Comparative analysis of knowledge representation and reasoning requirements across a range of life sciences textbooks.

BackgroundUsing knowledge representation for biomedical projects is now commonplace. In previous work, we represented the knowledge found in a college-level biology textbook in a fashion useful for answering questions. We showed that embedding the knowledge representation and question-answering abilities in an electronic textbook helped to engage student interest and improve learning. A natural question that arises from this success, and this paper's primary focus, is whether a similar approach is applicable across a range of life science textbooks. To answer that question, we considered four different textbooks, ranging from a below-introductory college biology text to an advanced, graduate-level neuroscience textbook. For these textbooks, we investigated the following questions: (1) To what extent is knowledge shared between the different textbooks? (2) To what extent can the same upper ontology be used to represent the knowledge found in different textbooks? (3) To what extent can the questions of interest for a range of textbooks be answered by using the same reasoning mechanisms?ResultsOur existing modeling and reasoning methods apply especially well both to a textbook that is comparable in level to the text studied in our previous work (i.e., an introductory-level text) and to a textbook at a lower level, suggesting potential for a high degree of portability. Even for the overlapping knowledge found across the textbooks, the level of detail covered in each textbook was different, which requires that the representations must be customized for each textbook. We also found that for advanced textbooks, representing models and scientific reasoning processes was particularly important.ConclusionsWith some additional work, our representation methodology would be applicable to a range of textbooks. The requirements for knowledge representation are common across textbooks, suggesting that a shared semantic infrastructure for the life sciences is feasible. Because our representation overlaps heavily with those already being used for biomedical ontologies, this work suggests a natural pathway to include such representations as part of the life sciences curriculum at different grade levels

PowerAqua: Open Question Answering on the Semantic Web

With the rapid growth of semantic information in the Web, the processes of searching and querying these very large amounts of heterogeneous content have become increasingly challenging. This research tackles the problem of supporting users in querying and exploring information across multiple and heterogeneous Semantic Web (SW) sources. A review of literature on ontology-based Question Answering reveals the limitations of existing technology. Our approach is based on providing a natural language Question Answering interface for the SW, PowerAqua. The realization of PowerAqua represents a considerable advance with respect to other systems, which restrict their scope to an ontology-specific or homogeneous fraction of the publicly available SW content. To our knowledge, PowerAqua is the only system that is able to take advantage of the semantic data available on the Web to interpret and answer user queries posed in natural language. In particular, PowerAqua is uniquely able to answer queries by combining and aggregating information, which can be distributed across heterogeneous semantic resources. Here, we provide a complete overview of our work on PowerAqua, including: the research challenges it addresses; its architecture; the techniques we have realised to map queries to semantic data, to integrate partial answers drawn from different semantic resources and to rank alternative answers; and the evaluation studies we have performed, to assess the performance of PowerAqua. We believe our experiences can be extrapolated to a variety of end-user applications that wish to open up to large scale and heterogeneous structured datasets, to be able to exploit effectively what possibly is the greatest wealth of data in the history of Artificial Intelligence

Knowledge Extraction from Textual Resources through Semantic Web Tools and Advanced Machine Learning Algorithms for Applications in Various Domains

Nowadays there is a tremendous amount of unstructured data, often represented by texts, which is created and stored in variety of forms in many domains such as patients' health records, social networks comments, scientific publications, and so on. This volume of data represents an invaluable source of knowledge, but unfortunately it is challenging its mining for machines. At the same time, novel tools as well as advanced methodologies have been introduced in several domains, improving the efficacy and the efficiency of data-based services. Following this trend, this thesis shows how to parse data from text with Semantic Web based tools, feed data into Machine Learning methodologies, and produce services or resources to facilitate the execution of some tasks. More precisely, the use of Semantic Web technologies powered by Machine Learning algorithms has been investigated in the Healthcare and E-Learning domains through not yet experimented methodologies. Furthermore, this thesis investigates the use of some state-of-the-art tools to move data from texts to graphs for representing the knowledge contained in scientific literature. Finally, the use of a Semantic Web ontology and novel heuristics to detect insights from biological data in form of graph are presented. The thesis contributes to the scientific literature in terms of results and resources. Most of the material presented in this thesis derives from research papers published in international journals or conference proceedings

DESIGN AND EXPLORATION OF NEW MODELS FOR SECURITY AND PRIVACY-SENSITIVE COLLABORATION SYSTEMS

Collaboration has been an area of interest in many domains including education, research, healthcare supply chain, Internet of things, and music etc. It enhances problem solving through expertise sharing, ideas sharing, learning and resource sharing, and improved decision making. To address the limitations in the existing literature, this dissertation presents a design science artifact and a conceptual model for collaborative environment. The first artifact is a blockchain based collaborative information exchange system that utilizes blockchain technology and semi-automated ontology mappings to enable secure and interoperable health information exchange among different health care institutions. The conceptual model proposed in this dissertation explores the factors that influences professionals continued use of video- conferencing applications. The conceptual model investigates the role the perceived risks and benefits play in influencing professionals’ attitude towards VC apps and consequently its active and automatic use

Working Notes from the 1992 AAAI Workshop on Automating Software Design. Theme: Domain Specific Software Design

The goal of this workshop is to identify different architectural approaches to building domain-specific software design systems and to explore issues unique to domain-specific (vs. general-purpose) software design. Some general issues that cut across the particular software design domain include: (1) knowledge representation, acquisition, and maintenance; (2) specialized software design techniques; and (3) user interaction and user interface

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

04441 Abstracts Collection -- Mobile Information Management

From 24.10.04 to 29.10.04, the Dagstuhl Seminar 04441 ``Mobile Information Management\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Managing Changes in Collaborative Networks: A Conceptual Approach

Collaborative Networks represent organizational forms that became omnipresent in today’s way of making business. Such organizational forms are often established in order to satisfy a complex customer need, which one company could not satisfy on its own. This means that the participating companies are to a certain degree dependent on each other. Managing inter-firm relationships by means of inter-organizational interdependencies represents an important Business-IT Alignment issue. In this paper, we present the Dependency-based Alignment Framework, which represents a conceptual approach for managing changes in Collaborative Networks from a holistic perspective. A detailed and methodologically well-founded approach in the definition and design of our framework is accompanied by a detailed investigation of relevant properties of this design artifact. To demonstrate the applicability of our framework in practice, we introduce a case study, which uses Semantic Media Wiki and the SPARQL query language. Finally, we evaluate our results in an argumentative and deductively descriptive way