2,827 research outputs found

    Supporting public decision making in policy deliberations: An ontological approach

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    This is the post-print version of the Paper. The official published version can be accessed from the link below - Copyright @ 2011 SpringerSupporting public decision making in policy deliberations has been a key objective of eParticipation which is an emerging area of eGovernment. EParticipation aims to enhance citizen involvement in public governance activities through the use of information and communication technologies. An innovative approach towards this objective is exploiting the potentials of semantic web technologies centred on conceptual knowledge models in the form of ontologies. Ontologies are generally defined as explicit human and computer shared views on the world of particular domains. In this paper, the potentials and benefits of using ontologies for policy deliberation processes are discussed. Previous work is then extended and synthesised to develop a deliberation ontology. The ontology aims to define the necessary semantics in order to structure and interrelate the stages and various activities of deliberation processes with legal information, participant stakeholders and their associated arguments. The practical implications of the proposed framework are illustrated.This work is funded by the European Commission under the 2006/1 eParticipation call

    A model for digital preservation repository risk relationships

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    The paper introduces the Preserved Object and Repository Risk Ontology (PORRO), a model that relates preservation functionality with associated risks and opportunities for their mitigation. Building on work undertaken in a range of EU and UK funded research projects (including the Digital Curation Centre , DigitalPreservationEurope and DELOS ), this ontology illustrates relationships between fundamental digital library goals and their parameters; associated rights and responsibilities; practical activities and resources involved in their accomplishment; and risks facing digital libraries and their collections. Its purpose is to facilitate a comprehensive understanding of risk causality and to illustrate opportunities for mitigation and avoidance. The ontology reflects evidence accumulated from a series of institutional audits and evaluations, including a specific subset of digital libraries in the DELOS project which led to the definition of a digital library preservation risk profile. Its applicability is intended to be widespread, and its coverage expected to evolve to reflect developments within the community. Attendees will gain an understanding of the model and learn how they can utilize this online resource to inform their own risk management activities

    Semantic Business Process Modeling

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    This book presents a process-oriented business modeling framework based on semantic technologies. The framework consists of modeling languages, methods, and tools that allow for semantic modeling of business motivation, business policies and rules, and business processes. Quality of the proposed modeling framework is evaluated based on the modeling content of SAP Solution Composer and several real-world business scenarios

    Consortium Proposal NFDI-MatWerk

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    This is the official proposal the NFDI-consortium NFDI-MatWerk submitted to the DFG within the request for funding the project. Visit www.dfg.de/nfdi for more infos on the German National Research Data Infrastructure (Nationale Forschungsdateninfrastruktur - NFDI) initiative. Visit www.nfdi-matwerk.de for last infos about the project NFDI-MatWerk

    Chemical information matters: an e-Research perspective on information and data sharing in the chemical sciences

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    Recently, a number of organisations have called for open access to scientific information and especially to the data obtained from publicly funded research, among which the Royal Society report and the European Commission press release are particularly notable. It has long been accepted that building research on the foundations laid by other scientists is both effective and efficient. Regrettably, some disciplines, chemistry being one, have been slow to recognise the value of sharing and have thus been reluctant to curate their data and information in preparation for exchanging it. The very significant increases in both the volume and the complexity of the datasets produced has encouraged the expansion of e-Research, and stimulated the development of methodologies for managing, organising, and analysing "big data". We review the evolution of cheminformatics, the amalgam of chemistry, computer science, and information technology, and assess the wider e-Science and e-Research perspective. Chemical information does matter, as do matters of communicating data and collaborating with data. For chemistry, unique identifiers, structure representations, and property descriptors are essential to the activities of sharing and exchange. Open science entails the sharing of more than mere facts: for example, the publication of negative outcomes can facilitate better understanding of which synthetic routes to choose, an aspiration of the Dial-a-Molecule Grand Challenge. The protagonists of open notebook science go even further and exchange their thoughts and plans. We consider the concepts of preservation, curation, provenance, discovery, and access in the context of the research lifecycle, and then focus on the role of metadata, particularly the ontologies on which the emerging chemical Semantic Web will depend. Among our conclusions, we present our choice of the "grand challenges" for the preservation and sharing of chemical information

    Forecasting the Spreading of Technologies in Research Communities

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    Technologies such as algorithms, applications and formats are an important part of the knowledge produced and reused in the research process. Typically, a technology is expected to originate in the context of a research area and then spread and contribute to several other fields. For example, Semantic Web technologies have been successfully adopted by a variety of fields, e.g., Information Retrieval, Human Computer Interaction, Biology, and many others. Unfortunately, the spreading of technologies across research areas may be a slow and inefficient process, since it is easy for researchers to be unaware of potentially relevant solutions produced by other research communities. In this paper, we hypothesise that it is possible to learn typical technology propagation patterns from historical data and to exploit this knowledge i) to anticipate where a technology may be adopted next and ii) to alert relevant stakeholders about emerging and relevant technologies in other fields. To do so, we propose the Technology-Topic Framework, a novel approach which uses a semantically enhanced technology-topic model to forecast the propagation of technologies to research areas. A formal evaluation of the approach on a set of technologies in the Semantic Web and Artificial Intelligence areas has produced excellent results, confirming the validity of our solution
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