1 / 56

Peter Fox Tetherless World Constellation RPI Australia Ontology Workshop 2009

Balancing Expressivity and Implementability in OWL Ontologies for Semantic Data Frameworks: The Journey from 2004 to 2009 and Beyond. Peter Fox Tetherless World Constellation RPI Australia Ontology Workshop 2009. Outline. The origins of this effort Why a framework and not a system?

vangie
Download Presentation

Peter Fox Tetherless World Constellation RPI Australia Ontology Workshop 2009

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Balancing Expressivity and Implementability in OWL Ontologies forSemantic Data Frameworks: The Journey from 2004 to 2009 and Beyond Peter Fox Tetherless World Constellation RPI Australia Ontology Workshop 2009

  2. Outline • The origins of this effort • Why a framework and not a system? • Semantics in 2004 • The design and development methods • Ontologies and the software and production! • Semantics between 2004 and 2009 • Discussion of the expressivity and implementabilitybalance and one more … • Since it is almost 2010 … what we are up to Tetherless World Constellation

  3. Background Scientists should be able to access a global, distributed knowledge base of scientific data that: • appears to be integrated • appears to be locally available But… data is obtained by multiple instruments, using various protocols, in differing vocabularies, using (sometimes unstated) assumptions, with inconsistent (or non-existent) meta-data. It may be inconsistent, incomplete, evolving, and distributed And… there exist(ed) significant levels of semantic heterogeneity, large-scale data, complex data types, legacy systems, inflexible and unsustainable implementation technology…

  4. Origins • In 2000-2001 the need for capturing and preserving knowledge in science data became very clear but the barriers were high • In 2004 we started a virtual observatory project based on semantic technologies • Use case driven – in solar and solar-terrestrial physics with an emphasis on instrument-based measurements and real data pipelines; we needed implementations • We knew we also needed integration and provenance (but that came later) • We aimed to push semantics into our systems to build new ‘prototypes’ but we ‘failed’ ;-) Tetherless World Constellation

  5. In 2004 • 2004 – OWL was a W3 recommendation!! • Protégé 2.x and the Protégé-Java-OWL API • SWOOP was a viable editor • Jena and the Jena API were in good shape • Pellet worked • SPARQL was still a twinkle in the RDF working group’s eye • Semantics were still the realm of computer scientists – luckily we had one of the best Tetherless World Constellation

  6. Frameworks vs. Systems • Prior to 2005, we built systems • Rough definitions • Systems have very well-define entry and exit points. A user tends to know when they are using one. Options for extensions are limited and usually require engineering • Frameworks have many entry and use points. A user often does not know when they are using one. Extension points are part of the design • You don’t have to agree, this was our view Tetherless World Constellation

  7. Ontology Spectrum Thesauri “narrower term” relation Selected Logical Constraints (disjointness, inverse, …) Frames (properties) Formal is-a Catalog/ ID Informal is-a Formal instance General Logical constraints Terms/ glossary Value Restrs. Originally from AAAI 1999- Ontologies Panel by Gruninger, Lehmann, McGuinness, Uschold, Welty; – updated by McGuinness. Description in: www.ksl.stanford.edu/people/dlm/papers/ontologies-come-of-age-abstract.html

  8. Design and Development • We made a conscious decision only to develop ontologies that were required to answer specific use cases • We made a conscious effort to use whatever ontologies were available** • We were pretty sure that rules would be needed • We ignored query Tetherless World Constellation

  9. Content: Coupling Energetics and Dynamics of Atmospheric Regions Community data archive for observations and models of Earth's upper atmosphere and geophysical indices and parameters needed to interpret them. Includes browsing capabilities by periods, instruments, models, …

  10. Content: Mauna Loa Solar Observatory Near real-time data from Hawaii from a variety of solar instruments. Source for space weather, solar variability, and basic solar physics Other content used too – CISM – Center for Integrated Space Weather Modeling

  11. Virtual Observatories Make data and tools quickly and easily accessible to a wide audience. Operationally, virtual observatories need to find the right balance of data/model holdings, portals and client software that researchers can use without effort or interference as if all the materials were available on his/her local computer using the user’s preferred language: i.e. appear to be local and integrated Likely to provide controlled vocabularies that may be used for interoperation in appropriate domains along with database interfaces for access and storage and “smart” tools for evolution and maintenance.

  12. ? Early days of VxOs VO2 VO3 VO1 DBn DB2 DB3 … … … … DB1

  13. Limited interoperability Lightweight semantics Limited meaning, hard coded Limited extensibility Under review The Astronomy approach; data-types as a service • VOTable • Simple Image Access Protocol • Simple Spectrum Access Protocol • Simple Time Access Protocol VO App2 VO App3 VO App1 OGC: {WFS, WCS, WMS} and SWE {SOS, SPS, SAS} use the same approach VO layer DBn DB2 DB3 … … … … DB1

  14. Science and technical use cases Find data which represents the state of the neutral atmosphere anywhere above 100km and toward the arctic circle (above 45N) at any time of high geomagnetic activity. • Extract information from the use-case - encode knowledge • Translate this into a complete query for data - inference and integration of data from instruments, indices and models Provide semantically-enabled, smart data query services via a SOAP web for the Virtual Ionosphere-Thermosphere-Mesosphere Observatory that retrieve data, filtered by constraints on Instrument, Date-Time, and Parameter in any order and with constraints included in any combination.

  15. 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 temperaturefrom the Millstone-HillFabry Perot, operatingin thenon-vertical modeduringJanuary 2000as atime 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

  16. Knowledge representation • Statements as triples: {subject-predicate-object} interferometer is-a optical instrument Fabry-Perotis-a interferometer Optical instrumenthas focal length Optical instrument is-ainstrument Instrumenthas instrument operating mode Instrument has measured parameter Instrument operating modehas measured parameter NeutralTemperatureis-atemperature Temperature is-aparameter • 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

  17. Added value Education, clearinghouses, other services, disciplines, etc. Semantic interoperability Added value Added value Semantic query, hypothesis and inference Semantic mediation layer - mid-upper-level Added value VO API Web Serv. VO Portal Query, access and use of data Mediation Layer • Ontology - capturing concepts of Parameters, Instruments, Date/Time, Data Product (and associated classes, properties) and Service Classes • Maps queries to underlying data • Generates access requests for metadata, data • Allows queries, reasoning, analysis, new hypothesis generation, testing, explanation, etc. Semantic mediation layer - VSTO - low level Metadata, schema, data DBn DB2 DB3 … … … … DB1 Fox - APAC 2007, Driving e-research: Grids and Semantics

  18. Semantic filtering by domain or instrument hierarchy Partial exposure of Instrument class hierarchy - users seem to LIKE THIS Fox - APAC 2007, Driving e-research: Grids and Semantics

  19. Inferred plot type and return required axes data

  20. Semantic Web Services

  21. Semantic Web Services OWL document returned using VSTO ontology - can be used both syntactically or semantically Fox - APAC 2007, Driving e-research: Grids and Semantics

  22. Semantic Web Benefits • Unified/ abstracted query workflow: Parameters, Instruments, Date-Time • Decreased input requirements for query: in one case reducing the number of selections from eight to three • Generates only syntactically correct queries: which was not always insurable in previous implementations without semantics • Semantic query support: by using background ontologies and a reasoner, our application has the opportunity to only expose coherent query (portal and services) • Semantic integration: in the past users had to remember (and maintain codes) to account for numerous different ways to combine and plot the data whereas now semantic mediation provides the level of sensible data integration required,and exposed as smart web services • understanding of coordinate systems, relationships, data synthesis, transformations. • returns independent variables and related parameters • A broader range of potential users (PhD scientists, students, professional research associates and those from outside the fields)

  23. http://escience.rpi.edu/schemas/vsto_all.owl

  24. Semantic Web Methodology and Technology Development Process Adopt Technology Approach Leverage Technology Infrastructure Science/Expert Review & Iteration Rapid Prototype Open World: Evolve, Iterate, Redesign, Redeploy Use Tools Evaluation Analysis Use Case Develop model/ ontology Small Team, mixed skills

  25. Developing ontologies • Use cases and small team (7-8; 2-3 domain/ data experts, 2 knowledge experts, 1 software engineer, 1 facilitator, 1 scribe) • Identify classes and minimal properties (leverage controlled vocab.) • Start with narrower terms, generalize when needed or possible • Adopt a suitable conceptual decomposition (e.g. SWEET) • Import modules when concepts are orthogonal • Add service classes and properties where needed • Review, vet, publish • Only code them (in RDF or OWL) when needed (CMAP, …) • Ontologies: small and modular

  26. Species validation Tetherless World Constellation

  27. Expressivity VSTO 1.0 Tetherless World Constellation

  28. Expressivity VSTO dev. version Tetherless World Constellation

  29. Yikes Tetherless World Constellation

  30. Ontologies and the software • Protégé 2.x and then 3.x built from our ontology on the web • Java class generation • Eclipse as a development environment • Leveraged a portal code base (from the Earth System Grid project) Tetherless World Constellation

  31. 2

  32. Implementation choices • Our big challenge was time – in use cases and in the representation • Depending on the level of granularity there were > 200,000 day-time records, and > 70,000,000 sub-day time intervals – no triple store could handle this** • We descoped our effort to delay use cases such as: find all neutral temperature data around the summer solstice for the last decade • We chose a minimal time encoding in the ontology and delegated that to a relational DB • Reasoning in finite time does not mean 3-4 secs! Tetherless World Constellation

  33. Web Service VSTO - semantics and ontologies in an operational environment:www.vsto.org Fox - APAC 2007, Driving e-research: Grids and Semantics

  34. Implications and OWL 1.0 • Lack of numeric support meant that the the rules and procedural logic were implemented in java, i.e. in the code • On several occasions the tools (not to be named) pushed us into OWL-Full, introduced inconsistencies, etc. • Finally, they stabilized, and in 2005 (and again in 2006 and twice in 2007) we had stable releases Tetherless World Constellation

  35. Evaluation • Highlights: • Less clicks to data • Auto identification and retrieval of independent variables & plotting support • Faster • Support for finding instruments (without specifying the id includes finding data from instruments that the user did not know to ask for) • Questions (potentially with 35 responses) • What do you like about the new searching interface? (9) • Are you finding the data you need? (35: Yes=34, No=1) • What is the single biggest difference? (8) • How do you like to search for data? Browse, type a query, visual? (10, Browse=7, Type=0, Visual=3) • What other concepts are you interested in using for search, e.g. time of high solar activity, campaign, feature, phenomenon, others? (5, all of these) • Does the interface and services deliver the functionality, speed, flexibility you require? (30, Yes=30, No=0) • How often do you use the interface in your normal work? (19, Daily=13, Monthly=4, Longer=2) • Are there places where the interface/ services fail to perform as desired? (5, Yes=1, No=4) Tetherless World Constellation

  36. Iteration • We need the ability to evolve the ontology and not break the framework • As we broaden re-use of these ontologies and creation of new ones • We needed visual tools like CMAP Ontology Editor • We needed the visual tools to work with the editing/ plugintools – they do not • We needed to use natural language forms but this ended up being sparse but that need will increase • Need tools aimed at software engineers and domain scientists: three-pronged approach and interoperable: • OWL in editors (e.g. Protégé, SWOOP, etc.) • Visual (e.g. CMAP/COE) • Natural Language (e.g. Rabbit, CL, Peng) Tetherless World Constellation

  37. Maintenance • Support for collaborative feedback, evolution • Change management • Support for ‘comments’ and ‘annotations’, i.e. self-documentation • Package management: creation, dependency, consistency checking Tetherless World Constellation

  38. Semantics between 2004 and 2009 • Ontologies were needed for data integration • and provenance • and mediation for data mining • Protégé 3.x and then 4.0 came out • SWOOP development was interrupted • Cmap added OWL predicate support* • SPARQL became a recommendation • Triple stores exploded in use and capability • Linked Open Data started to take off • Pellet 2.0 came out • We invaded OWLED 2006, 2007, and 2009 Tetherless World Constellation

  39. Semantic Web Layers

  40. Other projects – ontologies for faceted search Tetherless World Constellation

  41. For data integration Tetherless World Constellation

  42. Ontology packaging Tetherless World Constellation

  43. Provenance Tetherless World Constellation

  44. Discussion of E versus I • We had to expand the balance to now include maintainability (/ evolvability) • E-M-I briefly • E.g. modularization has become essential to facilitate ontology packaging -> need to take advantage of OWL 2 • Separation of class and instances • Makes visual development possible • Also facilitates SPARQL end-point approaches • As tools and applications improve we reconsider our past choices • Adding time** back into VSTO and moving to OWL 2 Tetherless World Constellation

  45. 2010 • Recently funded to take our developments into a configurable SDF, thus we will push ontology languages and tools on new ways: • OWL 2 – RL in particular • Annotations • Property chaining • SPARQL (yawn) • RIF – probably not for a while • However, the tools still lag behind – especially for visual and natural language development Tetherless World Constellation

  46. Modularization • One of the primary goals of VSTO 2.0 is to modularize the VSTO ontology, e.g., an instrument module does not require any other classes besides the instrument and maybe an instrument operating mode to substantiate what an instrument is. • The problem with modularization, however, is that although a subset may substantiate a concept, that concept, especially in VSTO, has a number of relations linking it with other concepts within the ontology, for instance the instrument module may measure a number of parameters in the parameter module, or have a time coverage that would be defined in the time module. • Each observatory that the VSTO integrates data for will import only the modules that are appropriate for the observatory's domain. • There are also some modules that will always be required, regardless of the domain, like the instrument, parameter, and time modules. Each observatory ontology has its own way of linking these modular concepts, which will be called link properties. • This presents a problem, as the VSTO portal may not know which link property to use to associate an instrument with a set of parameters or a time coverage, as it becomes the responsibility of the ontology for the respective observatory to define the link properties. Tetherless World Constellation

  47. ‘Interfaces’ or ‘Extensions’ • This is where the VSTO interface ontology comes in. It doesn't have to be called the VSTO interface, it could be VSTO link properties, or anything for that matter. • The purpose of this ontology is to define a few link properties that will be required for navigation to data in the VSTO portal. For instance, the guided workflows as they work now, would require a number of link properties. E.g. the Start by Instrument Workflow, the VSTO interface would require an instrument and time coverage link property to get from step 1 to step 2 in the workflow. • In the case that an instrument of the CEDAR observatory is selected in step 1, this link property could be created in a rule-based logic as… • ( Instrument_1 hasInstrumentOperatingMode IOM_1 ^ IOM_1 hasDataset Dataset_1 ^ Dataset_1 hasTimeCoverage TimeInterval_1 ) => Instrument_1 hasTimeCoverageTimeInterval_1 • Of course, this would have to be done for all instrument operating modes and all datasets associated with those operating modes to determine the full time coverage of an instrument. Tetherless World Constellation

  48. OWL 2 considerations • What's good?: • new syntactic sugar to simplify ontology • ability to compare numerics • OWL 2 QL Synopsis: • focused on ontology interoperability with database systems where scalable reasoning and query answering over large numbers of instances is most important task • Why is it a good match?: • synopsis above, query answering over a large number of time instances will have to be performed • Why isn't it a good match?: • does not support enumerations, a feature required by some concepts in VSTO • does not support functional properties, a feature required by some properties in VSTO • does not support property inclusions involving property chains, a feature we hope to utilize to define rules for VSTO • does not support keys, a feature we hope to add when Protege 4.1 released (along with support for creation of keys) Tetherless World Constellation

More Related