This talk was presented at the BioCaddie http://biocaddie.org/ workshop at the Force15 conference (https://www.force11.org/meetings/force2015) on changing the future of scholarly communication. The goal was to increase awareness of why a Semantic Web-compliant standard was needed for describing data, where current standards fall short, and how this new emerging standard that extends prior efforts can aid data discovery and integration. This work is being lead by Michel Dumontier, Alasdair Gray, Joachim Baran, and M. Scott Marshall; participants and end-user testers are welcome, see: http://tiny.cc/hcls-datadesc-ed

1. Describing Datasets with the W3C
HCLS standard
Melissa Haendel
Michel Dumontier

2. World Wide Web Consortium (W3C)
 The W3C is the main international standards
organization for the World Wide Web
 The W3C is made up of over 400 member
organizations for the purpose of working
together in the development of standards for the
World Wide Web
 W3C has sophisticated development and
community validation procedures for standards
development

3. The Semantic Web
is the new global web of knowledge
It involves standards for publishing, sharing, and querying
facts, expert knowledge and services
It is a scalable approach to the
discovery of independently formulated
and distributed knowledge
Cyganiak and Jentzsch. http://lod-cloud.net/

4. Resource Description Framework
 Language to represent knowledge
 Logic-based formalism -> automated reasoning
 graph-like properties -> data analysis
 Good for:
 Describing in terms of type, attributes, relations
 Integrating data from different sources
 Sharing the data (W3C standard)
 Reusing what is available, developing what you need,
and contributing back to the web of data

5. Challenge: Working with Web Data
 Often have inadequate descriptions so we don’t know what
they are about or how they were constructed
 Datasets change over time, but often don’t come with
versioning information
 May have been constructed using other data, but it’s not clear
which version of data was used or whether these were
modified
 Data may be available in a variety of formats
 There may be multiple copies of data from different providers,
but it’s unclear if they are exact copies or derivatives
 Version of standard or vocabulary used not indicated
 Data registries are not synchronized and can contain
conflicting information

6. Key Use Cases for HCLS Dataset
description
1. Dataset Identification, Description, Licensing and
Provenance
2. Dataset Discovery (via Catalog)
3. Exchange of Dataset Descriptions
4. Dataset Linking
5. Content Summary
6. Monitoring of Dataset Changes

7. Objectives
 Develop a guidance note for reusing existing
vocabularies to describe datasets with RDF
– Mandatory, recommended, optional descriptors
– Identifiers
– Versioning
– Attribution
– Provenance
– Content summarization
 Recommend vocabulary-linked attributes and
value sets
 Provide reference editor and validation

8. We complied a list of metadata fields
used across the community
and then surveyed over 20 vocabularies to see if they
provided relevant metadata elements or value sets…
…to produce a big spreadsheet that maps metadata
needs with existing vocabularies

9. Dublin Core Metadata Initiative
Widely used
Broadly applicable
– Documents
– Datasets
✗Generic terms
✗Not comprehensive
✗No required properties
“Date: A point or period of time
associated with an event in the
lifecycle of the resource.”

10. DCAT: Data Catalog
 Separates Dataset and Distribution
✗No versioning
✗No prescribed properties

11. No single vocabulary provides
all key metadata fields

12. http://tiny.cc/hcls-datadesc

14. Included Vocabularies

15. Three Component Metadata Model:
description – version – distribution

16. Description
 Identifiers
 Title
 Description
 Homepage
 License
 Language
 Keywords
 Concepts and vocabularies used
 Standards
 Publication

17. Attribution
 Simple Model
– Individuals are related to roles using specific
properties
e.g. dct:creator, pav:createdBy, pav:curatedBy
 Expandable Model
– Individuals are related to roles and dates via
associated object
– PROV, VIVO-ISF

18. Provenance and Change
 Version number
 Source
 Provenance: retrieved from, derived from,
created with
 Frequency of change

19. Availability
 Format
 Download URL
 Landing page
 SPARQL endpoint

20. VoID Editor
Tools to create the metadata

21. Tools to validate the metadata
New version
using ShEx in
development

22. HCLS:
http://www.w3.org/blog/hcls/
Mailing list: http://lists.w3.org/Archives/Public/public-
semweb-lifesci/
Editors’ Draft:
http://tiny.cc/hcls-datadesc-ed
W3C Interest Group Note:
http://tiny.cc/hcls-datadesc
Special thanks to Alasdair Gray, Scott Marshall, Joachim Baran
Thanks to all other contributors to the HCLS note