Top Banner
Ontology Best Practices: Experiences with SWEET Rob Raskin NASA/Jet Propulsion Laboratory Pasadena, CA
17

Ontology Best Practices: Experiences with SWEET

Dec 31, 2015

Download

Documents

portia-mcmahon

Ontology Best Practices: Experiences with SWEET. Rob Raskin NASA/Jet Propulsion Laboratory Pasadena, CA. Why an Upper-Level Ontology for Earth System Science? Why cooperate?. Many common concepts used across Earth Science disciplines (e,g, Temperature, Pressure) - PowerPoint PPT Presentation
Welcome message from author
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
Page 1: Ontology Best Practices:  Experiences with SWEET

Ontology Best Practices: Experiences with SWEET

Rob RaskinNASA/Jet Propulsion Laboratory

Pasadena, CA

Page 2: Ontology Best Practices:  Experiences with SWEET

Why an Upper-Level Ontology for Earth System Science?

Why cooperate?

Many common concepts used across Earth Science disciplines (e,g, Temperature, Pressure)

Provides common definitions for terms used in multiple disciplines or communities

Provides common language in support of community and multidisciplinary activities

Provides common “properties” (relations) for tool developers Reduced burden (and barrier to entry) on creators of

specialized domain ontologies Only need to create ontologies for incremental knowledge

Page 3: Ontology Best Practices:  Experiences with SWEET

Role of Upper Level Earth Science Ontology

Math Physics Chemistry

Space

TimeProperty

PlanetaryRealmProcess, Phenomena

SubstanceData

StratosphericChemistry

Biogeochemistry Specialized domains

import

import

Common Earth elements

General domains

Page 4: Ontology Best Practices:  Experiences with SWEET

Semantic Web for Earth and Environmental Terminology (SWEET)

Concept space written in OWL Initial focus to assist search for data resources

Funded by NASA Later focus to serve as community standard Enables scalable classification of Earth system science

concepts Populated initially with GCMD, CF concepts (decomposed)

Page 5: Ontology Best Practices:  Experiences with SWEET

Non-LivingSubstances

LivingSubstances

PhysicalProcesses

Earth Realm

PhysicalProperties

Time

NaturalPhenomena

Human Activities

Integrative Ontologies

Space

Data

SWEET 1.0 Ontologies (and their interrelationships)

Faceted Ontologies

Units

Numerics

Page 6: Ontology Best Practices:  Experiences with SWEET

SWEET 2.0 Same facets, but organized by subject 12 ontologies --> 100 ontologies Easier for domain specialists to build

self-contained specialized ontologies that extend existing ones

Page 7: Ontology Best Practices:  Experiences with SWEET

SWEET 2.0Ontologies

Importationt

Page 8: Ontology Best Practices:  Experiences with SWEET

Common Issues Units

UDUnits Standard math

Ordered pairs and triples, arithmetic operations Intervals

hasLowerBound, hasUpperBound, hasUnit Provenance

Sequence of steps Fuzzy concepts

nearlySameAs, similarityMeasure [0…1]

Page 9: Ontology Best Practices:  Experiences with SWEET

Best Practices (1): Identify characteristic level of abstraction of

each term If multiple definitions/levels (e.g., “climate”), repeat

in multiple ontologies (namespaces) Keep ontologies small, modular

Be careful that “Owl:Import” imports everything Use higher level ontologies where possible

Identify hierarchy of concept spaces Try to keep dependencies unidirectional

Page 10: Ontology Best Practices:  Experiences with SWEET

Best Practices (2):

For synonyms, identify (community, preferred term) pairs

Gain community buy-in Involve respected leaders

Most ontologies can be faceted Holistic ontologies can be layers/wrappers atop

faceted ontologies

Page 11: Ontology Best Practices:  Experiences with SWEET

Best Practices (3):

Use OWL individuals (instances) sparingly Assume OWL-DL will be used, because most tools

cannot support OWL-Full Typically, a data collection is a “class” and a component

of the Earth is a class A particular observation at a specific time is a “state” (of

the planet) which could be an individual OWL has limited capabilities

Instructions to reasoners can be included (e.g., “multiply”) Collect suggestions for implementations in future

versions, or an OWL-Sci package

Page 12: Ontology Best Practices:  Experiences with SWEET

Community Issues

Review Board Who will oversee and maintain for perpetuity (or at least through the

next funding cycle) ESSI? Content

Maintain alignment given expansion of classes and properties No removal of terms except for spelling or factual errors Subscription service to notify affected ontologies when changes made Must avoid contradictions Additions can create redundancy if sameAs not used Humans must oversee “matching” CF has established moderator to carry out analogous additions

Page 13: Ontology Best Practices:  Experiences with SWEET

PlanetOnt.orgCollaboration Web Site

Discussion tools Blog, wiki, moderated discussion board

Version Control/ Configuration Management Trace dependencies on external ontologies Tools to search for existing concepts in registered

ontologies Ontology Validation Procedure

W3C note is formal submission method Registry/discovery of ontologies Support workflows/services for ontology development

Page 14: Ontology Best Practices:  Experiences with SWEET

PlanetOnt.org

Page 15: Ontology Best Practices:  Experiences with SWEET

ESIP Federation

Page 16: Ontology Best Practices:  Experiences with SWEET

PO.DAAC Knowledge Bases

PeopleDocuments

Data Products

MetadataTools/

Services

Roles/Tasks

ScienceConcepts

Missions

Applications

Instruments

Web Pages

DataProcessing

Organiza-tions

Announce-ments

Inquiries Computers

Public access

Page 17: Ontology Best Practices:  Experiences with SWEET

Resources SWEET

http://sweet.jpl.nasa.gov Ontology development/sharing site

http://PlanetOnt.org Noesis (search tool)

http://noesis.itsc.uah.edu SESDI

http://sesdi.hao.ucar.edu