Semantic Web Technologies for Enterprise Application Integration
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Semantic Integration and Knowledge Discovery for Environmental Research
Journal of Database Management, 18(1), 43-67, January-March 2007 43 Semantic Integration and Knowledge Discovery for Environmental Research Zhiyuan Chen, University of Maryland, Baltimore County (UMBC), USA Aryya Gangopadhyay, University of Maryland, Baltimore County (UMBC), USA George Karabatis, University of Maryland, Baltimore County (UMBC), USA Michael McGuire, University of Maryland, Baltimore County (UMBC), USA Claire Welty, University of Maryland, Baltimore County (UMBC), USA ABSTRACT Environmental research and knowledge discovery both require extensive use of data stored in various sources and created in different ways for diverse purposes. We describe a new metadata approach to elicit semantic information from environmental data and implement semantics- based techniques to assist users in integrating, navigating, and mining multiple environmental data sources. Our system contains specifications of various environmental data sources and the relationships that are formed among them. User requests are augmented with semantically related data sources and automatically presented as a visual semantic network. In addition, we present a methodology for data navigation and pattern discovery using multi-resolution brows- ing and data mining. The data semantics are captured and utilized in terms of their patterns and trends at multiple levels of resolution. We present the efficacy of our methodology through experimental results. Keywords: environmental research, knowledge discovery and navigation, semantic integra- tion, semantic networks, -
Semantic Integration Across Heterogeneous Databases Finding Data Correspondences Using Agglomerative Hierarchical Clustering and Artificial Neural Networks
DEGREE PROJECT IN COMPUTER SCIENCE AND ENGINEERING, SECOND CYCLE, 30 CREDITS STOCKHOLM, SWEDEN 2018 Semantic Integration across Heterogeneous Databases Finding Data Correspondences using Agglomerative Hierarchical Clustering and Artificial Neural Networks MARK HOBRO KTH ROYAL INSTITUTE OF TECHNOLOGY SCHOOL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCE Semantic Integration across Heterogeneous Databases Finding Data Correspondences using Agglomerative Hierarchical Clustering and Artificial Neural Networks MARK HOBRO Master in Computer Science Date: April 11, 2018 Supervisor: John Folkesson Examiner: Hedvig Kjellström Swedish title: Semantisk integrering mellan heterogena databaser: Hitta datakopplingar med hjälp av hierarkisk klustring och artificiella neuronnät School of Computer Science and Communication iii Abstract The process of data integration is an important part of the database field when it comes to database migrations and the merging of data. The research in the area has grown with the addition of machine learn- ing approaches in the last 20 years. Due to the complexity of the re- search field, no go-to solutions have appeared. Instead, a wide variety of ways of enhancing database migrations have emerged. This thesis examines how well a learning-based solution performs for the seman- tic integration problem in database migrations. Two algorithms are implemented. One that is based on informa- tion retrieval theory, with the goal of yielding a matching result that can be used as a benchmark for measuring the performance of the machine learning algorithm. The machine learning approach is based on grouping data with agglomerative hierarchical clustering and then training a neural network to recognize patterns in the data. This al- lows making predictions about potential data correspondences across two databases. -
L Dataspaces Make Data Ntegration Obsolete?
DBKDA 2011, January 23-28, 2011 – St. Maarten, The Netherlands Antilles DBKDA 2011 Panel Discussion: Will Dataspaces Make Data Integration Obsolete? Moderator: Fritz Laux, Reutlingen Univ., Germany Panelists: Kazuko Takahashi, Kwansei Gakuin Univ., Japan Lena Strömbäck, Linköping Univ., Sweden Nipun Agarwal, Oracle Corp., USA Christopher Ireland, The Open Univ., UK Fritz Laux, Reutlingen Univ., Germany DBKDA 2011, January 23-28, 2011 – St. Maarten, The Netherlands Antilles The Dataspace Idea Space of Data Management Scalable Functionality and Costs far Web Search Functionality virtual Organization pay-as-you-go, Enterprise Dataspaces Admin. Portal Schema Proximity Federated first, DBMS DBMS scient. Desktop Repository Search DBMS schemaless, near unstructured high Semantic Integration low Time and Cost adopted from [Franklin, Halvey, Maier, 2005] DBKDA 2011, January 23-28, 2011 – St. Maarten, The Netherlands Antilles Dataspaces (DS) [Franklin, Halevy, Maier, 2005] is a new abstraction for Information Management ● DS are [paraphrasing and commenting Franklin, 2009] – Inclusive ● Deal with all the data of interest, in whatever form => but semantics matters ● We need access to the metadata! ● derive schema from instances? ● Discovering new data sources => The Münchhausen bootstrap problem? Theodor Hosemann (1807-1875) DBKDA 2011, January 23-28, 2011 – St. Maarten, The Netherlands Antilles Dataspaces (DS) [Franklin, Halevy, Maier, 2005] is a new abstraction for Information Management ● DS are [paraphrasing and commenting Franklin, 2009] – Co-existence -
Learning to Match Ontologies on the Semantic Web
The VLDB Journal manuscript No. (will be inserted by the editor) Learning to Match Ontologies on the Semantic Web AnHai Doan1, Jayant Madhavan2, Robin Dhamankar1, Pedro Domingos2, Alon Halevy2 1 Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA fanhai,[email protected] 2 Department of Computer Science and Engineering, University of Washington, Seattle, WA 98195, USA fjayant,pedrod,[email protected] Received: date / Revised version: date Abstract On the Semantic Web, data will inevitably come and much of the potential of the Web has so far remained from many different ontologies, and information processing untapped. across ontologies is not possible without knowing the seman- In response, researchers have created the vision of the Se- tic mappings between them. Manually finding such mappings mantic Web [BLHL01], where data has structure and ontolo- is tedious, error-prone, and clearly not possible at the Web gies describe the semantics of the data. When data is marked scale. Hence, the development of tools to assist in the ontol- up using ontologies, softbots can better understand the se- ogy mapping process is crucial to the success of the Seman- mantics and therefore more intelligently locate and integrate tic Web. We describe GLUE, a system that employs machine data for a wide variety of tasks. The following example illus- learning techniques to find such mappings. Given two on- trates the vision of the Semantic Web. tologies, for each concept in one ontology GLUE finds the most similar concept in the other ontology. We give well- founded probabilistic definitions to several practical similar- Example 1 Suppose you want to find out more about some- ity measures, and show that GLUE can work with all of them. -
Towards a Conceptual Framework for Persistent
Nova Southeastern University NSUWorks CEC Theses and Dissertations College of Engineering and Computing 2017 Towards a Conceptual Framework for Persistent Use: A Technical Plan to Achieve Semantic Interoperability within Electronic Health Record Systems Shellon Blackman-Lees Nova Southeastern University, [email protected] This document is a product of extensive research conducted at the Nova Southeastern University College of Engineering and Computing. For more information on research and degree programs at the NSU College of Engineering and Computing, please click here. Follow this and additional works at: https://nsuworks.nova.edu/gscis_etd Part of the Computer Sciences Commons Share Feedback About This Item NSUWorks Citation Shellon Blackman-Lees. 2017. Towards a Conceptual Framework for Persistent Use: A Technical Plan to Achieve Semantic Interoperability within Electronic Health Record Systems. Doctoral dissertation. Nova Southeastern University. Retrieved from NSUWorks, College of Engineering and Computing. (998) https://nsuworks.nova.edu/gscis_etd/998. This Dissertation is brought to you by the College of Engineering and Computing at NSUWorks. It has been accepted for inclusion in CEC Theses and Dissertations by an authorized administrator of NSUWorks. For more information, please contact [email protected]. Towards a Conceptual Framework for Persistent Use: A Technical Plan to Achieve Semantic Interoperability within Electronic Health Record Systems By Shellon M. Blackman-Lees A dissertation report submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Information Systems College of Engineering and Computing Nova Southeastern University 2017 An Abstract of a Dissertation Submitted to Nova Southeastern University in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Towards a Conceptual Framework for Persistent Use: A Technical Plan to Achieve Semantic Interoperability within Electronic Health Record Systems by Shellon M. -
Semantic Integration in the IFF Gies , Etc
ogies, composing ontologies via fusions, noting dependen- cies between ontologies, declaring the use of other ontolo- 3 Semantic Integration in the IFF gies , etc. The IFF takes a building blocks approach to- wards the development of object-level ontological struc- ture. This is a rather elaborate categorical approach, which Robert E. Kent uses insights and ideas from the theory of distributed logic Ontologos known as information flow (Barwise and Seligman, 1997) [email protected] and the theory of formal concept analysis (Ganter and Wille, 1999). The IFF represents metalogic, and as such operates at the structural level of ontologies. In the IFF, Abstract there is a precise boundary between the metalevel and the object level. The IEEE P1600.1 Standard Upper Ontology (SUO) The modular architecture of the IFF consists of metale- project aims to specify an upper ontology that will provide vels, namespaces and meta-ontologies. There are three me- a structure and a set of general concepts upon which do- talevels: top, upper and lower. This partition, which cor- main ontologies could be constructed. The Information responds to the set-theoretic distinction between small Flow Framework (IFF), which is being developed under (sets), large (classes) and generic collections, is permanent. the auspices of the SUO Working Group, represents the Each metalevel services the level below by providing a structural aspect of the SUO. The IFF is based on category language that is used to declare and axiomatize that level. theory. Semantic integration of object-level ontologies in * The top metalevel services the upper metalevel, the upper the IFF is represented with its fusion construction . -
Rule-Based Intelligence on the Semantic Web Implications for Military Capabilities
UNCLASSIFIED Rule-Based Intelligence on the Semantic Web Implications for Military Capabilities Dr Paul Smart Senior Research Fellow School of Electronics and Computer Science University of Southampton Southampton SO17 1BJ United Kingdom 26th November 2007 UNCLASSIFIED Report Documentation Page Report Title: Rule-Based Intelligence on the Semantic Web Report Subtitle Implications for Military Capabilities Project Title: N/A Number of Pages: 57 Version: 1.2 Date of Issue: 26/11/2007 Due Date: 22/11/2007 Performance EZ~01~01~17 Number of 95 Indicator: References: Reference Number: DT/Report/RuleIntel Report Availability: APPROVED FOR PUBLIC RELEASE; LIMITED DISTRIBUTION Abstract Availability: APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED Authors: Paul Smart Keywords: semantic web, ontologies, reasoning, decision support, rule languages, military Primary Author Details: Client Details: Dr Paul Smart Senior Research Fellow School of Electronics and Computer Science University of Southampton Southampton, UK SO17 1BJ tel: +44 (0)23 8059 6669 fax: +44 (0)23 8059 2783 email: [email protected] Abstract: Rules are a key element of the Semantic Web vision, promising to provide a foundation for reasoning capabilities that underpin the intelligent manipulation and exploitation of information content. Although ontologies provide the basis for some forms of reasoning, it is unlikely that ontologies, by themselves, will support the range of knowledge-based services that are likely to be required on the Semantic Web. As such, it is important to consider the contribution that rule-based systems can make to the realization of advanced machine intelligence on the Semantic Web. This report aims to review the current state-of-the-art with respect to semantic rule-based technologies. -
Semantic Web Technologies and Data Management
Semantic Web Technologies and Data Management Li Ma, Jing Mei, Yue Pan Krishna Kulkarni Achille Fokoue, Anand Ranganathan IBM China Research Laboratory IBM Software Group IBM Watson Research Center Bei Jing 100094, China San Jose, CA 95141-1003, USA New York 10598, USA Introduction The Semantic Web aims to build a common framework that allows data to be shared and reused across applications, enterprises, and community boundaries. It proposes to use RDF as a flexible data model and use ontology to represent data semantics. Currently, relational models and XML tree models are widely used to represent structured and semi-structured data. But they offer limited means to capture the semantics of data. An XML Schema defines a syntax-valid XML document and has no formal semantics, and an ER model can capture data semantics well but it is hard for end-users to use them when the ER model is transformed into a physical database model on which user queries are evaluated. RDFS and OWL ontologies can effectively capture data semantics and enable semantic query and matching, as well as efficient data integration. The following example illustrates the unique value of semantic web technologies for data management. Figure 1. An example of ontology based data management In Figure 1, we have two tables in a relational database. One stores some basic information of several companies, and another one describes shareholding relationship among these companies. Sometimes, users want to issue such a query “find Company EDOX’s all direct and indirect shareholders which are from Europe and are IT company”. Based on the data stored in the database, existing RDBMSes cannot represent and answer the above query. -
Semantic Integration and Analysis of Clinical Data-1024
Semantic integration and analysis of clinical data Hong Sun, Kristof Depraetere, Jos De Roo, Boris De Vloed, Giovanni Mels, Dirk Colaert Advanced Clinical Applications Research Group, Agfa HealthCare, Gent, Belgium {hong.sun, kristof.depraetere, jos.deroo, boris.devloed, giovanni.mels, dirk.colaert }@agfa.com Abstract. There is a growing need to semantically process and integrate clinical data from different sources for Clinical Data Management and Clinical Deci- sion Support in the healthcare IT industry. In the clinical practice domain, the semantic gap between clinical information systems and domain ontologies is quite often difficult to bridge in one step. In this paper, we report our experi- ence in using a two-step formalization approach to formalize clinical data, i.e. from database schemas to local formalisms and from local formalisms to do- main (unifying) formalisms. We use N3 rules to explicitly and formally state the mapping from local ontologies to domain ontologies. The resulting data ex- pressed in domain formalisms can be integrated and analyzed, though originat- ing from very distinct sources. Practices of applying the two-step approach in the infectious disorders and cancer domains are introduced. Keywords: Semantic interoperability, N3 rules, SPARQL, formal clinical data, data integration, data analysis, clinical information system. 1 Introduction A decade ago formal semantics, the study of logic within a linguistic framework, found a new means of expression, i.e. the World Wide Web and with it the Semantic Web [1]. The Semantic Web provides additional capabilities that enable information sharing between different resources which are semantically represented. It consists of a set of standards and technologies that include a simple data model for representing information (RDF) [2], a query language for RDF (SPARQL) [3], a schema language describing RDF vocabularies (RDFS) [4], a few syntaxes to represent RDF (RDF/XML [20], N3 [19]) and a language for describing and sharing ontologies (OWL) [5]. -
A Case Study of Data Integration for Aquatic Resources Using Semantic Web Technologies
A Case Study of Data Integration for Aquatic Resources Using Semantic Web Technologies By Janice Gordon, Nina Chkhenkeli, David Govoni, Frances Lightsom, Andrea Ostroff, Peter Schweitzer, Phethala Thongsavanh, Dalia Varanka, and Stephan Zednik Open-File Report 2015–1004 U.S. Department of the Interior U.S. Geological Survey U.S. Department of the Interior SALLY JEWELL, Secretary U.S. Geological Survey Suzette M. Kimball, Acting Director U.S. Geological Survey, Reston, Virginia: 2015 For more information on the USGS—the Federal source for science about the Earth, its natural and living resources, natural hazards, and the environment—visit http://www.usgs.gov or call 1–888–ASK–USGS For an overview of USGS information products, including maps, imagery, and publications, visit http://www.usgs.gov/pubprod To order this and other USGS information products, visit http://store.usgs.gov Suggested citation: Gordon, Janice, Chkhenkeli, Nina, Govoni, David, Lightsom, Frances, Ostroff, Andrea, Schweitzer, Peter, Thongsavanh, Phethala, Varanka, Dalia, and Zednik, Stephan, 2015, A case study of data integration for aquatic resources using semantic web technologies: U.S. Geological Survey Open-File Report 2015–1004, 55 p., http://dx.doi.org/10.3133/ofr20151004. ISSN 2331-1258 (online) Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Although this information product, for the most part, is in the public domain, it also may contain copyrighted materials as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner. ii Contents Abstract ...................................................................................................................................................................... 1 Introduction ................................................................................................................................................................ -
An Approach to Formalizing Ontology Driven Semantic Integration: Concepts, Dimensions and Framework Wenlong Gao
Florida State University Libraries Electronic Theses, Treatises and Dissertations The Graduate School 2012 An Approach to Formalizing Ontology Driven Semantic Integration: Concepts, Dimensions and Framework Wenlong Gao Follow this and additional works at the FSU Digital Library. For more information, please contact [email protected] THE FLORIDA STATE UNIVERSITY COLLEGE OF COMMUNICATION AND INFORMATION AN APPROACH TO FORMALIZING ONTOLOGY DRIVEN SEMANTIC INTEGRATION: CONCEPTS, DIMENSIONS AND FRAMEWORK By WENLONG GAO A Dissertation submitted to the School of Library and Information Studies In partial fulfillment of the requirements for the degree of Doctor of Philosophy Degree Awarded: Spring Semester, 2012 Wenlong Gao defended this dissertation on December 9, 2011 The members of the supervisory committee were: Corinne Jörgensen Professor Directing Dissertation Daniel Schwartz University Representative Ian Douglas Committee Member Besiki Stvilia Committee Member The Graduate School has verified and approved the above-named committee members and certifies that the dissertation has been approved in accordance with university requirements. ii For my parents, I could not have done this without you. iii ACKNOWLEDGEMENTS This dissertation could not have been completed without the tremendous support and help of my dissertation committee, friends and family. First, I would like to thank Dr. Corinne Jörgensen, my dissertation chair and mentor. You supported me through this entire process, and encouraged me whenever I encountered challenges. I will always appreciate the trust and confidence you placed in me. It has been an honor and privilege to be your doctoral student. Second, I am thankful for other committee members, Dr. Ian Douglas, Dr. Besiki Stvilia, Dr. Daniel Schwartz, who inspired me not only throughout the dissertation development but also though my personal academic development. -
Semantic Web and Peer-To-Peer Steffenstaab·Heinerstuckenschmidt(Eds.) Semantic Web and Peer-To-Peer
Semantic Web and Peer-to-Peer SteffenStaab·HeinerStuckenschmidt(Eds.) Semantic Web and Peer-to-Peer Decentralized Management and Exchange of Knowledge and Information With 89 Figures and 15 Tables 123 Editors Steffen Staab University of Koblenz Institute for Computer Science Universitaetsstr. 1 56016 Koblenz, Germany [email protected] Heiner Stuckenschmidt University of Mannheim Institute for Practical Computer Science A5, 6 68159 Mannheim, Germany [email protected] Library of Congress Control Number: 2005936055 ACM Computing Classification (1998): C.2.4, H.3, I.2.4 ISBN-10 3-540-28346-3 Springer Berlin Heidelberg New York ISBN-13 978-3-540-28346-1 Springer Berlin Heidelberg New York This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable for prosecution under the German Copyright Law. Springer is a part of Springer Science+Business Media springeronline.com © Springer-Verlag Berlin Heidelberg 2006 Printed in Germany The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant pro- tective laws and regulations and therefore free for general use.