COMP 6703 eScience Project Semantic Web for Museums Student : Lei Junran Client/Technical Supervisor : Tom Worthington Academic Supervisor : Peter Strazdins.
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COMP 6703 eScience Project Semantic Web for Museums Student : Lei Junran Client/Technical Supervisor : Tom Worthington Academic Supervisor : Peter Strazdins Period : 2006 Semester 1
What is in my presentation Motivation Objectives Technologies Design Considerations Demonstration Conclusion Future Work
Motivation - Constraints Constrains of Current Museums Collections Management Methods –Natural features of cultural collections — Rich associations eg, creator of painting A had other paintings with the same style, which originates from another artist, who drew painting B with the same topic… –Collections are preserved as isolated objects in individual museums
Motivation - Solution The emerging semantic web technology (W3C Semantic Web) would be proposed to solve the constraints and provide a better way for cultural heritage preservation and management.
Project Objectives Current Objective - to develop an effective semantic web archive system for museums. Long Terms - research the promising semantic technology for creating the knowledge management network among museums.
Technologies- What is Semantic Web Tim Berners-Lee's original web vision involved more than retrieving Hypertext Markup Language (HTML) pages from Web servers. Make the web a more collaborative medium. Create a web of data that machines can process
How to make Semantic Web possible? Make the data smarter. –application-independent, easily discovered, to be described with concrete relationships…
Four Levels of smart data Text Documents and Database Records –Data just can be used in a single application XML documents using single vocabulary –Data is now smart enough to move between applications in this museum. XML documents with mixed vocabularies – Data can be composed from multiple museums or institutes
Four Levels of smart data Ontologies and rules –data is now smart enough to be described with concrete relationships –new data can be inferred from existing data by following logical rules
Semantic Web Elements and technologies Metadata XML RDF Ontology
Metadata Meta-data: meaning of data values; Example : DATA META DATA John Smith Name 222 Happy Lane Address
XML XML(Extensible Markup Language) is the syntactic foundation layer of the Semantic Web. Provides a simple, standard syntax for encoding the meaning of data values, or meta data. Example : John Smith 222 Happy Lane
XML Metadata benefits All data are described with a set of predefined vocabulary and syntax. Enable exchange, interoperability, information integration and application independence.
RDF The resource described in RDF could be identified by URI. The statement about resource is combined of three elements, or triple. &ns;/location/ Greece Subject &ns;/location/ Europe Object locateAt Predicate
What are included in Ontology? Classes: Object, Activity, Location Relationships: object location, company organization Properties: Identifier(cardinality 1:1), Type, Creator Constrains and Rules: If X is true, then Y must also be true. Functions and Process: A formal vocabulary (defined terms) for all above
Ontology Languages Ontology is represented in knowledge representation languages –RDFS (lightweight ontology) Elements: Class, label, subclassOf, Property, Domain, range, type, subPropertyof… –OWL (Robust ontology) Elements: RDFS plus someValuesFrom ∃, allValuesFrom ∀, hasValue ∋, minCardinality ≥, cardinality =, intersectionOf, unionOf…
Why Use Ontology defines the domain vocabulary. Improve association expression, interoperability Ontology languages are backed by a rigorous formal logic, which makes the ontology machine-interpretable.
Semantic Levels Summary Semantic Levels (Redrawn after C. Daconta, et al 2003)
Design Considerations Use existing ontology –CIDOC CRM CIDOC: The International Committee for Documentation of the International Council of Museums CRM: Conceptual Reference Model A domain ontology for cultural heritage information
Design Considerations Use existing metadata standard –Dublin Core A simple yet effective element set for describing a wide range of networked resources. Simplicity, Commonly understood semantics, Extensibility Example Elements: Identifier, Description, Format, Date, Creator…
CIDOC CRM Advantages –Comprehensive and widely accepted –Mappings have been established with major metadata standards Disadvantages –Includes 81 classes and 132 properties –Vocabulary is too detailed to be used as metadata directly
Solutions Use subset of CRM Use Dublin Core Metadata Standard Redesign the vocabulary of the applied subset when DC can not express the meaning of the subset. Use DC and subset vocabulary (SWM vocabulary) as metadata
Conclusion A semantic web prototype system has been developed A RDF Schema has been designed The museums collections could be input and transferred to RDF data for preservation
Conclusion Data is now smart enough to be described with concrete relationships RDF data output and Batch input increases the interoperability with other semantic systems and provide a convenient transfer way to existing data.
Review the four levels of smart data Ontologies and rules –data is now smart enough to be described with concrete relationships –new data can be inferred from existing data by following logical rules
Half way of the fourth level Reasons –Use RDFS (lightweight ontology language); –Use subset of ontology, the relationships is not rich enough. –No enough constrains, rules and associations to infer.
Future Work Redesign Ontology using robust ontology language (eg. OWL) Add more constrains and rules for inference Design system showing more benefits of semantic web technology Web Services and Taxonomies in Semantic Web.