Linked Data Competency Index Linked Library Data Interest Group (ALCTS/LITA) January 9, 2016

Outcomes** Competency Index for learning Linked Data - to help learners and instructors identify and prioritize skills for proficiency in Linked Data. Exploratorium of educational resources for learning the competencies. ** both to be sustained and evolving

About us Project under the jurisdiction of the Dublin Core Metadata Initiative (DCMI) Education & Outreach Committee. Funded by the Institute of Museum and Library Services (IMLS). Exploratorium & Competency Index will be sustained by DCMI to support its education and outreach activities.

Four Questions

What resources do you use to learn & teach Linked Data?

Are there ‘known unknowns’ you have about learning Linked Data? (Will there ever be a clear definition of what falls into the scope of “Linked Data?”) https://en.wikipedia.org/wiki/Known_and_Unknown:_A_Memoir ISBN: 978-1-59523-067-6

Are there specific tasks you have tried to learn and be unable to find a resource for?

What are some use cases for leveraging a competency index?

Outcome 1: Competency Index

6 top-level clusters & approx. 125 concepts http://explore.dublincore.net/linked-data-learning-resources/

Six top-level clusters: Fundamentals of Resource Description Framework Identity in RDF RDF data model Related data models RDF serialization RDF vocabularies Finding RDF vocabularies Maintaining RDF vocabularies Versioning RDF vocabularies Publishing RDF vocabularies Mapping RDF vocabularies RDF application profiles Fundamentals of Linked Data Web technology Linked data principles Linked Data architectures and services Linked Data policies and best practices Non-RDF Linked Data

Six top-level clusters (cont): Creating and transforming RDF Data Managing identifiers (URIs) Creating RDF data Versioning RDF data RDF data provenance Cleaning and reconciling RDF data Mapping and enriching RDF data Interacting with RDF Data Finding RDF Data Programming RDF Data Querying RDF Data Visualizing RDF Data Reasoning over RDF Assessing RDF data quality RDF Data analytics Manipulating RDF Data Creating Linked Data applications Storing RDF data Linked Data application architecture Linked Data mashups

Drilling down…. Fundamentals of Resource Description Framework RDF data model Competency: Formulates QNames as a shorthand mechanism in writing prefixes for long URIs Benchmark: Uses prefixes for URIs in RDF specifications and data Interacting with RDF Data Querying RDF Data Competency: Demonstrates a working knowledge of the forms and uses of SPARQL result sets (SELECT, CONSTRUCT, DESCRIBE, and ASK) Benchmark: Uses the SELECT clause to identify the variables to appear in a table of query results Benchmark: Uses DESCRIBE to extract a single graph containing RDF data about resources

Learning Resources

    SPARQL in 11 minutes, by Bob Ducharme https://www.youtube.com/watch?v=FvGndkpa4K0

Resource to competency mapping At 0:46 in the video, we get the anatomy of a triple. This can to be mapped to a competency in the competency index. In the index, we find: Knows the subject-predicate-object structure of a triple

Mapping from Ducharme to competencies im an editorial board member. this just shows my process for mapping. i was going through Bob Ducharmes book on sparql and basically mapped the different examples and skills to particular pages in the book.

What’s under the hood? (It’s RDF) The resource metadata are encoded in RDFXML, using schema.org and dc terms: <ns0:dateCreated rdf:datatype="http://purl.org/dc/terms/W3CDTF">2014- 01-01T07:00:00.000Z</ns0:dateCreated> <ns0:about xml:lang="en-US">SPARQL syntax</ns0:about> <ns0:about xml:lang="en-US">filtering</ns0:about> <ns0:about xml:lang="en-US">sorting</ns0:about> [show full resource.xml for Gruber tutorial?] so we have 3 namespaces here: xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#", xmlns:ns0="http://schema.org/", xmlns:ns1="http://purl.org/dc/terms/">. this is just a snippet of a metadata, RDF-ized document describing a resource in our exploratorium. so here we see the resource is about sparql syntax, specifically filtering and sorting

Outcome 2: Exploratorium

Exploratorium: Where competencies and resources meet http://explore.dublincore.net/linked-data-learning-resources/

Exploratorium: Where competencies and resources meet http://explore.dublincore.net/linked-data-learning-resources/

What resources do you use to learn & teach Linked Data?