What can be done with the Semantic Web? An overview of Watson-based applications

Thanks to the huge efforts deployed in the community for creating, building and generating semantic information for the Semantic Web, large amounts of machine processable knowledge are now openly available. Watson is an infrastructure component for the Semantic Web, a gateway that provides the necessary functions to support applications in using the Semantic Web. In this paper, we describe a number of applications relying on Watson, with the purpose of demonstrating what can be achieved with the Semantic Web nowadays and what sort of new, smart and useful features can be derived from the exploitation of this large, distributed and heterogeneous base of semantic information

Ontology Services for Knowledge Organization Systems

Ontologies and other knowledge organization systems, such as controlled vocabularies, can be used to enhance the findability of information. By describing the contents of documents using a shared, harmonized terminology, information systems can provide efficient search and browsing functionalities for the contents. Explicit descriptive metadata aims to solve some of the prevailing issues in full text search in many search engines, including the processing of synonyms and homonyms. The use of ontologies as domain models enables the machine-processability of contents, semantic reasoning, information integration, and other intelligent ways of processing the data. The utilization of knowledge organization systems in content indexing and information retrieval can be facilitated by providing automated tools for their efficient use. This thesis studies and presents novel methods and systems for publishing and using knowledge organization systems as ontology services. The research is conducted by designing and evaluating prototype systems that support the use of ontologies in real-life use cases. The research follows the principles of the design science and action research methodologies. The presented ONKI system provides user interface components and application programming interfaces that can be integrated into external applications to enable ontology-based workflows. The features of the system are based on analyzing the needs of the main user groups of ontologies. The common functionalities identified in ontology-based workflows include concept search, browsing, and selection. The thesis presents the Linked Open Ontology cloud approach for managing and publishing a set of interlinked ontologies in an ontology service. The system enables the users to use multiple ontologies as a single, interoperable, cross-domain representation instead of individual ontologies. For facilitating the simultaneous use of ontologies published in different ontology repositories, the Normalized Ontology Repository approach is presented. As a use case of managing and publishing a semantically rich knowledge organization system as an ontology, the thesis presents the Taxon Meta-Ontology model for biological nomenclatures and classifications. The model supports the representation of changes and differing opinions of taxonomic concepts. The ONKI system and the ontologies developed using the methods presented in this thesis have been provided as a living lab service http://onki.fi, which has been run since 2008. The service provides tools and support for the users of ontologies, including content indexers, information searchers, ontology developers, and application developers.Ontologioita ja muita tietämyksen järjestämisen menetelmiä, kuten kontrolloituja sanastoja, voidaan käyttää tiedon löytämisen parantamiseksi. Kun dokumenttien sisällöt kuvaillaan käyttämällä jaettua, yhtenäistettyä terminologiaa, tietojärjestelmät voivat tarjota tehokkaita haku- ja selaustoiminnallisuuksia sisältöihin. Eksplisiittisesti esitetty, kuvaileva metatieto pyrkii ratkaisemaan monien hakukoneiden käyttämän kokotekstihaun ongelmia, kuten synonyymien ja homonyymien huomioimisen. Ontologioiden käyttäminen käsitemalleina mahdollistaa sisältöjen koneellisen käsittelyn, semanttisen päättelyn, tiedon integroinnin ja muita älykkäitä menetelmiä. Tietämyksen järjestämisen menetelmien hyödyntämistä sisältöjen indeksoinnissa ja haussa voidaan helpottaa tarjoamalla käyttäjille automatisoituja työkaluja niiden tehokkaaseen käyttämiseen. Tässä väitöskirjassa tutkitaan ja esitetään uudenlaisia menetelmiä ja järjestelmiä tietämyksen järjestämisen menetelmien julkaisemiseksi ontologiapalveluina. Tutkimus on toteutettu suunnittelemalla ja arvioimalla prototyyppijärjestelmiä, jotka edistävät ontologioiden käyttämistä todellisissa käyttötapauksissa. Tutkimus nojautuu suunnittelutieteen ja toimintatutkimuksen metodologioiden periaatteisiin. Työssä esitetty ONKI-järjestelmä tarjoaa käyttöliittymäkomponentteja ja ohjelmallisia rajapintoja, jotka voidaan integroida ulkoisiin sovelluksiin ontologiaperustaisten työnkulkujen mahdollistamiseksi. Järjestelmän ominaisuudet on toteutettu perustuen ontologioiden keskeisten käyttäjäryhmien tarpeiden selvittämiseen. Ontologiaperustaisista työnkuluista tunnistettuja yleisiä toiminnallisuuksia ovat käsitteen haku, selailu ja valinta. Tässä työssä esitetään linkitetyn avoimen ontologiapilven menetelmä toisiinsa linkitettyjen ontologioiden ylläpitämiseen ja julkaisemiseen ontologiapalvelussa. Järjestelmän avulla käyttäjät voivat käyttää useita ontologioita yhtenä, yhteentoimivana, alat yhdistävänä kokonaisuutena erillisten ontologioiden sijaan. Eri ontologiapalveluissa julkaistujen ontologioiden samanaikaisen käytön helpottamiseksi esitetään normalisoidun ontologiapalvelun menetelmä. Käyttötapauksena semanttisesti rikkaan tietämyksen järjestämisen menetelmän ylläpitämisestä ja julkaisemisesta työssä esitetään biologisten nimistöjen ja luokitusten taksonominen ontologiamalli. Malli mahdollistaa taksonomisten käsitteiden muutosten ja toisistaan poikkeavien näkemysten esittämisen. ONKI-järjestelmä ja työssä esitetyillä menetelmillä kehitetyt ontologiat ovat olleet käytettävissä living lab -palvelussa http://onki.fi, joka on ollut toiminnassa vuodesta 2008 lähtien. Palvelu tarjoaa työkaluja ja tukea ontologioiden käyttäjille, kuten tiedon indeksoijille, hakijoille, ontologioiden kehittäjille ja sovelluskehittäjille

Proof of Concept of Ontology-based Query Expansion on Financial Domain

Este trabajo presenta el uso de una ontología en el dominio financiero para la expansión de consultas con el fin de mejorar los resultados de un sistema de recuperación de información (RI) financiera. Este sistema está compuesto por una ontología y un índice de Lucene que permite recuperación de conceptos identificados mediante procesamiento de lenguaje natural. Se ha llevado a cabo una evaluación con un conjunto limitado de consultas y los resultados indican que la ambigüedad sigue siendo un problema al expandir la consulta. En ocasiones, la elección de las entidades adecuadas a la hora de expandir las consultas (filtrando por sector, empresa, etc.) permite resolver esa ambigüedad.This paper explains the application of ontologies in financial domains to a query expansion process. The final goal is to improve financial information retrieval effectiveness. The system is composed of an ontology and a Lucene index that stores and retrieves natural language concepts. An initial evaluation with a limited number of queries has been performed. Obtained results show that ambiguity remains a problem when expanding a query. The filtering of entities in the expansion process by selecting only companies or references to markets helps in the reduction of ambiguity.Este trabajo ha sido parcialmente financiado por el proyecto Trendminer (EU FP7-ICT287863) , el proyecto Monnet (EU FP7-ICT 247176) y MA2VICMR (S2009/TIC-1542).Publicad

Ontology-based end-user visual query formulation: Why, what, who, how, and which?

Value creation in an organisation is a time-sensitive and data-intensive process, yet it is often delayed and bounded by the reliance on IT experts extracting data for domain experts. Hence, there is a need for providing people who are not professional developers with the flexibility to pose relatively complex and ad hoc queries in an easy and intuitive way. In this respect, visual methods for query formulation undertake the challenge of making querying independent of users’ technical skills and the knowledge of the underlying textual query language and the structure of data. An ontology is more promising than the logical schema of the underlying data for guiding users in formulating queries, since it provides a richer vocabulary closer to the users’ understanding. However, on the one hand, today the most of world’s enterprise data reside in relational databases rather than triple stores, and on the other, visual query formulation has become more compelling due to ever-increasing data size and complexity—known as Big Data. This article presents and argues for ontology-based visual query formulation for end-users; discusses its feasibility in terms of ontology-based data access, which virtualises legacy relational databases as RDF, and the dimensions of Big Data; presents key conceptual aspects and dimensions, challenges, and requirements; and reviews, categorises, and discusses notable approaches and systems

Informatic system for a global tissue–fluid biorepository with a graph theory–oriented graphical user interface

The Richard Floor Biorepository supports collaborative studies of extracellular vesicles (EVs) found in human fluids and tissue specimens. The current emphasis is on biomarkers for central nervous system neoplasms but its structure may serve as a template for collaborative EV translational studies in other fields. The informatic system provides specimen inventory tracking with bar codes assigned to specimens and containers and projects, is hosted on globalized cloud computing resources, and embeds a suite of shared documents, calendars, and video-conferencing features. Clinical data are recorded in relation to molecular EV attributes and may be tagged with terms drawn from a network of externally maintained ontologies thus offering expansion of the system as the field matures. We fashioned the graphical user interface (GUI) around a web-based data visualization package. This system is now in an early stage of deployment, mainly focused on specimen tracking and clinical, laboratory, and imaging data capture in support of studies to optimize detection and analysis of brain tumour–specific mutations. It currently includes 4,392 specimens drawn from 611 subjects, the majority with brain tumours. As EV science evolves, we plan biorepository changes which may reflect multi-institutional collaborations, proteomic interfaces, additional biofluids, changes in operating procedures and kits for specimen handling, novel procedures for detection of tumour-specific EVs, and for RNA extraction and changes in the taxonomy of EVs. We have used an ontology-driven data model and web-based architecture with a graph theory–driven GUI to accommodate and stimulate the semantic web of EV science