Motivating SKOS in Knowledge Graphs and introducing SKOS Shuttle, a web available SKOS service.

Transcription

1 Motivating SKOS in Knowledge Graphs and introducing SKOS Shuttle, a web available SKOS service. September 7 th, 2018 Expert Group Meeting: Software & Tools 14:00-17:00 at Scigility, Zürich fabio.ricci@semweb.ch Herzlich willkommen!

2 Content Introduction and Motivation Definition Knowledge-Graph Navigating the giant graph RDF (short) SKOS Who uses SKOS Thesauri? 5 Use SKOS cases Thesis SKOS semweb [Taxonomy governance & blockchain discussion] Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 2

3 Motivation Knowledge Graphs Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 3

4 Motivation Knowledge Graphs Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 4

5 Motivation Knowledge Graphs qdo the well known relational models inevitably lead to better results? qcan schema modifications be easily integrated into running systems? qdoes the relational technology easily support interrelation with other external sources? Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 5

6 Motivation Knowledge Graphs qthe value of data is directly proportional to its interrelation with other data... In the web as well as in in the enterprise. qpartially formalized, strongly interrelated data face well formalized but isolated data. Source /1/ Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 6

7 Motivation Knowledge Graphs q Knowledge Graphs depict multi-level structures predestined to express and link meaningful data as entities. q The more industry groups will build (and publish) their Knowledge Graphs, the higher the granularity of the resulting main (giant) Knowledge Graph and the efficiency of their interrelation. Source /1/ Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 7

8 Motivation Knowledge Graphs What is a graph Motivating SKOS in Knowledge Graphs September 7th, 2018 Slide 8

9 Motivation Knowledge Graphs What is a graph Motivating SKOS in Knowledge Graphs 2018 September 7th, 2018 Slide 9

10 Motivation Knowledge Graphs What is a graph In mathematics, and more specifically in graph theory, a graph is a structure amounting to a set of objects in which some pairs of the objects are in some sense "related". The objects correspond to mathematical abstractions called vertices (also called nodes or points) and each of the related pairs of vertices is called an edge (also called an arc orline) Wikipedia. Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 10

11 Knowledge Graphs (explicit) Knowledge (Human) Knowledge is a familiarity, awareness, or understanding of someone or something, such as facts, information, descriptions, or skills, acquired through experience or education by perceiving, discovering, or learning. (Human) Knowledge can refer to a theoretical or practical understanding of a subject. It can be implicit (as with practical skill or expertise) or explicit (as with the theoretical understanding of a subject); it can be more or less formal or systematic. (Wikipedia) Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 11

12 Knowledge Graphs Knowledge Graph vs. Linked Data Linked-Data? In computing, linked data is a method of publishing structured data so that it can be interlinked and become more useful through semantic queries (e.g. SPARQL). It builds upon standard Web technologies such as HTTP, RDF and URIs, but rather than using them to serve web pages for human readers, it extends them to share information in a way that can be read automatically by computers. (Wikipedia) Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 12

13 Knowledge Graphs Quality in Knowledge Graphs? A high quality Knowledge Graph is built using controlled vocabularies to define its components (entities). Controlled vocabulary: artifact (structured document) formally and uniquely defining entities, meaning and relationships among entities. Ontology: most complete formalizing document where entities are named, formally defined and interrelated. (e.g. OBO, OWL). Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 13

14 Knowledge Graphs Controlled vocabularies Controlled vocabularies provide a way to organize knowledge for subsequent retrieval. They are used in subject indexing schemes, subject headings, thesauri, taxonomies and other forms of knowledge organization systems (e.g. SKOS). Controlled vocabulary schemes mandate the use of predefined, authorized terms that have been preselected by the designers of the schemes, in contrast to natural language vocabularies, which have no such restriction. (Wikipedia) Thesauri are controlled vocabularies, where entities are interrelated in a standard way with each other defining a heterachy of concepts (ideally as a DAG direct acyclic graphs). Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 14

15 Knowledge Graphs Examples of Knowledge Graphs (1/6) Google s Graph Enhances search with relevant (associated) additional (relevant?) results. Queriable via Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 15

16 Knowledge Graphs Examples of Knowledge Graphs (2/6) DBPedia Publishes Wikipedia s Definitions and Interrelations als Linked Data Queriable via Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 16

17 Knowledge Graphs Examples of Knowledge Graphs (3/6) Wikidata Publishes common accessible collections of entities as Linked Data Queriable via Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 17

18 Knowledge Graphs Examples of Knowledge Graphs (4/6) Europeana Interrelated collections of art, fashion, music, photography and history as Linked-Data Queriable via Motivating SKOS in Knowledge Graphs September 7th, 2018 Slide 18

19 Knowledge Graphs Examples of Knowledge Graphs (5/6) UMLS many controlled vocabularies in the biomedical sciences (created 1986). 1mio Concepts, 5 mio Names Queriable via Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 19

20 Knowledge Graphs Examples of Knowledge Graphs (6/6) Lindas (Swiss Federal Archives) Interrelated collections of egov Data as Linked-Data Queriable via Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 20

21 Knowledge Graphs Discussion: What would be a Knowledge Graph all about in your enterprise? When data are not interrelated ist again a Knowledge Graph? Is this the situation we (still) (partially) have today? Where are the edges in your case? Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 21

22 Knowledge Graphs Building Knowledge Graphs How can a Knowledge Graph be built today? Using RDF Edges (Statements) RDF : Ressource Rescription Framework One RDF-Statement is an SPO triple Everything broken down to binary relationships at several levels. Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 22

23 Navigating Knowledge Graphs Navigating the giant graph How to (efficiently) query datasets with links and dozens of billions of unique triples? Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 23

24 Navigating Knowledge Graphs Navigating the giant graph Example of federated SPARQL Query fired from : PREFIX bif: <bif:> PREFIX edm: < PREFIX ore: < PREFIX dc: < PREFIX dct: < PREFIX dbc: < PREFIX foaf:< Works of known composers of Italian baroque (Limited to 5 composers) SELECT?surname?date?creator?title { SERVICE < {?cho ore:proxyin?proxy; dc:title?title; dc:date?date; dc:creator?creator. FILTER(bif:contains(?creator, str(?surname))). } SERVICE < { SELECT?surname {?musiker dct:subject dbc:italian_baroque ; foaf:surname?surname. } LIMIT 5 } } Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 24

25 Navigating Knowledge Graphs Navigating the giant graph 1. Download, index and query datasets from the LOD Cloud locally, (impractical for simple query resolution). 2. Run a federated query against all known sources, which is as good as the query endpoints that it relies on. 3. Browse online sources in a follow-your-nose way 4. Use LOD-a-lot /2/ does not prevent you from knowing the knowledge schema. 5. Each graph is shaped (modelled) differently Will you (effitiently) get you the information you are searching for? Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 25

26 Knowledge Graphs RDF-Entity Kant An entity in RDF is a set of RDF-Statements dbr:immanuel_kant rdf:type yago:socialscientist dbr:immanuel_kant a yago:wikicatgermanagnostics dbr:immanuel_kant a yago:wikicatphilosophersofart dbr:immanuel_kant rdfs:label "Immanuel Kant"@de dbr:immanuel_kant rdfs:label " تناك dbr:immanuel_kant rdfs:label "इम न य एल क ण ट"@sa dbr:immanuel_kant owl:sameas dbpedia-wikidata:q9312 See e.g. to check out all relationships, resp. attributes of the entity Immanuel Kant Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 26

27 An entity in RDF is a set of RDF-Statements dbr:immanuel_kant rdf:type yago:socialscientist dbr:immanuel_kant a yago:wikicatgermanagnostics dbr:immanuel_kant a yago:wikicatphilosophersofart prefixes = schemas (namespaces defined by vocabularies) dbr:immanuel_kant rdfs:label "Immanuel Kant"@de dbr:immanuel_kant rdfs:label "Immanuel Kant"@en dbr:immanuel_kant owl:sameas dbpedia-wikidata:q Knowledge Graphs RDF-Entity dbp: < < Siehe rdfs: < alle Relationen, bzw. Attributen zur Immanuel owl: < Kant einzusehen. dbpedia-wikidata: yago: < Namespaces (Controlled Vocabolary or Ontology) Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 27

28 Navigating Knowledge Graphs Navigating the giant graph An well organized Graph can be traversed / queried quicker SKOS (Simple Knowledge Organisation System) is a W3C recommendation since It is an OWL ontology (hence semantically and formerly defined) Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 28

29 Navigating Knowledge Graphs SKOS Model (partial) Documentation note changenote definition editorialnote example historynote scopenote Labeling preflabel altlabel hiddenlabel Notation ConceptScheme notation Example Creme X0815 broader Beauty Creme X (alternativelabel) Beauty Products member inscheme hastopconcept closematch Creme Y1345 Collection member Concept semanticrelation broadmatch Liquid Products OrderedCollection memberlist Semantic broader narrower Mapping broadmatch narrowmatch rdf:list related broadertransitive narrowertransitive relatedmatch closematch exactmatch Source: Sean Bechhofer SKOS: Past, Present and Future. ESWC Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 29

30 Navigating Knowledge Graphs SKOS Example for Bird SKOS 1x1 Each concept: One preferred label Many alternative labels One or more definitions One or more scope notes Interrelated concepts broader / narrower / related Concepts interrelation build a polyhyerarchy Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 30

31 Navigating Knowledge Graphs Who is using SKOS (Thesauri) since years? qdaimlerchrysler (automotive, EU) qfluor (engineering, GLOBAL) qroche (health, GLOBAL) qbiotech Quality (biotech, Belgium) qswiss Confederation (admin, Switzerland) qiaea (atomic, Austria) qctcn (climate, GLOBAL) qhealthdirect (health, AUSTRALIA) q Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 31

32 Navigating Knowledge Graphs Some major public RDF SKOS Thesauri qagrovoc: Multilingual agricultural thesaurus qearth: an Environmental Application Reference qeurovoc: The EU s multilingual thesaurus qgemet: GEneral Multilingual Environmental Thesaurus qgetty AAT: Art & Architecture Thesaurus qmesh: Medical Subject Headings qreegle: Renewable Energy and Energy Efficiency Partnership qstw: Thesaurus for Economics qjurivoc: Threelingual thesaurus of the Swiss Federal Tribunal qthe Basel Register of Thesauri, Ontologies & Classifications (BARTOC) lists more than Vocabularies. Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 32

33 Navigating Knowledge Graphs BIO-Zen 5 use cases BIRNLex Subject Headings Health Direct Europeana Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 33

34 Navigating Knowledge Graphs Use case 1 BIO-Zen allows the description of biological systems and the representation of scientific discourse on the web in a highly distributed manner. It is intended to be used by researchers and developers in the life sciences. SKOS is used in bio-zen for the representation of many existing life sciences vocabularies, taxonomies and ontologies coming from the "Open Biomedical Ontologies" (OBO) collection. The size of all converted taxonomies taken together is on the order of millions of concepts. Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 34

35 Navigating Knowledge Graphs Use case 2 BIRNLex: a lexicon for neurosciences Integrated ontology and lexicon used for various purposes some enduser/interactive, others back-end/infrastructure within the BIRN Project to support semantically-formal data annotation, semantic data integration, and semantically-driven, federated query resolution. Uses both the Dublin Core metadata elements and SKOS where ever possible Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 35

36 Navigating Knowledge Graphs Use case 3 Subject Headings (libraries) services lcsh.info Web services using SKOS to allow for simple browsing of the subject headings. Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 36

37 Navigating Knowledge Graphs Use case 4 healthdirect Australia Advising Portal The platform bundles content from over 140 specialized information providers. Users benefit from valuable and quality-assured medical information, which is made accessible through smart semantic search applications. Semantic capabilities such as faceted search and auto completion enrich the portal with intelligence that enable non-experts to do specialized research. Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 37

38 Navigating Knowledge Graphs Use case 5 EUROPEANA More than 20 million entities linked in an own dataset in the EDM (Europeana Data Model) using Dublin Core, OAI-ORE, SKOS and CIDOC-CRM models Providing access to cultural heritage domains such as art, music and fashion. Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 38

39 Navigating Knowledge Graphs Navigating the giant graph (thesis) Thesis: Having SKOS* organizing the giant graph would standardize access Quality Control E.g. via Graph Validators SKOS*: some suitable SKOS extension Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 39

40 SKOS as a Standard Introduction to SKOS Shuttle (3+4 slides) q Thesaurus managers enable practitioners to develop thesauri with limited training. q Domain experts can model their fields of expertise without IT support. q SKOS Shuttle thesaurus management software aas is compliant with SKOS and ensures interoperability of thesauri with other taxonomies, knowledge graphs and APIs. Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 40

41 SKOS Shuttle Scenarios q Taxonomy governance q Creation and / or Maintenance of big Thesauri q Search support via REST API q Blockchain secured thesauri q Suitable for every domain q q q q q q History Art Music Manufacturing Physics Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 41

42 SKOS Shuttle web thesauri (2) q Custom relations q Custom attributes SKOS++ q Units of measure q OWL extension - SKOSOWL (to be further developped) q Works with 7 major RDF stores: AllegroGraph, Blazegraph, GraphDB, Jena-Fuseki, MarkLogic, Stardog, Virtuoso Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 42

43 SKOS Shuttle Information Governance Deliver RDF changes to connected thesauri (prod environments) via RDF Push notifications 18. Mai 2017 Seite 43

44 SKOS Shuttle Archiving to Blockchain Securely archive RDF chunks (or whole SKOS Thesauri) To a private ethereumj instance operated at Semweb RDF code is compressed and uploaded / downloaded to / from the blockchain Next step and discussion: Blockchain is safe and (normally highly) redundant. Should it be also hosting a SPARQL engine? Who will start doing it? 18. Mai 2017 Seite 44

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50 Thank you! Questions? Bibliography /1/: Pan J.Z., 2017 Exploiting Linked Data and Knowledge Graphs in Large Organisations /2/: Motivating SKOS in Knowledge Graphs September 7 th, 2018 Slide 50