StrategiesTaxonomy June 9, 2014Copyright 2014 Taxonomy Strategies. All rights reserved. The Search for Meaning and Semantics: Taxonomies Get It Done Joseph Busch – Why Semantics Matter

2 Taxonomy Strategies The business of organized information Agenda v Why semantics matter (… a quick review from 2001) v What is semantic search, SKOS and Linked Data? v Some semantic search examples?

3 Taxonomy Strategies The business of organized information Why Semantics Matter May 20, 2001

4 Taxonomy Strategies The business of organized information When you own a Rembrandt you can spell his name any way you want.

5 Taxonomy Strategies The business of organized information But when you want to find a Rembrandt … you better spell his name correctly.

6 Taxonomy Strategies The business of organized information Vocabulary resources can help find the right artist even if their name is typed incorrectly.

7 Taxonomy Strategies The business of organized information Users cannot type in the complex queries needed to find all the relevant items... But this can be done automatically.

8 Taxonomy Strategies The business of organized information Complex queries are even more important when you search the entire web.

9 Taxonomy Strategies The business of organized information So you find Rembrandt the Dutch guy...

10 Taxonomy Strategies The business of organized information … And not Rembrandt the toothpaste.

11 Taxonomy Strategies The business of organized information Getty Vocabularies Linked Data Services February 19, 2014

12 Taxonomy Strategies The business of organized information Agenda v Why semantics matter v What is semantic search, SKOS and Linked Data? v Some semantic search examples?

13 Taxonomy Strategies The business of organized information Search Failure v 19% Character errors. (Young, et al) v 40% Vocabulary errors. (Seaman. Norgard, et al) v 20% Index confusion. v 21% Successful (Nielsen) 40% 20% 19% 21%

14 Taxonomy Strategies The business of organized information

15 Taxonomy Strategies The business of organized information Semantic search solution v Semantic search improves search accuracy by inferring the contextual meaning of terms via:  Disambiguation  Part of speech (POS) analysis  Synonyms, variations and quasi-synonyms  Concept matching  Natural language query analysis  Key sentence detection v Generate more consistent content to search on. v Correct user errors. v Map the language of users to the language of the target content. v Augment search results with linked data.

16 Taxonomy Strategies The business of organized information What semantics do for search? FunctionDescription Related searchQuery corrections … did you mean? Concept searchQuery expansion with synonyms, abbreviations, acronyms, etc. … do you also want? Ontology-based searchQuery expansion with narrower or broader terms; scoping exhaustive search results Faceted searchDynamic filtering of search results; online shopping ClusteringDynamically bucketing search results into pre- defined categories Stored queriesRSS feeds, alerts, SDI (selective dissemination of information), etc. PersonalizationWeighting search results based on explicit profiles and implicit data (where you’ve been and what you’ve done)

17 Taxonomy Strategies The business of organized information What is SKOS? v Provides the basis for any user, tool, or program to identify, define and link concept vocabularies. RelationshipDefinition ConceptA unit of thought, an idea, meaning, or category of objects or events. A Concept is independent of the terms used to label it. Preferred LabelA preferred lexical label for the resource such as a term used in a digital asset management system. Alternate LabelAn alternative label for the resource such as a synonym or quasi- synonym. Broader Concept Hierarchical link between two Concepts where one Concept is more general than the other. Narrower Concept Hierarchical link between two Concepts where one Concept is more specific than the other. Related Concept Link between two Concepts where the two are inherently "related", but that one is not in any way more general than the other.

18 Taxonomy Strategies The business of organized information lc:sh Fringe parking Park and ride systems Park and ride CONCEPT trt:Brddf Park & ride Park-n- ride altLabel prefLabel altLabel P&R system altLabel broader Parking trt:Brdd prefLabel

19 Taxonomy Strategies The business of organized information Why SKOS? According to Alistair Miles* (SKOS co-author) v Ease of combination with other standards  Vocabularies are used in great variety of contexts. – E.g., databases, faceted navigation, website browsing, linked open data, spellcheckers, etc.  Vocabularies are re-used in combination with other vocabularies. – E.g., Library of Congress Subject Headings + Transportation Research Thesaurus; USPS states + USPS zip codes + US Congressional districts; etc.Library of Congress Subject HeadingsTransportation Research ThesaurusUSPS statesUS Congressional districts v Flexibility and extensibility to cope with variations in structure and style  Variations between types of vocabularies – E.g., list vs. classification scheme  Variations within types of vocabularies – E.g., Z monolingual controlled vocabularies and the Transportation Research ThesaurusZ Transportation Research Thesaurus * Head of Epidemiological Informatics at Oxford University Wellcome Trust Centre for Human Genetics (formerly OUP Senior Computing Officer)

20 Taxonomy Strategies The business of organized information Why SKOS? (2) v Publish managed vocabularies so they can readily be consumed by applications  Identify the concepts – What are the named entities?  Describe the relationships – Labels, definitions and other properties  Publish the data – Convert data structure to standard format – Put files on an http server (or load statements into an RDF server) v Ease of integration with external applications  Use web services to use or link to a published concept, or to one or more entire vocabularies. – E.g., Google maps API, NY Times article search API, Linked open data; etc.Google maps APINY Times article search APILinked open data v A W3C standard like HTML, CSS, XML and RDF, RDFS, and OWL.

21 Taxonomy Strategies The business of organized information Agenda v Why semantics matter v What is semantic search, SKOS and Linked Data? v Some semantic search examples?

22 Taxonomy Strategies The business of organized information Taxonomy browser

23 Taxonomy Strategies The business of organized information Taxonomy-powered search results

24 Taxonomy Strategies The business of organized information Audience Products Location Organization Content Type Product Line Application Technology Industry Solution Person Oracle.com top-level taxonomy Has a Is a

25 Taxonomy Strategies The business of organized information Oracle event finder Filter on Location and Language More filters based on this result Results shown on Google maps UI Subscribe to RSS feed based on the criteria set on this page

26 Taxonomy Strategies The business of organized information APS Taxonomy browserTaxonomy browser

27 Taxonomy Strategies The business of organized information Linked data example APS Taxonomy Broad Subject Areas Methods & Theories Phenomena Physical Systems APS Taxonomy Broad Subject Areas Methods & Theories Phenomena Physical Systems Astronomical systems Atomic-scale objects Beams Complex systems Dynamical systems Electric & magnetic fields Engineered materials Fundamental particles Gases delete Information systems Liquids delete Materials Nonlinear system Nuclei Plasma Quasiparticles Astronomical systems Atomic-scale objects Beams Complex systems Dynamical systems Electric & magnetic fields Engineered materials Fundamental particles Gases delete Information systems Liquids delete Materials Nonlinear system Nuclei Plasma Quasiparticles Materials by Composition Materials by Dimensionality Materials by Property Materials by Structure Materials by Composition Materials by Dimensionality Materials by Property Materials by Structure Elements by Group Group 1 Group 2 Group 3 Group 4 Group 5 Group 6 Group 7 Group 8 Group 9 Group 10 Group 11 Group 12 Group 13 Group 14 Group 15 Group 16 Group 17 Group 18 Elements by Group Group 1 Group 2 Group 3 Group 4 Group 5 Group 6 Group 7 Group 8 Group 9 Group 10 Group 11 Group 12 Group 13 Group 14 Group 15 Group 16 Group 17 Group 18 Elements of the periodic table, and common isotopes Cadmium Copernicium Mercury Zinc Cadmium Copernicium Mercury Zinc 194Hg 196Hg 198Hg 199Hg 200Hg 201Hg 202Hg 204Hg 194Hg 196Hg 198Hg 199Hg 200Hg 201Hg 202Hg 204Hg A faceted taxonomy of concepts in physics

28 Taxonomy Strategies The business of organized information Paper submission tagging (prototype)Paper submission tagging

29 Taxonomy Strategies The business of organized information QUESTIONS Joseph A Busch Mobile

30 Taxonomy Strategies The business of organized information Session description v Semantic search – a phrase that is increasingly used in the popular as well as the professional literature. What does it look like, and how will it work. Panelists will present their visions of semantic search. Program is designed to be interactive with audience participation – suggestions for functions and features they see in the future.  What is semantic search?  What are the components of semantic search?  How can it be used in libraries?