25 research outputs found

    The Rationale of PROV

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    The PROV family of documents are the final output of the World Wide Web Consortium Provenance Working Group, chartered to specify a representation of provenance to facilitate its exchange over the Web. This article reflects upon the key requirements, guiding principles, and design decisions that influenced the PROV family of documents. A broad range of requirements were found, relating to the key concepts necessary for describing provenance, such as resources, activities, agents and events, and to balancing prov’s ease of use with the facility to check its validity. By this retrospective requirement analysis, the article aims to provide some insights into how prov turned out as it did and why. Benefits of this insight include better inter-operability, a roadmap for alternate investigations and improvements, and solid foundations for future standardization activities

    The lifecycle of provenance metadata and its associated challenges and opportunities

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    This chapter outlines some of the challenges and opportunities associated with adopting provenance principles and standards in a variety of disciplines, including data publication and reuse, and information sciences

    Towards Transparency of IoT Message Brokers

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    In this paper we propose an ontological model for documenting provenance of MQTT message brokers to enhance the transparency of interactions between IoT agents

    Knowledge Representation of digital Hermeneutics of archival and literary Sources

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    Scholarly analysis of archival, library, and literary sources results in a variety of digital artefacts meant to foster knowledge discovery and new research enquiries. Guidelines and standards to formally represent disciplinary information are available (e.g. XML schemas, ontologies, vocabularies). However, digital artefacts rarely address reusable structured information on the hermeneutical approach adopted by scholars when validating hypotheses. As a consequence, reproducibility and assessment of research results is hampered, and comparing online contradictory information is still a hard task. In this work we show how to leverage Semantic Web technologies in a high-level, portable data model for representing hermeneutical aspects related to cross-disciplinary analysis of archival and literary sources. We showcase three representative scenarios in the Cultural Heritage domain where the model is applied, and we describe benefits and limits of our solution

    Towards using focus groups to identify software developer's interests regarding their development process

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    The assurance of quality, reliability, and trustworthiness of software systems is a basic requirement in software development. Therefore, it is necessary to have a comprehension and detailed understanding of a software project. To make the understanding of a complex software system more accessible, a set of tools that analyze and visualize complex software systems could be introduced. Such a software analysis and visualization tool has to meet challenging requirements to be suited for the specific needs of users. To fulfill these requirements and to provide an intuitive way to understand the software projects with visual analysis, we use the human-oriented method of focus groups. We developed a design for focus groups to identify topics of interest regarding the analysis of software development processes. To test and improve our focus group design we conducted a pilot study with research software developers

    Structure-based knowledge acquisition from electronic lab notebooks for research data provenance documentation

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    BACKGROUND: Electronic Laboratory Notebooks (ELNs) are used to document experiments and investigations in the wet-lab. Protocols in ELNs contain a detailed description of the conducted steps including the necessary information to understand the procedure and the raised research data as well as to reproduce the research investigation. The purpose of this study is to investigate whether such ELN protocols can be used to create semantic documentation of the provenance of research data by the use of ontologies and linked data methodologies. METHODS: Based on an ELN protocol of a biomedical wet-lab experiment, a retrospective provenance model of the raised research data describing the details of the experiment in a machine-interpretable way is manually engineered. Furthermore, an automated approach for knowledge acquisition from ELN protocols is derived from these results. This structure-based approach exploits the structure in the experiment’s description such as headings, tables, and links, to translate the ELN protocol into a semantic knowledge representation. To satisfy the Findable, Accessible, Interoperable, and Reuseable (FAIR) guiding principles, a ready-to-publish bundle is created that contains the research data together with their semantic documentation. RESULTS: While the manual modelling efforts serve as proof of concept by employing one protocol, the automated structure-based approach demonstrates the potential generalisation with seven ELN protocols. For each of those protocols, a ready-to-publish bundle is created and, by employing the SPARQL query language, it is illustrated that questions about the processes and the obtained research data can be answered. CONCLUSIONS: The semantic documentation of research data obtained from the ELN protocols allows for the representation of the retrospective provenance of research data in a machine-interpretable way. Research Object Crate (RO-Crate) bundles including these models enable researchers to easily share the research data including the corresponding documentation, but also to search and relate the experiment to each other
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