introduction to semantic web in library services dr. devika p. madalli documentation research and...
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Introduction to Semantic Web in Library Services
Dr. Devika P. MadalliDocumentation Research and Training Center
Indian Statistical Institute, Bangalore
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Introduction • World Wide Web has emerged as a global medium for
information exchange after the advent of Internet.
• As the technologies evolved, WWW became more dynamic and responsive than being merely a static collection of web documents.
• As business and service sectors grew, the potential of Web, various standards, software components written in different programming languages were deployed.
• Thus, Web service technology has introduced a new abstraction layer over and a radically new architecture for software, setting the stage to grow exponentially to handle complex web services (Sabou, 2006).
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Definition
• Semantic Web is a group of methods and technologies to allow machines to understand the meaning - or "semantics" - of information on the World Wide Web (Wikipedia, 2011)
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WWW to Semantic Web
• As an innovative concept, Semantic Web, develops techniques to use the existing Web data with logics based formal descriptions of their meaning. Here ontologies came
into play (Gruber, 1993).
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Web to Semantic Web
Majority of the web pages (static) are written in HTML
Even the dynamic web pages wrap information in HTML
Though dynamic web pages are retrieved normally from structured databases, but they become unstructured in HTML. In any case dynamic pages are not indexed by search engines. (Deep web problem)
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Web to Semantic Web
HTML is more a word processor of the web not a database of the web
HTML Tags are non-semanticFor eg:
<html> </html><title> </title><body><p></body>
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Semantics
Machine can handle structured data (XML) but not unstructured data (HTML)
Presently, only humans can handle unstructured data
• Eg: you have a tooth problem can your web agent recommend a “dentist” to you?
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In essence
Problem: Much of the data/information on the web is meant for human understanding and not machine processable.
Challenge: How to make data machine processable
One solution: metadata and ontologies (Librarians' tools)
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Library Vs Semantic Web
• Given that the library and the Semantic Web are cultures devoted to increasing information access and knowledge discovery, it makes sense to explore the foundations of the library (the more established institution) and consider what primary functions may help advance the Semantic Web initiative (Greenberg , 2007).
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Similarities (Greenberg, 2007) Examples Library Services Semantic Web
Response to information abundance
Library to digital library is developed since the abundance of information increased
Semantic Web was initiated as a means to more effectively manage and take advantage of the increased amount of digital data
Missions grounded in service, information access, and knowledge discovery
Objectives, goals serve the purpose to facilitate information;
Semantic Web strives to allow data to be shared and reused across applications, enterprises, and community boundaries. It is a collaborative effort led by W3C and partners, based on the Resource Description Framework (RDF)
Part of society’s fabric
Part of life, for all walks, in all types, physically and virtually
Current Web is any indication of Semantic Web’s reach, which seems quite logical, the Semantic Web will surely impact millions of people’s lives daily.
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Examples Library Services Semantic Web
Advancement via international and national standards
Libraries consolidated development of cataloging codes; formalized classificatory and verbal systems; and encoding/communication standards (International Bibliographic Description (ISBD) and MAchine Readable Cataloging (MARC), many metadata schemes, Functional Requirements for Bibliographic Records (1998), and Resource Description and Access (RDA)
The Semantic Web has followed a similar path as evidenced by a collection of information standards: eXtensible Markup Language (XML), RDF, OWL, Friend Of A Friend (FOAF), and Simple Knowledge Organizations System (SKOS).
Collaborative spirit
American Library Association, Association of Library Collections and Technical Services, Cataloging and Classification Section (ALA/ALCTS/CCS), committees review cataloging polices and standards, and interact with international organizations (e.g, IFLA and the Dublin Core Metadata Initiative).
All of the enabling technologies/standards listed above (RDF, OWL, FOAF, and SKOS) have been developed through working groups and public calls for comment.. The World Wide Web Consortium (W3C), the home of the Semantic Web, involves academic, research, and industry members
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Semantic Web Development
Traditional Services Semantic Web Services
Collection development Semantic Web selection
Cataloging ‘Semantic metadata’ representation
Reference Semantic Web reference service
Classification Knowledge representation
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Library Approach
Compare Web Search Engines with Search facilities librarians are familiar with (bibliographic databases), like CD-databases On-line databases Library automation packages
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Different Search options
Nested BooleanBy FieldBy DateBy RangeProximity
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Context Sensitive Search
Can we do Context sensitive search?LIS has many models
PRECIS POPSI etc.
Are we overemphasising on Recall? In the era of 'information glut/deluge', should we
emphasize recall rather than Precision?
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DRTC-ISI Semantic Web projects
Living Knowledge: European Commission project, Frontier and Emerging Technologies (FET)
AgINFRA: European Commission project, e-infrastructure project
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Background – LivingKnowledge Project
• Living Knowledge’ (LK) [EU FET project n0 231126] considers diversity as an asset and aimed to make it traceable, understandable and exploitable, with the goal of improving navigation and searching in very large datasets (Maltese, etal, 2009). Aims of the project
• study the effects of diversity and time on opinions and bias in socio-economic relevance, especially for seamless representation and exchange of information.
• Intuitive search and navigation tools (e.g. search engines) need produce more insightful, better organized, aggregated and easier-to-understand output.
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1. UNIVERSITÀ DEGLI STUDI DI TRENTO, Trento - ITALY
2. FUNDACIÓ BARCELONA MEDIA UNIVERSITAT POMPEU FABRA, Barcelona – SPAIN
3. SORA, Vienna – AUSTRIA
4. CONSORZIO NAZIONALE INTERUNIVERSITARIO PER LE TELECOMUNICAZIONI, Parma ITALY
5. STICHTING EUROPEAN ARCHIVE, Amsterdam – NETHERLANDS
6. UNIVERSITÀ DEGLI STUDI DI PAVIA, Pavia – ITALY
7. UNIVERSITY OF SOUTHAMPTON, Southampton, UNITED KINDOM
8. DOCUMENTATION RESEARCH AND TRAINING CENTRE, INDIAN STATISTICAL INSTITUTE
9. GOTTFRIED WILHELM LEIBNIZ UNIVERSITAET HANNOVER, GERMANY.
10. MAX PLANCK GESELLSCHAFT ZUR FOERDERUNG DER WISSENSCHAFTEN E.V., Muenchen – GERMANY
Living Knowledge Consortium
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Living Knowledge Project
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Aginfra
• European Commission FP7 'research infrastructure...' project
• http://aginfra.eu/
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Aginfra
A data infrastructure to support agricultural scientific communities Promoting data sharing and development of trust in agricultural sciences
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AgInfra Consortium
University of Alcala (UAH), SpainFood & Agriculture Organization of the United Nations (FAO), Rome , ItalyNational Institute of Nuclear Physics (INFN), ItalySalzburg Research Forschungsgesellschaft (SRFG), Austria Institute of Physics, Belgrade (IPB), Serbia Computer and Automation Research Institute, Hungarian Academy of Sciences (SZTAKI), HungaryAgro-Know Technologies (AK), Greece21c Consultancy (21c), UKEscuela Superior Politecnica del Litoral (ESPOL), EcuadorChinese Academy of Agricultural Sciences (CAAS), ChinaThe Open University (OU), UKIndian Statistical Institute, India
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Entity type [E]
Musical instrument Idophone
Struck idiophonePlucked idophoneFriction idophone
MembranophoneStruck membranophonePlucked membranophoneFriction membranophoneSinging membrane
ChordophoneSimple chordophoneComposite chordphone
AerophoneFree aerophoneNon-free aerophone
Electrophone
Entity type [E]
Kinds of music Dramatic music
operaReligious music
Church musicSacred instrumental music
Vocal musicSequencesCapella music
Instrumental musicSymphonic musicEnsemble music
Popular musicAvant garde
Chamber musicInstruments concertante
Glimpses of music ontology
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Relation [R]Person
StudyMusicologistOrganologistEthnomusicologist
InstrumentPianistViolinistKeyboardist
ContributionWriterVocalistLyricist
WorkImpresarioChoral directorArranger
RecordingRecording engineerAudio-visual technician
Glimpses of music ontology (2)
Attribute [A]
Musical work First movement
AllegroPresto
Second movementThird movementLast movement
Music form Shorter formDance formBallroom dance
Media UtilitiesStorage media
CompressionFile format Standard and quality
CeritificationCertification
...
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Statistics
Objects Quantity
Entity types 637
Relations 55
Attributes 32
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Can we?
Can we get precise search results for queries like Who is the author of Tom Sawyer? Who works on ontology engineering in India? I have toothache! (fetches list of dentists) What are the trains between Mumbai and Delhi?
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Challenges for Semantic Web
1. Knowledge modelling 2. Domain Ontology Building and Inconsistent
Ontologies 3. Crosswalking 4. Interoperability
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Semantic Technology for Libraries
• Richer metadata• Enhanced user-profiling • Enhanced searching and browsing • Displaying results • Connecting ideas and people
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References
• McIlraith, S., Son, T., and Zeng, H. (2001). Semantic Web Services. IEEE Intelligent Systems. Special Issue on the Semantic Web, 16(2):46 – 53.
• Sabou, M. (2006). Building Web Service Ontologies, SIKS Dissertation Series No. 2006-4.
• Berners-Lee, T., Hendler, J., and Lassila, O. (2001). The Semantic Web. Scientific American, 284(5): 34-43.
• http://xmlns.com/foaf/spec/
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