevity • Established organization more likely to continue to exist and retain its focus • More likely to have heard of it in the past • Institutional Resources • Well funded organization more likely to continue to invest in the product
  21. 21. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Persistence requires Sustainability • Appropriate Product Governance • Balancing internal / external participation • Balancing recognition of institution / individuals • Balancing quantity / quality • Balancing accuracy / usability • Ensuring diversity …
  22. 22. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Trust: Similarity People tend to view the actions of other members of groups with which they identify (in-groups) more favorably than those of members of groups with which they do not. Even when the action is identical. We are more likely to trust organizations that seem to share similar missions, constituencies or worldviews to our own. Summary: https://en.wikipedia.org/wiki/In-group_and_out-group
  23. 23. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Similarity/Diversity Paradox Cultural Heritage is diverse, spanning all human activity. Fully understanding that heritage requires systemic diversity, both at institutional and individual levels. We are conditioned to trust those that are most similar to us, where we should be trusting those that are most diverse.
  24. 24. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Structuring Data is a Political Act with Ethical Implications https://lincsproject.ca/events/lincs-conference-2021/ • Information systems enact systems of power • All data are contextual, discursively produced, and historically contingent • There are many different kinds of knowledge, and ways to come to know things -- Erin Canning, LINCS Project (Linked Infrastructure for Networked Cultural Scholarship)
  25. 25. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Illusions of Grandeur • Similarity, Impact, Longevity and Resourcing: Reputation • Governance, Internal Impact, Diversity, People: Invisible We base our usage of data on the illusory grandeur of the organization, which has nothing to do with the data itself
  26. 26. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Linked Data: Who is Involved? • Researcher (user / data consumer) • Client Software Engineer • Publisher (institution making data available) • Content Specialist • Data Modeler • Software/Data Engineer • Standards Publishing Institutions • Editors & Contributors
  27. 27. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Client Developer
  28. 28. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Usability The data must be usable by a software engineer implementing an application’s user interface, in order to be presented to the researcher. The user of the data is the application developer The researcher experiences the data only through the lens of the developer’s application
  29. 29. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Utility is Judged through the Application
  30. 30. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Perceived Utility depends on Data Usability
  31. 31. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Utility is Judged through the Application
  32. 32. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Perceived Utility depends on Data Usability
  33. 33. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Trust External Impact Perceived Utility
  34. 34. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Design Patterns for Usability 1. Scope design through shared use cases 2. Design for international use 3. As simple as possible, but no simpler 4. Make easy things easy, complex things possible 5. Avoid dependency on specific technologies 6. Use REST / Don’t break the web 7. Separate concerns, keep APIs loosely coupled 8. Design for JSON-LD, using LOD principles 9. Follow existing standards & best practices, when possible 10. Define success, not failure (for extensibility) https://iiif.io/api/annex/notes/design_patterns/, https://linked.art/api/1.0/principles/
  35. 35. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Trust that it was Said?
  36. 36. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Don’t Fear the Network • Trust that the data will be delivered when requested • = Data Availability • Trust that the data will not be modified en route • = Data Integrity Baseline Assumptions: • Deliver data from own domain via HTTPS • Confidentiality is not a concern (data is open)
  37. 37. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 I know … Blockchains! https://www.hyperledger.org/blog/2018/04/19/lessons-learned-from-hyperledger-fabric-poc-projects
  38. 38. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 More simply…
  39. 39. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Linked Data Signatures Important aspect of blockchain is the signature of the data: • Mathematical proof of data integrity in an untrusted communication channel • Any change to the data changes the signature Linked Data Signatures are coming in the W3C But they’re also unnecessary for our use cases… https://w3c.github.io/lds-wg-charter/explainer.html
  40. 40. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Web Archiving Public archiving of open data: • Trusted third party to ensure integrity and availability • Many CH organizations already engaged with web archiving, for digital preservation purposes • Allows “time travel” through different versions • Across multiple archives • Memento / IETF RFC 7089 http://mementoweb.org/guide/, esp. http://dx.doi.org/10.1109/MIC.2012.78
  41. 41. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Ensuring Completeness: Harvestable How do we ensure that all of the data is archived? Need to know: • What data exists? • When does it change? Solutions: • OAI-PMH • ResourceSync • Activity Streams IIIF Change Discovery https://iiif.io/api/discovery/
  42. 42. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Separating Accuracy and Accessibility
  43. 43. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Trust what the Data Means? How can the researcher be sure that their understanding of the information is what was intended by the content specialist?
  44. 44. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Trust what the Data Means?
  45. 45. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 App Developer Needs to Understand Model
  46. 46. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 … Via a Shared Standard
  47. 47. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Standards Need Same Considerations as Data If the standard conveys the meaning, how do we trust the standard? • Sustainable products with governance and institutions • Archived, versioned and harvestable • Usable by data modelers and developers • Useful to content specialists and researchers • Diversity of institutions and people, in every role
  48. 48. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 • Conceptual Model • Abstract way to think about the world, holistically, consistently and coherently • Ontology • Shared set of terms to encode that thinking in a logical, machine-actionable way • Vocabulary • Curated set of sub-domain specific terms, to make the ontology more concrete encodes refines Model Ontology Vocabulary Abstraction Standards
  49. 49. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 encodes refines specialized by available by Model Ontology Vocabulary Profile API Implementation Standards A Profile is a selection of appropriate abstractions, to encode the scope of what can be described. An API is a selection of appropriate technologies, to give access to the data managed using the profile.
  50. 50. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Example: Linked Art • Model: CIDOC Conceptual Reference Model • Ontology: RDF encoding of CRM 7.1, plus extensions • Vocabulary: Getty AAT, plus minimal extensions • Profile: Art Museum oriented (but dips toes in adjacent domains) • API: JSON-LD format with 10 primary divisions of content See: https://linked.art/
  51. 51. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 … Via Shared Standards
  52. 52. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Trust is SHARED Trustable data and standards are: • Sustainable (necessary for ongoing use) • Harvestable (back-up plan & ease of access) • Available (online with clear usage license) • Reconciled (entities linked across systems) • Enhanced (incorporates others’ knowledge) • Diverse (institutions, people, practices)
  53. 53. Trust and Belief in Linked Open Data robert. sanderson @yale.edu @azaroth42 Thank You! Comments, Criticism and Questions all Welcome Robert Sanderson Director for Cultural Heritage Metadata Yale University robert.sanderson@yale.edu

Editor's Notes

  • Or at the very least naive
  • What do you need to know about Linked Data for this presentation to make sense? Don’t worry, there’s no need to talk about triples, inference, RDF, or anything like that.
  • Conflation of three separable features.
  • Looking for hair in materials for an analysis of human remains in a collection, then this record is very useful – high utility for that research question, but low for most others given the uncertain (but perhaps accurate) information.
  • Looking for the oldest person in our data… 39 trillion years old.
  • When we talk about trust, we often mean confidence.
  • Accuracy is needed, of course. Need to be confident that the institution knows what it is talking about.
    People come and go, but we want the data to remain open and available. Needs to have the right governance and motivations to continue to spend its resources for the good of the community
  • Another relevant factor for trust is similarity between trustor and trustee. I would trust Getty over Google, even if they both published the same data.
  • Resist the centralization and homogenization of knowledge, for that is the new cultural colonization. We need diverse ecosystems of data, not a single organization or monoculture.
  • But don’t worry, it’s about to get worse when we add in the next actor…
  • So the researcher’s belief about the utility of the data, is dependent on the application’s rendition of that data. The same data rendered to the user in a different way might evoke different belief in its utility.
  • Utility of the data in aggregate across many researchers and users is a large factor in external impact. And external impact is a factor in our trust in the institution. Consider Wikidata – Usability, mostly from having a lot of information in one spot, and assuming some basic level of accuracy, building on the confidence of a similar but unrelated product – Wikipedia.
  • 3 & 4. Balance of Accuracy vs Usability – encoding the structured expression of certainty in the data reduces usability at the expense of marginal benefit over expressing it only in a human-understandable form
    9 – Coming back to standards in few.
  • 30 MINUTES
    But before standards…
  • Adam Soroka of the Smithsonian
  • Yes, you in the back who looks like the know the answer… yeah, no.
  • But if you do have a spare 69.3 million dollars, I also have some linked metadata about images to sell you.
  • Reducing the need for trust in the institution, only confidence. Can archive locally as well to avoid any third party trust.
  • 35 MINUTES
  • Now we have a bunch of lego bricks
  • The profile tells us how to put those lego bricks together in a useful way.
    The API tells the technologists how to get access to the results in a usable way.

×