Semantic Web Cluster and Energy and Climate Cluster

ESIP Winter ECC 2-3:30pm, Jan 5, 2012

Peter Fox (RPI) pfox@cs.rpi.eduTetherless World Constellation

Basci unit of exchange – the triple - example (linked data)

Heath (2009) [annotated]

Subject-Predicate-Object

Subj Obj

SubjObj

Pred

Pred

Note: namespaces, e.g. ‘rc’, ‘foaf’, ‘dbpedia’, etc. and types, e.g.objects, data, functions, …Best practice: put semantics between/ in your interfaces

Pred

3

Semantic Web Layers

http://www.w3.org/2003/Talks/1023-iswc-tbl/slide26-0.html, http://flickr.com/photos/pshab/291147522/

Working with knowledge

Expressivity

Maintainability/ Extensibility

Implementability

Working with knowledge

Query

Rule execution

Inference

Or it may be this …

Query

Rule execution

Inference

Expressivity/ Implementation

Declarative Procedural

Linked open dataURI/http/RDF *

Ontology encoded

Ontology SpectrumAn ontology specifies a rich description of the• Terminology, concepts, nomenclature• Properties explicitly defining concepts• Relations among concepts (hierarchical and lattice)• Rules distinguishing concepts, refining definitions and relations

(constraints, restrictions, regular expressions)

relevant to a particular domain or area of interest.

www.ksl.stanford.edu/people/dlm/papers/ontologies-come-of-age-abstract.html slide from Kendall/McGuinness SemTech Tutorial

Semantic Web Standards*

• Schema - RDFS (Resource Description Framework Schema, 2004)

• Ontology - OWL 1.0 (Web Ontology Language, 2004)• Query - SPARQL 1.0 (SPARQL Protocol and RDF

Query Language, 2008)• OWL 2.0 (2009)• Taxonomy - SKOS (Simple Knowledge Organization

System, 2009)• Rules - RIF (Rule Interchange Framework, 2010)• SPARQL 1.1 (2012?)• NB. No service standards! But, many in use…

10See http://www.w3.org/TR/owl-features/ section 2 for features

and relation to RDF or OWL species

Query - SPARQL

• SPARQL has 4 result forms:– SELECT – Return a table of results.– CONSTRUCT – Return an RDF graph, based on a

template in the query.– DESCRIBE – Return an RDF graph, based on

what the query processor is configured to return.– ASK – Ask a boolean query.

• The SELECT form directly returns a table• DESCRIBE and CONSTRUCT use the

outcome of matching to build RDF graphs.

11http://www.dajobe.org/2005/04-sparql/SPARQLreference-1.8-us.pdf

SPARQL Solution Modifiers

• Pattern matching produces a set of solutions. This set can be modified in various ways:– Projection - keep only selected variables– OFFSET/LIMIT - chop the number solutions (best

used with ORDER BY)– ORDER BY - sorted results– DISTINCT - yield only one row for one

combination of variables and values.

• The solution modifiers OFFSET/LIMIT and ORDER BY always apply to all result forms.

12

13

Rule Interchange Format (RIF)

• Interlingua (similar to KIF)

• http://www.w3.org/2005/rules/wiki/RIF_Working_Group

• Tools starting (just) to emerge

• http://www.w3.org/2005/rules/wiki/RIF_FAQ

• Reality: SWRL, Jena, Jess, OWL 2-RL

How we do things…

• Semantics require domain expertise,

• And a (or many) use case(s),

• And a methodology to proceed with knowledge extraction

• In case you have not visited our page: http://wiki.esipfed.org/index.php/Semantic_Web (it’s messy)

E.g. RPI/TWC Methodology …

• Use cases• Stakeholders• Distributed

authority• Access control• Ontologies• Maintaining

Identity

16

Use Case example

• Plot the neutral temperature from the Millstone-Hill Fabry Perot, operating in the non-vertical mode during January 2000 as a time series.

• Plot the neutral temperature from the Millstone-Hill Fabry Perot, operating in the non-vertical mode during January 2000 as a time series.

• Objects: – Neutral temperature is a (temperature is a) parameter– Millstone Hill is a (ground-based observatory is a) observatory– Fabry-Perot is a interferometer is a optical instrument is a

instrument– Non-vertical mode is a instrument operating mode– January 2000 is a date-time range– Time is a independent variable/ coordinate– Time series is a data plot is a data product

17

Elements of KR in Semantic Web

• Declarative Knowledge• Statements as triples: {subject-predicate-object}

interferometer is-a optical instrument

Fabry-Perot is-a interferometer

Optical instrument has focal length

Optical instrument is-a instrument

Instrument has instrument operating mode

Instrument has measured parameter

Instrument operating mode has measured parameter

NeutralTemperature is-a temperature

Temperature is-a parameter

• A query: select all optical instruments which have operating mode vertical

• An inference: infer operating modes for a Fabry-Perot Interferometer which measures neutral temperature

Information Modeling

• Conceptual

• Logical

• Physical

18

Who we do this with

• ESIP as a whole – ESIP network, FUNding Friday project, IT&I committee

• Internally

• IQ cluster

• PS cluster

• D cluster

• Past: Water Cluster, AQ Cluster

What is produced?

• Tutorials (both lecture style and hands-on), guides, etc.

• Ontologies (across the spectrum) with community governance

• [Some] Technical infrastructure – test bed(s), e.g. triple store, SPARQL endpoint, …

• Applications

• Demonstrations

Data type and services

Data Quality Ontology Development (Quality flag)

Working together with Chris Lynnes’s DQSS project, started from the pixel-level quality view.

Data Quality Ontology Development (Bias)

http://cmapspublic3.ihmc.us:80/servlet/SBReadResourceServlet?rid=1286316097170_183793435_22228&partName=htmltext

Modeling quality (Uncertainty)

Link to other cmap presentations of quality ontology:

http://cmapspublic3.ihmc.us:80/servlet/SBReadResourceServlet?rid=1299017667444_1897825847_19570&partName=htmltext

AeroStat Ontology

25

Opportunities

• I’ll mention just a few (so remember)– Tutorials (both lecture style and hands-on),

guides, etc.– Ontologies (across the spectrum) with

community governance– [Some] Technical infrastructure – test bed(s),

e.g. triple store, SPARQL endpoint, …– Applications– Demonstrations– Cool people ;-)

SWEET (2.3)

• http://sweet.jpl.nasa.gov/ • Mappings to CF

http://sweet.jpl.nasa.gov/sweetCF.xls

• Governed via Cluster, http://wiki.esipfed.org/index.php/SWEET_Governance

Frameworks - DPSIR

Semantics of DPSIR?

CMIP5 catalog explorer

• … with Earth System Grid Federation– Stage 1 – Catalog as linked data

• Visual exploration of a large graph (cf. Wed. poster)

– Stage 2 – data as linked data• For knowledge discovery…

Related

• CSML – Climate Science Markup Language - http://csml.badc.rl.ac.uk/

• MOLES - Metadata Objects for Linking Environmental Sciences - http://proj.badc.rl.ac.uk/moles/wiki

Rules of Engagement

• Semantics require domain expertise,

• And a (or many) use case(s),

Contact

• pfox@cs.rpi.edu

• http://wiki.esipfed.org/index.php/Semantic_Web

• 4th Tuesday telecon 1500ET

• http://rtpnet.org/mailman/listinfo/esip-semanticweb

• http://rtpnet.org/pipermail/esip-semanticweb/ (archives)

Reference material

Data-Information-Knowledge Ecosystem

35

Data Information Knowledge

Producers Consumers

Context

PresentationOrganization

IntegrationConversation

CreationGathering

Experience

36

Producers Consumers

Quality Control

Fitness for Purpose Fitness for Use

Quality Assessment

Trustee Trustor

Quality & Bias assessment using FreeMind

from the Aerosol Parameter Ontology

FreeMind allows capturing various relations between various aspects of aerosol measurements, algorithms, conditions, validation, etc. The “traditional” worksheets do not support complex multi-dimensional nature of the task

RDFS

• Note: XMLS not an ontology language– Changes format of DTDs (document schemas) to

be XML

– Adds an extensible type hierarchy• Integers, Strings, etc.

• Can define sub-types, e.g., positive integers

• RDFS is recognisable as an ontology language– Classes and properties

– Sub/super-classes (and properties)

– Range and domain (of properties)38

However

• RDFS too weak to describe resources in sufficient detail– No localized range and domain constraints

• Can’t say that the range of hasChild is person when applied to persons and elephant when applied to elephants

– No existence/cardinality constraints• Can’t say that all instances of person have a mother that is also a

person, or that persons have exactly 2 parents

– No transitive, inverse or symmetrical properties• Can’t say that isPartOf is a transitive property, that hasPart is the

inverse of isPartOf or that touches is symmetrica

• Difficult to provide reasoning support– No “native” reasoners for non-standard semantics– May be possible to reason via First Order axiomatisation

39

The OWL language:

• Three species of OWL– OWL full is union of OWL syntax and RDF– OWL DL restricted to FOL fragment (¼ DAML+OIL)– OWL Lite is “easier to implement” subset of OWL DL

• Semantic layering– OWL DL ¼ OWL full within DL fragment– DL semantics officially definitive

• OWL DL based on SHIQ Description Logic– In fact it is equivalent to SHOIN(Dn) DL

• OWL DL Benefits from many years of DL research– Well defined semantics– Formal properties well understood (complexity, decidability)– Known reasoning algorithms– Implemented systems (highly optimized)

40

41

W3C OWL 2 Documents

• Document Overview - The place to start – light introduction to OWL 2 and its relationship to OWL

http://www.w3.org/TR/owl2-overview/

• New Features and Rationale - More details of the new features in OWL 2 along with their motivations

http://www.w3.org/TR/owl2-new-features/

• Primer - An introduction to OWL using a running example

http://www.w3.org/TR/owl2-primer/

• Quick Reference A brief synopsis of the features of OWL along with links into relevant documents (both to user and specification documents)

http://www.w3.org/TR/owl2-quick-reference/

Profiles

• OWL defines only one fragment (OWL Lite)• OWL 2 defines three different fragments with useful

computational properties– EL: polynomial time reasoning for schema and data - Useful

for ontologies with large conceptual part

– QL: fast (logspace) query answering using RDBMs via SQL - Useful for large datasets already stored in RDBs

– RL: fast (polynomial) query answering using rule-extended DBs - Useful for large datasets stored as RDF triples

SKOS properties

Simple Knowledge Organization System - W3C Recommendation Status on August 18, 2009 http://www.w3.org/2004/02/skos/

• skos:notee.g. ‘Anything goes.’

• skos:definitione.g. ‘A long curved fruit with a yellow skin and soft, sweet white flesh inside.’

• skos:examplee.g. ‘A bunch of bananas.’

• skos:scopeNotee.g. ‘Historically members of a sheriff's retinue armed with pikes who escorted judges at assizes.’

• skos:historyNotee.g. ‘Deleted 1986. See now Detention, Institutionalization (Persons), or Hospitalization.’

• skos:editorialNotee.g. ‘Confer with Mr. X. re deletion.’

• skos:changeNotee.g. ‘Promoted “love” to preferred label, demoted “affection” to alternative label, Joe Bloggs, 2005-

08-09.’ 43

SKOS Vocabulary Elements

• skos:mappingRelation

• skos:closeMatch

• skos:exactMatch

• skos:broadMatch

• skos:narrowMatch

• skos:relatedMatch

44

• skos:exactMatch is disjoint with each of the properties skos:broadMatch and skos:relatedMatch.

SKOS 2

• Is an OWL ontology (but OWL-Full) so use the subset that is OWL-DL (for reasoning support)

• See:http://www.w3.org/TR/skos-reference/

• http://swig.hpclab.ceid.upatras.gr/SKOS/Skos2Owl2 (for example)

46

Editors

• Protégé (http://protege.stanford.edu)

• SWOOP (http://mindswap.org/2004/SWOOP; see also http://swoop.sourgeforge.net )

• Altova SemanticWorks (http://www.altova.com/download/semanticworks/semantic_web_rdf_owl_editor.html)

• SWeDE (http://owl-eclipse.projects.semwebcentral.org/InstallSwede.html), goes with Eclipse

• NeON toolkit http://neon-toolkit.org/

• ThManager http://thmanager.sourceforge.net/

• TopBraid Composer and other commercial tools

47

Triple Stores

• Jena (http://jena.sourceforge.net/) and Jena/TBD• SeSAME/SAIL (http://www.openrdf.org/)• KOWARI (http://www.kowari.org/) ->• Mulgara (http://www.mulgara.org/)• Redland (http://librdf.org/index.html)• Oracle (!)• Virtuoso• Allegrograph• Many others (relational, object-relational)• Joseki, e.g. SPARQL end-point

48

Reasoners (aka Inference engines)

• Pellet **• Racer (and Racer Pro) **• SHER (IBM)

http://www.alphaworks.ibm.com/tech/sher • Medius KBS• FACT++• fuzzyDL• KAON2• MSPASS• QuOnto• Jess (for Rules)• …

49

Services, …

• Now 4 submissions to W3C– OWL-S - http://www.w3.org/Submission/OWL-S

(updated journal publication - http://springerlink.com/content/wp8q2133g5725340/ )

– SWSO/F/L - Semantic Web Services Ontology/Framework/Language - http://www.w3.org/Submission/SWSF/

– WSMO/X/L - Web Services Modeling Ontology/Exection/Language - http://www.w3.org/Submission/WSMX/ www.wsmo.org, www.wsmx.org

– SAWSDL - (WSDL-S)

• SADI - http://sadiframework.org/content/