BibSonomy publications for/user/iswc2007Proceedings of the Workshop on Privacy Enforcement and Accountability with Semantics (PEAS2007) at ISWC/ASWC2007, Busan, South Koreahttp://data.semanticweb.org/workshop/peas/2007/proceedingsNovemberAccess Control for Sharing Semantic Data across Desktops20072007accesscontroldatumdesktopiswcsemanticsharingworkshop_peasPersonal Information Management (PIM) systems aim to provide convenient access to all data and metadata on a desktop to the user itself as well as the co-workers. Obviously, sharing desktop data with co-workers raises privacy and access control issues which have to be addressed. In this paper we discuss these issues, and present appropriate solutions. In line with the architecture of current PIM systems, our solutions cover all semantic data shared in such a context, i.e. all desktop resources as well as other data structures created by the system, such as metadata in an RDF store and inverted index entries created for efficient textual search. We discuss different kinds of policies to specify protection for desktop data and metadata, and describe our access control system to express and execute these policies efficiently. Additionally, we describe the extension of an existing PIM system, Beagle++, with our approach, as well as our experiments, with convincing results on performance and scalability.Proceedings of the Workshop on Privacy Enforcement and Accountability with Semantics (PEAS2007) at ISWC/ASWC2007, Busan, South Koreahttp://data.semanticweb.org/workshop/peas/2007/proceedingsNovemberSemantic-Driven Enforcement of Rights Delegation Policies via the Combination of Rules and Ontologies20072007combinationdelegationenforcementiswcontologypolicyrightruleworkshop_peasWe show that the semantic formal model for Open Digital Right Language (ODRL)-based rights delegation policies can be enforced and expressed as a combination of ontologies and rules, e.g., Semantic Web Rule Language (SWRL). Based on ODRL's expressions and data dictionary, a rights delegation ontology is proposed in this study. Furthermore, we express the rights delegation policy as a set of ontology statements, rules, and facts for usage and transfer rights delegation. When verifying ODRL formal semantics, our SWRL approach is superior to the generic restricted First Order Logic (FOL) model because we have an understandable formal semantics of policies for automatic machine processing and a higher expressive power for policy compliance checking. On the other hand, the rights delegation semantics shown as a generic full FOL might have a higher complexity of license verification, which results in a policy compliance checking that is possibly undecidable. A real usage rights delegation scenario for digital content is demonstrated in order to justify the feasibility of our formal semantic model for digital rights delegation. We hope this study will shed some light on future sensitive information usage and delegation rights controlled from a privacy protection perspective.Proceedings of the Workshop on Privacy Enforcement and Accountability with Semantics (PEAS2007) at ISWC/ASWC2007, Busan, South Koreahttp://data.semanticweb.org/workshop/peas/2007/proceedingsNovemberPrivacy Enforcement in Data Analysis Workflows20072007analysisdatumenforcementiswcprivacyworkflowworkshop_peasCollaborative e-Science projects commonly require data analysis to be performed on distributed data sets which may contain sensitive information. In addition to the credential-based privacy protection, ensuring proper handling of computerized data for disclosure and analysis is particularly essential in e-Science. In this paper, we propose a semantic approach for enforcing it through workflow systems. We define privacy preservation and analysis-relevant terms as ontologies and incorporate them into a proposed policy framework to represent and enforce the policies. We believe that workflow systems with the proposed privacy-awareness incorporated could ease the scientists in setting up privacy polices that suit for different types of collaborative research projects and can help them in safeguarding the privacy of sensitive data throughout the data analysis lifecycle.Proceedings of the Workshop on Privacy Enforcement and Accountability with Semantics (PEAS2007) at ISWC/ASWC2007, Busan, South Koreahttp://data.semanticweb.org/workshop/peas/2007/proceedingsNovemberPrivacy and Capability Management for the European eIDM Framework20072007capabilityeuropeanframeworkiswcmanagementprivacyworkshop_peasThe natural evolution of eGovernment is to go beyond the management of identities and therefore it is necessary to manage people, companies or organizations, and their capabilities to interact with Public Administrations. When developing an application based on an eID management system, this management issue must be tackled within each application (i.e. demonstrate the capability of one person to act, demonstrate the economical reliability, demonstrate his professional status, etc ...) and is normally based on the local jurisdiction. The objective of the present paper is to introduce a distributed system for the privacy-enhanced management of the capabilities associated to a person within the EU framework, independently from the origin and destination EU member state. The core of this system is the intelligence of the Capabilities Resolution Nodes (CRN) to cope with the complexity of the capability resolution and the capability sources discovery in the pan-European scenario. A European Capacity Resolution Network will be able to grow up the interoperability of the digital identities provided and valid in each member state and will answer the question “is this person, identified with this digital identity and who is described by those attributes, allowed to carry out this legal act in this country according to its law?”.Proceedings of the Workshop on Privacy Enforcement and Accountability with Semantics (PEAS2007) at ISWC/ASWC2007, Busan, South Koreahttp://data.semanticweb.org/workshop/peas/2007/proceedingsNovemberRecommendation Privacy Protection in Trust-based Knowledge Sharing Network20072007iswcknowledgenetworkprivacyprotectionrecommendationsharingworkshop_peasTrust can be applied to knowledge sharing on a distributed network of knowledge source agents. Each agent represents a person who trusts some other agents. Based on these trust-relationships, an agent can infer the trustworthiness of an unknown agent by asking trusted agents for recommendations. However, the person represented by an agent may not be willing to share his or her individual opinion about the trustwor-thiness of a particular agent to agents that do not protect information privacy. A solution for this issue is proposed using three kinds of privacy policies: generosity, caution, and non-cooperation. An agent that adopts the caution policy towards another agent will hide the details of the trust recommendation path. An analysis shows the effect of the privacy policies on the calculated reliabilities of the recommended trust values.Proceedings of the Workshop on Privacy Enforcement and Accountability with Semantics (PEAS2007) at ISWC/ASWC2007, Busan, South Koreahttp://data.semanticweb.org/workshop/peas/2007/proceedingsNovemberLogging in Distributed Workflows20072007iswcloggingworkflowworkshop_peasBusiness needs are nowadays frequently realized by business workflows spanning multiple organizations. Current infrastructures, such as SOA, support this trend on the implementation side. As a side effect these issues of privacy and data protection arise, because data is shipped across organizational boundaries. At the same time increased awareness about protection of privacy and IPR have lead to comprehensive contractual and legal constructs - including the information of services consumers about the ways their data is handled. We propose to solve such information requests in widely distributed workflow executions by gathering the related information during the execution and attaching it directly to the processed data. Together with the data this information is passed through the workflow and at the end it is returned to the service consumer.Proceedings of the Workshop on Privacy Enforcement and Accountability with Semantics (PEAS2007) at ISWC/ASWC2007, Busan, South KoreaNovemberProceedings of the Workshop on Privacy Enforcement and Accountability with Semantics (PEAS2007) at ISWC/ASWC2007, Busan, South Korea20072007iswcworkshop_peasProceedings of the Workshop on Ontology Matching (OM2007) at ISWC/ASWC2007, Busan, South Koreahttp://data.semanticweb.org/workshop/om/2007/proceedingsNovemberOntology Mapping - A User Survey20072007iswcmappingontologysurveyuserworkshop_omOntology mapping is the key to data interoperability in the semantic web vision. Computing mappings is the first step to applications such as query rewriting, instance sharing, web-service integration, and ontology merging. This problem has received a lot of attention in recent years, but little is known about how users actually construct mappings. Several ontology-mapping tools have been developed, but which tools do users actually use? What processes are users following to discover, track, and compute mappings? How do teams coordinate when performing mappings? In this paper, we discuss the results from an online user survey where we gathered feedback from the community to help answer these important questions. We discuss the results from the survey and the implications they may have on the mapping research community.Proceedings of the Workshop on Ontology Matching (OM2007) at ISWC/ASWC2007, Busan, South Koreahttp://data.semanticweb.org/workshop/om/2007/proceedingsNovemberFinding Semantic Similarity in a Biological Domain: A Human-Centered Approach20072007approachfindingiswcsemanticsimilarityworkshop_omA behavioral study investigated how college students judge similarity between cell pictures. The study indicates that there is a strong tendency to rely on class-inclusion relations in judgments of similarity. This means that biological concepts are likely to be organized and conceptualized with respect to class-inclusion relations even for non-experts.Proceedings of the Workshop on Ontology Matching (OM2007) at ISWC/ASWC2007, Busan, South Koreahttp://data.semanticweb.org/workshop/om/2007/proceedingsNovemberEvaluating a confidence value for ontology alignment20072007alignmentconfidenceiswcontologyvalueworkshop_omMany methods for automatic and semi-automatic ontology alignment have been proposed, but they remain error prone and labor-intensive. This paper describes a novel generic process for evaluating the mappings' confidence value. This process uses rules extracted through inductive machine learning methods from the matching results proposed by others. Further, the precision and recall of the extracted rules are exploited in order to transform each rule into a mathematical formula that generates the mappings' confidence value. Mappings are then classified not as valid or invalid but through a quantitative confidence value that can be easily managed during the alignment process.