323,190 research outputs found

    Bechhofer, S.

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    myExperiment: An ontology for e-Research

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    myExperiment describes itself as a "Social Virtual Research Environment" that provides the ability to share Research Objects (ROs) over a social infrastructure to facilitate actioning of research. The myExperiment Ontology is a logical representation of the data model used by this environment, allowing its data to be published in a standard RDF format, whilst providing a generic extensible framework that can be reused by similar projects. ROs are data structures designed to semantically enhance research publications by capturing and preserving the research method so that it can be reproduced in the future. This paper provides some motivation for an RO specification and briefly considers how existing domain-specifific ontologies might be integrated. It concludes by discussing the future direction of the myExperiment Ontology and how it will best support these ROs

    Conceptual Linking: Ontology-based Open Hypermedia

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    This paper describes the attempts of the COHSE project to define and deploy a Conceptual Open Hypermedia Service. Consisting of • an ontological reasoning service which is used to represent a sophisticated conceptual model of document terms and their relationships; • a Web-based open hypermedia link service that can offer a range of different link-providing facilities in a scalable and non-intrusive fashion; and integrated to form a conceptual hypermedia system to enable documents to be linked via metadata describing their contents and hence to improve the consistency and breadth of linking of WWW documents at retrieval time (as readers browse the documents) and authoring time (as authors create the documents)

    Scientific Social Objects: The Social Objects and Multidimensional Network of the myExperiment Website

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    Scientific research is increasingly conducted digitally and online, and consequently we are seeing the emergence of new digital objects shared as part of the conduct and discourse of science. These Scientific Social Objects are more than lumps of domain-specific data: they may comprise multiple components which can also be shared separately and independently, and some contain descriptions of scientific processes from which new objects will be generated. Using the myExperiment social website as a case study we explore Scientific Social Objects and discuss their evolution

    Managing semantic Grid metadata in S-OGSA

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    Grid resources such as data, services, and equipment, are increasingly being annotated with descriptive metadata that facilitates their discovery and their use in the context of Virtual Organizations (VO). Making such growing body of metadata explicit and available to Grid services is key to the success of the VO paradigm. In this paper we present a model and management architecture for Semantic Bindings, i.e., firstclass Grid entities that encapsulate metadata on the Grid and make it available through predictable access patterns. The model is at the core of the S-OGSA reference architecture for the Semantic Grid

    A Linked Data Approach to Sharing Workflows and Workflow Results

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    A bioinformatics analysis pipeline is often highly elaborate, due to the inherent complexity of biological systems and the variety and size of datasets. A digital equivalent of the ‘Materials and Methods’ section in wet laboratory publications would be highly beneficial to bioinformatics, for evaluating evidence and examining data across related experiments, while introducing the potential to find associated resources and integrate them as data and services. We present initial steps towards preserving bioinformatics ‘materials and methods’ by exploiting the workflow paradigm for capturing the design of a data analysis pipeline, and RDF to link the workflow, its component services, run-time provenance, and a personalized biological interpretation of the results. An example shows the reproduction of the unique graph of an analysis procedure, its results, provenance, and personal interpretation of a text mining experiment. It links data from Taverna, myExperiment.org, BioCatalogue.org, and ConceptWiki.org. The approach is relatively ‘light-weight’ and unobtrusive to bioinformatics users

    Research Objects: Towards Exchange and Reuse of Digital Knowledge

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    What will researchers be publishing in the future? Whilst there is little question that the Web will be the publication platform, as scholars move away from paper towards digital content, there is a need for mechanisms that support the production of self-contained units of knowledge and facilitate the publication, sharing and reuse of such entities. In this paper we discuss the notion of research objects, semantically rich aggregations of resources, that possess some scientific intent or support some research objective. We present a number of principles that we expect such objects and their associated services to follow

    Why linked data is not enough for scientists

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    Simply publishing linked data into the cloud does not necessarily meet the requirements of reuse. Scientific data stands to represent a significant portion of the linked open data cloud and science itself stands to benefit from the data fusion capability that this will afford. However, simply publishing linked data into the cloud does not necessarily meet the requirements of reuse. Publishing has requirements of provenance, quality, credit, attribution, methods in order to provide the reproducibility that allows validation of results. In this paper we make the case for a scientific data publication model on top of linked data and introduce the notion of Research Objects as first class citizens for sharing and publishing. Citation: Bechhofer, S., Ainsworth, J., Bhagat, J., Buchan, I., Couch, P., Cruickshank, D., Delderfield, M., Dunlop, I., Gamble, M., Goble, C., Michaelides, D., Missier, P., Owen, S., Newman, D., De Roure, D. and Sufi, S. (2010) Why Linked Data is Not Enough for Scientists. In: Sixth IEEE e–Science conference (e-Science 2010), December 2010, Brisbane, Australia. (Submitted) &nbsp

    Diffusive author(s), cohesive author: Analysis of S/N (1994)

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    This study indicates the ways in which various aspects of the author(s) are brought forth in Dumb type’s performance art, the S/N production. Previous research has suggested a non-hierarchical organization of Dumb type and the absence of a “privileged author” in Dumb type’s collaborative work, S/N. However, the results that I have investigated from member’s interviews on the creative process of S/N along with my analysis of the recorded images of S/N, indicate a different aspect of the author(s). First, S/N was created through, so to speak, the collective ideas of the members of Dumb type. Further, S/N has at least nine quotations from previous performances, installations, and printed writings, besides the work-in-progress technique. Explicating one of the “author functions” as given by Michel Foucault, each text has plural subjects of the author. However, it has been revealed from members’ interviews that Teiji Furuhashi had a decision-making role in selecting the members’ ideas within the performance. Since then, S/N has had plural subjects of creation; however, Furuhashi is one of the subjects of creation along with the “privileged author.” S/N has plural authors (diffusive authors) yet at the same time, it has a “privileged author,” Teiji Furuhashi (cohesive author)

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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