Several proposals have been put forward to support distributed agent cooperation in the Semantic Web, by allowing concepts and roles in one ontology be reused in another ontology. In general, these proposals reduce the autonomy of each ontology by defining the semantics of the ontology to depend on the semantics of the other ontologies.
We propose a new framework for managing autonomy in a set of cooperating ontologies (or ontology space). In this framework, each language entity (concept/role/individual) in an ontology may have its meaning assigned either locally with respect to the semantics of its own ontology, to preserve the autonomy of the ontology, or globally with respect to the semantics of any neighbouring ontology in which it is defined, thus enabling semantic cooperation between multiple ontologies.
In this way, each ontology has a \"subjective semantics\" based on local interpretation and a \"foreign semantics\" based on semantic binding to neighbouring ontologies. We study the properties of these two semantics and describe the conditions under which entailment and satisfiability are preserved. We also introduce two reasoning mechanisms under this framework: \"cautious reasoning\" and \"brave reasoning\". Cautious reasoning is done with respect to a local ontology and its neighbours (those ontologies in which its entities are defined); brave reasoning is done with respect to the transitive closure of this relationship. This framework is independent of ontology languages. As a case study, for Description Logic ALCN we present two tableau-based algorithms for performing each form of reasonings and prove their correctness.
", "label" : "Semantic Cooperation and Knowledge Reuse by Using Autonomous Ontologies", "student-paper" : "No" }, { "track" : "Research track", "paper-id" : "248", "author" : [ "Andreas Harth", "Juergen Umbrich", "Aidan Hogan", "Stefan Decker" ], "type" : "Paper", "subject" : [ "Applications of the Semantic Web technologies", "Information integration", "Agents and Services for the Semantic Web", "Semantics in peer to peer systems and grids", "Database technologies for the Semantic Web", "Management of the Semantic Web data" ], "abstract" : "We present the architecture of an end to end semantic search engine that uses a graph data model to enable interactive query answering over structured and interlinked data collected from many disparate sources on the Web. In particular, we study distributed indexing methods for graph structured data and parallel query evaluation methods on a cluster of computers. We evaluate the system on a dataset with 430 million statements collected from the Web, and provide scale up experiments on 7 billion synthetically generated statements.", "label" : "YARS2: A Federated Repository for Querying Graph Structured Data from the Web", "student-paper" : "Yes" }, { "track" : "Research track", "paper-id" : "272", "author" : [ "Mianwei Zhou", "Shenghua Bao", "Xian Wu", "Yong Yu" ], "type" : "Paper", "subject" : [ "Social networks and processes on the Semantic Web", "Ontology creation, search, extraction and evolution", "Management of the Semantic Web data", "Semantic Web content creation, annotation, and extraction" ], "abstract" : "This paper deals with the problem of exploring hierarchical semantics from social annotations. Recently, social annotation services have become more and more popular in Semantic Web. It allows users to arbitrarily annotate web resources, thus, largely lowers the barrier to cooperation. Furthermore, through providing abundant meta-data resources, social annotation might become a key to the development of Semantic Web. However, on the other hand, social annotation has its own apparent limitations, for instance, 1) ambiguity and synonym phenomena and 2) lack of hierarchical information. In this paper, we propose an unsupervised model to automatically derive hierarchical semantics from social annotations. Using a social bookmark service Del.icio.us as example, we demonstrate that the derived hierarchical semantics has the ability to compensate those shortcomings. We further apply our model on another data set from Flickr to testify our model's applicability on different environments. The experimental results demonstrate our model's effciency.", "label" : "An Unsupervised Model for Exploring Hierarchical Semantics from Social Annotations", "student-paper" : "Yes" }, { "track" : "Research track", "paper-id" : "87", "author" : [ "Qi Zhou", "Chong Wang", "Miao Xiong", "Haofen Wang", "Yong Yu" ], "type" : "Paper", "subject" : [ "Applications of the Semantic Web technologies", "Ontology creation, search, extraction and evolution" ], "abstract" : "Semantic search promises to provide more accurate result than present-day keyword search. However, progress with semantic search has been delayed due to the complexity of its query languages. In this paper, we explore a novel approach of adapting keywords to querying the semantic web: the approach automatically translates keyword queries into formal logic queries so that end users can use familiar keywords to perform semantic search. A prototype system named ‘SPARK’ has been implemented in light of this approach. Given a keyword query, SPARK outputs a ranked list of SPARQL queries as the translation result. The translation in SPARK consists of three major steps: term mapping, query graph construction and query ranking. Specifically, a probabilistic query ranking model is proposed to select the most likely SPARQL query. In the experiment, SPARK achieved an encouraging translation result.", "label" : "SPARK: Adapting Keyword Query to Semantic Search", "student-paper" : "Yes" }, { "label" : "Grit Denker", "email" : "Grit.Denker@sri.com", "type" : "Person", "affiliation" : "SRI International" }, { "label" : "Valentina Ceausu", "email" : "ceausu@math-info.univ-paris5.fr", "type" : "Person", "affiliation" : "Paris V University" }, { "label" : "Alfio Gliozzo", "email" : "gliozzo@gmail.com", "type" : "Person", "affiliation" : "CNR-ISTC" }, { "label" : "John Darlington", "email" : "jd@ecs.soton.ac.uk", "type" : "Person" }, { "label" : "Dave Kolas", "email" : "dkolas@bbn.com", "type" : "Person", "affiliation" : "BBN Technologies" }, { "label" : "Xiongzhi Zhou", "email" : "zhouxiongzhi@taikanglife.com", "type" : "Person", "affiliation" : "Taikang Life Insurance Company" }, { "label" : "Yang Yang", "email" : "yangyy@cn.ibm.com", "type" : "Person", "affiliation" : "IBM China Research Laboratory" }, { "label" : "Chintan Patel", "email" : "chintan.patel@dbmi.columbia.edu", "type" : "Person", "affiliation" : "Columbia University Medical Center" }, { "label" : "Tom Heath", "email" : "t.heath@open.ac.uk", "type" : "Person", "affiliation" : "KMi, The Open University, UK" }, { "label" : "David Martin", "email" : "martin@ai.sri.com", "type" : "Person", "affiliation" : "SRI International" }, { "label" : "James Ressler", "email" : "james.ressler@ngc.com", "type" : "Person", "affiliation" : "Northrop Grumman" }, { "label" : "Edward Benson", "email" : "ebenson@bbn.com", "type" : "Person", "affiliation" : "BBN Technologies" }, { "label" : "Carol Tullo", "email" : "carol.tullo@opsi.x.gsi.gov.uk", "type" : "Person" }, { "label" : "Chris Bizer", "email" : "chris@bizer.de", "type" : "Person", "affiliation" : "Freie Universit\u00E4t Berlin" }, { "label" : "Osma Suominen", "email" : "osma.suominen@tkk.fi", "type" : "Person", "affiliation" : "Helsinki University of Technology TKK, Finland" }, { "label" : "Reginald Ford", "email" : "reginald.ford@sri.com", "type" : "Person", "affiliation" : "SRI International" }, { "label" : "Chuck Morris", "email" : "chuck.morris@ngc.com", "type" : "Person", "affiliation" : "Northrop Grumman" }, { "label" : "Jens Lehmann", "email" : "lehmann@informatik.uni-leipzig.de", "type" : "Person", "affiliation" : "Universit\u00E4t Leipzig" }, { "label" : "Guotong Xie", "email" : "xieguot@cn.ibm.com", "type" : "Person", "affiliation" : "IBM China Research Laboratory" }, { "label" : "Kavitha Srinivas", "email" : "ksrinivs@us.ibm.com", "type" : "Person" }, { "label" : "Troy Self", "email" : "tself@bbn.com", "type" : "Person", "affiliation" : "BBN Technologies" }, { "label" : "John Domingue", "email" : "J.B.Domingue@open.ac.uk", "type" : "Person", "affiliation" : "KMi, The Open University, UK" }, { "label" : "Richard Cyganiak", "email" : "richard@cyganiak.de", "type" : "Person", "affiliation" : "Freie Universit\u00E4t Berlin" }, { "label" : "Mark Johnson", "email" : "mark.johnson@sri.com", "type" : "Person", "affiliation" : "SRI International" }, { "label" : "James Cimino", "email" : "ciminoj@dbmi.columbia.edu", "type" : "Person", "affiliation" : "Columbia University Medical Center" }, { "label" : "Aldo Gangemi", "email" : "aldo.gangemi@istc.cnr.it", "type" : "Person", "affiliation" : "CNR-ISTC" }, { "label" : "David Dupplaw", "email" : "dpd@ecs.soton.ac.uk", "type" : "Person" }, { "label" : "Knud M\u00F6ller", "email" : "knud.moeller@deri.org", "type" : "Person", "affiliation" : "DERI, NUI Galway" }, { "label" : "Kim Viljanen", "email" : "kim.viljanen@tkk.fi", "type" : "Person", "affiliation" : "Helsinki University of Technology TKK, Finland" }, { "label" : "Nigel Shadbolt", "email" : "nrs@ecs.soton.ac.uk", "type" : "Person", "affiliation" : "University of Southampton" }, { "label" : "Sylvie Despr\u00E8s", "email" : "sd@math-info.univ-paris5.fr", "type" : "Person", "affiliation" : "Paris V University" }, { "label" : "Diana Maynard", "email" : "diana@dcs.shef.ac.uk", "type" : "Person", "affiliation" : "University of Sheffield, UK" }, { "label" : "Shengping Liu", "email" : "liusp@cn.ibm.com", "type" : "Person", "affiliation" : "IBM China Research Laboratory" }, { "label" : "Valentina Presutti", "email" : "valentina.presutti@istc.cnr.it", "type" : "Person", "affiliation" : "CNR-ISTC" }, { "label" : "Horacio Saggion", "email" : "saggion@dcs.shef.ac.uk", "type" : "Person", "affiliation" : "University of Sheffield, UK" }, { "label" : "Eero Hyvnen", "email" : "eero.hyvonen@tkk.fi", "type" : "Person", "affiliation" : "Helsinki University of Technology TKK, Finland" }, { "label" : "Zhaoming Qiu", "email" : "qiuzhaom@cn.ibm.com", "type" : "Person", "affiliation" : "IBM China Research Laboratory" }, { "label" : "S\u00F6ren Auer", "email" : "auer@seas.upenn.edu", "type" : "Person", "affiliation" : "University of Pennsylvania" }, { "label" : "Georgi Kobilarov", "email" : "gkob@gmx.de", "type" : "Person", "affiliation" : "Freie Universit\u00E4t Berlin" }, { "label" : "Edith Schonberg", "email" : "ediths@us.ibm.com", "type" : "Person", "affiliation" : "IBM Watson Research Center" }, { "label" : "John Sheridan", "email" : "john.sheridan@opsi.x.gsi.gov.uk", "type" : "Person" }, { "label" : "Mike Dean", "email" : "mdean@bbn.com", "type" : "Person", "affiliation" : "BBN Technologies" }, { "label" : "Daniel Elenius", "email" : "elenius@csl.sri.com", "type" : "Person", "affiliation" : "SRI International" }, { "label" : "Kieron O\'Hara", "email" : "kmo@ecs.soton.ac.uk", "type" : "Person" }, { "label" : "Harith Alani", "email" : "ha@ecs.soton.ac.uk", "type" : "Person", "affiliation" : "University of Southampton" }, { "label" : "Zachary Ives", "email" : "zives@cis.upenn.edu", "type" : "Person", "affiliation" : "University of Pennsylvania" }, { "label" : "Eric Dorner", "email" : "eric.dorner@ngc.com", "type" : "Person", "affiliation" : "Northrop Grumman" }, { "track" : "Semantic Web in Use track", "paper-id" : "253", "author" : [ "Aldo Gangemi", "Alfio Gliozzo", "Valentina Presutti" ], "type" : "Paper", "subject" : [ "Application", "Tool", "Framework", "Ontology", "Industry: Public Sector" ], "abstract" : "This paper introduces a framework to add a semantic web layer to legacy organizational information, and describes its application to the use case provided by the Italian National Research Council (CNR) intraweb. \nBuilding on a traditional web-based view of information from different legacy databases, we have performed a semantic porting of data into a knowledge base, dependent on an OWL domain ontology. We have enriched the knowledge base by means of text mining techniques, in order to discover on-topic relations. Several reasoning techniques have been applied, in order to infer relevant implicit relationships. \nFinally, the ontology and the knowledge base have been deployed on a semantic wiki by means of the WikiFactory tool, which allows users to browse the ontology and the knowledge base, to introduce new relations, to revise wrong assertions in a collaborative way, and to perform semantic queries. \nIn our experiments, we have been able to easily implement several functionalities, such as expert finding, by simply formulating ad-hoc queries from either an ontology editor or the semantic wiki interface. The result is an intelligent and collaborative front end, which allow users to add information, fill gaps, or revise existing information on a semantic basis, while keeping the knowledge base automatically updated.", "label" : "A Collaborative Semantic Web Layer to Enhance Legacy Systems" }, { "track" : "Semantic Web in Use track", "paper-id" : "232", "author" : [ "Daniel Elenius", "Mark Johnson", "Reginald Ford", "Grit Denker", "David Martin" ], "type" : "Paper", "subject" : [ "Application", "Tool", "Problem Statement", "Ontology" ], "abstract" : "We describe a novel approach by which software can assess the ability of a confederation of heterogeneous systems to interoperate to achieve a given purpose. The approach uses ontologies and knowledge bases (KBs) to capture the salient characteristics of systems, on the one hand, and of tasks for which these systems will be employed, \non the other. Rules are used to represent the conditions under which \nthe capabilities provided by systems can ful\uFB01ll the capabilities needed to \nsupport the roles and interactions that make up each task. An Analyzer \ncomponent employs these KBs and rules to determine if a given con- \nfederation will be adequate, to generate suitable confederations from a collection of available systems, to pre-diagnose potential interoperability problems that might arise, and to suggest system con\uFB01guration options that will help to make interoperability possible. We have demonstrated the feasibility of this approach using a prototype Analyzer and KBs. \n \nNote: Approval of this paper by the Government client is pending. If \napproval is not forthcoming, it must be withdrawn.", "label" : "Purpose-Aware Reasoning about Interoperability of Heterogeneous Training Systems" }, { "track" : "Semantic Web in Use track", "paper-id" : "222", "author" : [ "S\u00F6ren Auer", "Chris Bizer", "Jens Lehmann", "Georgi Kobilarov", "Richard Cyganiak", "Zachary Ives" ], "type" : "Paper", "subject" : [ "Application", "Tool", "Framework", "Ontology" ], "abstract" : "DBpedia is a community effort to extract structured information from Wikipedia and to make this information available on the Web. DBpedia allows you to ask sophisticated queries against datasets derived from Wikipedia and to link other datasets on the Web to Wikipedia data. We describe the extraction of the DBpedia datasets, and how the resulting information can be made available on the Web for humans and machines. We describe some emerging applications from the DBpedia community and show how website operators can reduce costs by facilitating royalty-free DBpedia content within their sites. Finally, we present the current status of interlinking DBpedia with other open datasets on the Web and outline how DBpedia could serve as a nucleus for an emerging Web of open data sources.", "label" : "DBpedia: A Nucleus for a Web of Open Data" }, { "track" : "Semantic Web in Use track", "paper-id" : "195", "author" : [ "Kavitha Srinivas", "Chintan Patel", "James Cimino", "Li Ma", "Julian Dolby", "Achille Fokoue", "Aditya Kalyanpur", "Aaron Kershenbaum", "Edith Schonberg" ], "type" : "Paper", "subject" : [ "Ontology", "Industry: Pharmaceuticals / Health" ], "abstract" : "This paper describes a large case study that explores the applicability of ontology reasoning to problems in the medical domain. We investigate whether it is possible to use such reasoning to automate common clinical tasks that are currently labor intensive and error prone, and focus our case study on improving cohort selection for clinical trials. An obstacle to automating such clinical tasks is the need to bridge the semantic gulf between raw patient data, such as laboratory tests or specific medications, and the way a clinician interprets this data. Our key insight is that matching patients to clinical trials can be formulated as a problem of semantic retrieval. We describe the technical challenges to building a realistic case study, which include problems related to scalability, the integration of large ontologies, and dealing with noisy, inconsistent data. Our solution is based on the SNOMED CT ontology, and scales to one year of patient records (approx. 240,000 patients).", "label" : "Matching Patient Records to Clinical Trials Using Ontologies" }, { "track" : "Semantic Web in Use track", "paper-id" : "188", "author" : [ "Harith Alani", "David Dupplaw", "John Sheridan", "Kieron O\'Hara", "John Darlington", "Nigel Shadbolt", "Carol Tullo" ], "type" : "Paper", "subject" : [ "None of the above", "Industry: Public Sector" ], "abstract" : "Governments often hold very rich data and whilst much of this information is published and available for re-use by others, it is often trapped by poor data structures, locked up in legacy data formats or in fragmented databases. One of the great benefits that Semantic Web (SW) technology offers is facilitating the large scale integration and sharing of distributed data sources. At the heart of information policy in the UK, the Office of Public Sector Information (OPSI) is the part of the UK government charged with enabling the greater re-use of public sector information. This paper described the actions, findings, and lessons learnt from a pilot study, involving several parts of government and the public \nsector. The aim was to show to government how they can adopt SW \ntechnology for the dissemination, sharing and use of its data.", "label" : "Unlocking the Potential of Public Sector Information with Semantic Web Technology" }, { "track" : "Semantic Web in Use track", "paper-id" : "165", "author" : [ "Dave Kolas", "Troy Self" ], "type" : "Paper", "subject" : [ "Framework", "Industry: Other" ], "abstract" : "As an increasing number of applications on the web contain some elements of spatial data, there is a need to efficiently integrate Semantic Web technologies and spatial data processing. This paper describes a prototype system for storing spatial data and Semantic Web data together in a SPatially-AUgmented Knowledgebase (SPAUK) without sacrificing query efficiency. The goals are motivated through use several use cases. The prototype\u2019s design and architec-ture are described, and resulting performance improvements are discussed.", "label" : "Spatially Augmented Knowledgebase" }, { "track" : "Semantic Web in Use track", "paper-id" : "89", "author" : [ "James Ressler", "Mike Dean", "Edward Benson", "Eric Dorner", "Chuck Morris" ], "type" : "Paper", "subject" : [ "Application", "Ontology" ], "abstract" : "An ontology provides a precise specification of the vocabulary used by a community of interest (COI). Multiple communities of interest may describe the same concept using the same or different terms. When such communities interact, ontology alignment and translation is required. This is typically a time consuming process. This paper describes Snoggle, an open source tool designed to ease development of ontology translation rules, and discusses its application to geospatial ontologies.", "label" : "Application of Ontology Translation" }, { "track" : "Semantic Web in Use track", "paper-id" : "81", "author" : [ "Valentina Ceausu", "Sylvie Despr\u00E8s" ], "type" : "Paper", "subject" : [ "Application", "Tool", "Framework", "Ontology", "Industry: Transport / Logistics" ], "abstract" : "This paper presents a semantic case-based reasoning framework for text categorization. Text categorization is the task of classifying text documents under predened categories. \n Accidentology is our application eld and the goal of our framework \nis to classify documents describing real road accidents under predened \nroad accident prototpypes, which also are described by text documents. \nAccidents are described by accident reports while accident prototypes \nare described by accident scenarios. Thus, text categorization is done by \nassigning each accident report to an accident scenario, which highlights \nparticular mechanisms leading to accident. \n We propose a textual case based reasoning approach (TCBR), which \nallows us to integrate both textual and domain knowledge aspects in \norder to carry out this categorization. CBR solves a new problem (target case) by identifying its similarity to one or several previously solved problems (source cases) stored in a case base and by adapting their known solutions. Cases of our framework are created from text. Most of TCBR applications create cases from text by using Information Retrieval techniques, which leads to knowledge-poor descriptions of cases. \nWe show that using semantic resources (two ontology of accidentology) \nmakes possible to overcome this diculty, and allows us to enrich cases by using formal knowledge. \n In this paper, we argue that semantic resources are likely to improve the quality of cases created from text, and, therefore, such resources can support the reasoning cycle. We illustrate this claim with our framework developed to classify documents in the accidentology domain.", "label" : "A semantic case-based reasoning framework for text categorization" }, { "track" : "Semantic Web in Use track", "paper-id" : "228", "author" : [ "Knud M\u00F6ller", "Tom Heath", "Siegfried Handschuh", "John Domingue" ], "type" : "Paper", "subject" : [ "Application", "Ontology" ], "abstract" : "Semantic Web conferences such as ESWC and ISWC offer prime opportunities to test and showcase semantic technologies. Conference metadata about people, papers and talks is diverse in nature and neither too small to be uninteresting or too big to be unmanageable. Many metadata-related challenges that may arise in the Semantic Web at large are also present here. Metadata must be generated from sources which are often unstructured and hard to process, and may originate from many different players, therefore suitable workflows must be established. Moreover, the generated metadata must use appropriate formats and vocabularies, and be served in a way that is consistent with the principles of linked data. This paper reports on the metadata efforts from ESWC and ISWC, identifies specific issues and barriers encountered during the projects, and discusses how these were approached. Recommendations are made as to how these may be addressed in the future, and we discuss how these solutions may generalize to metadata production for the Semantic Web at large.", "label" : "Recipes for Semantic Web Dog Food - The ESWC and ISWC Metadata Projects" }, { "track" : "Semantic Web in Use track", "paper-id" : "158", "author" : [ "Guotong Xie", "Yang Yang", "Shengping Liu", "Zhaoming Qiu", "Yue Pan", "Xiongzhi Zhou" ], "type" : "Paper", "subject" : [ "Application", "Tool", "Ontology", "Industry: Banking / Finance" ], "abstract" : "Data warehouse is now widely used in business analysis and decision making processes. To adapt the rapidly changing business environment, we develop a tool to make data warehouses more business-friendly by using Semantic Web technologies. The main idea is to make business semantics explicit by uniformly representing the business metadata (i.e. conceptual enterprise data model and multidimensional model) with an extended OWL language. Then a mapping from the business metadata to the schema of the data warehouse is built. When an analysis request is raised, a customized data mart with data populated from the data warehouse can be automatically generated with the help of this built-in knowledge. This tool, called Enterprise Information Asset Workbench (EIAW), is deployed at the Taikang Life Insurance Company, one of the top five insurance companies of China. User feedback shows that OWL provides an excellent basis for the representation of business semantics in data warehouse, but many necessary extensions are also needed in the real application. The user also deemed this tool very helpful because of its flexibility and speeding up data mart deployment in face of business changes.", "label" : "EIAW: Towards a Business-friendly Data Warehouse Using Semantic Web Technologies" }, { "track" : "Semantic Web in Use track", "paper-id" : "217", "author" : [ "Horacio Saggion", "Kalina Bontcheva", "Adam Funk", "Diana Maynard" ], "type" : "Paper", "subject" : [ "Application", "Tool", "Ontology", "Industry: Banking / Finance" ], "abstract" : "Business Intelligence (BI) requires the acquisition and aggregation of \nkey pieces of knowledge from multiple sources in order to provide \nvaluable information to customers or feed statistical BI models and tools. \n The massive amount of information available \nto business analysts makes information extraction and other natural \nlanguage processing tools key enablers \nfor the acquisition and use of that semantic information. \nWe describe the application of \nontology-based extraction and merging in the context of a \npractical e-business application for the EU \nMUSING Project where the goal is to gather international company intelligence and country/region information. \nThe results of our experiments so far are very promising and we are now in the process of bulding a complete end-to-end solution.", "label" : "Ontology-based Information Extraction for Business Applications" }, { "track" : "Semantic Web in Use track", "paper-id" : "35", "author" : [ "Eero Hyvnen", "Kim Viljanen", "Osma Suominen" ], "type" : "Paper", "subject" : [ "Application", "Framework", "Ontology", "Industry: Public Sector" ], "abstract" : "This paper shows how semantic web techniques can be applied to solving problems of distributed content creation, discovery, linking, aggregation, and reuse in health information portals, both from end-user\u2019s and content publishers\u2019s viewpoints. As a case study, the national semantic health portal HEALTHFINLAND is presented. It provides citizens with intelligent searching and browsing services to reliable and up-to-date health information created by various health organizations in Finland. The system is based on a shared semantic metadata schema, ontologies, and mash-up ontology services. The content includes metadata of thousands of web documents such as web pages, articles, reports, campaign information, news, services, and other information related to health.", "label" : "HealthFinland - Finnish Health Information on the SemanticWeb" } ], "types" : { "Person" : { pluralLabel: "People" }, "Paper" : { pluralLabel: "Papers" } }, "properties" : { "author" : { "valueType" : "item" } } }