Introduction to Semantic Web in Library Services Dr. Devika P. Madalli Documentation Research and Training Center Indian Statistical Institute, Bangalore.

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Presentation transcript:

Introduction to Semantic Web in Library Services Dr. Devika P. Madalli Documentation Research and Training Center Indian Statistical Institute, Bangalore

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).

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)

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).

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)

Web to Semantic Web HTML is more a word processor of the web not a database of the web HTML Tags are non-semantic For eg:

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?

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)

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).

Similarities (Greenberg, 2007) ExamplesLibrary ServicesSemantic 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.

ExamplesLibrary ServicesSemantic 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

Semantic Web Development Traditional ServicesSemantic Web Services Collection developmentSemantic Web selection Cataloging‘Semantic metadata’ representation ReferenceSemantic Web reference service ClassificationKnowledge representation

Library Approach Compare Web Search Engines with Search facilities librarians are familiar with (bibliographic databases), like  CD-databases  On-line databases  Library automation packages

Different Search options Nested Boolean By Field By Date By Range Proximity

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?

DRTC-ISI Semantic Web projects Living Knowledge: European Commission project, Frontier and Emerging Technologies (FET) AgINFRA: European Commission project, e- infrastructure project

Background – LivingKnowledge Project Living Knowledge’ (LK) [EU FET project n ] 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.

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

Living Knowledge Project

Aginfra European Commission FP7 'research infrastructure...' project

Aginfra A data infrastructure to support agricultural scientific communities Promoting data sharing and development of trust in agricultural sciences

AgInfra Consortium University of Alcala (UAH), Spain Food & Agriculture Organization of the United Nations (FAO), Rome, Italy National Institute of Nuclear Physics (INFN), Italy Salzburg Research Forschungsgesellschaft (SRFG), Austria Institute of Physics, Belgrade (IPB), Serbia Computer and Automation Research Institute, Hungarian Academy of Sciences (SZTAKI), Hungary Agro-Know Technologies (AK), Greece 21c Consultancy (21c), UK Escuela Superior Politecnica del Litoral (ESPOL), Ecuador Chinese Academy of Agricultural Sciences (CAAS), China The Open University (OU), UK Indian Statistical Institute, India

Entity type [E] Musical instrument Idophone Struck idiophone Plucked idophone Friction idophone Membranophone Struck membranophone Plucked membranophone Friction membranophone Singing membrane Chordophone Simple chordophone Composite chordphone Aerophone Free aerophone Non-free aerophone Electrophone Entity type [E] Kinds of music Dramatic music opera Religious music Church music Sacred instrumental music Vocal music Sequences Capella music Instrumental music Symphonic music Ensemble music Popular music Avant garde Chamber music Instruments concertante Glimpses of music ontology

Relation [R] Person Study Musicologist Organologist Ethnomusicologist Instrument Pianist Violinist Keyboardist Contribution Writer Vocalist Lyricist Work Impresario Choral director Arranger Recording Recording engineer Audio-visual technician Glimpses of music ontology (2) Attribute [A] Musical work First movement Allegro Presto Second movement Third movement Last movement Music form Shorter form Dance form Ballroom dance Media Utilities Storage media Compression File format Standard and quality Ceritification Certification...

Statistics ObjectsQuantity Entity types637 Relations55 Attributes32

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?

Challenges for Semantic Web 1.Knowledge modelling 2.Domain Ontology Building and Inconsistent Ontologies 3.Crosswalking 4.Interoperability

Semantic Technology for Libraries Richer metadata Enhanced user-profiling Enhanced searching and browsing Displaying results Connecting ideas and people

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 Berners-Lee, T., Hendler, J., and Lassila, O. (2001). The Semantic Web. Scientific American, 284(5):