Abstract
In many research domains, studies need to be addressed in a multidisciplinary manner: each expert deals with a particular aspect of the problem. It may be useful for experts to take into account new data, share partial results, and update their own indicators and models, in order to take advantage of new measures and updated indexes in real time. For this, an easily-understandable knowledge model for any raw data source, statistical operator, indicator or business process to be available for experts, is needed. In this paper, we propose a goal-oriented meta-model, to index and reuse treatments and an extension of existing semantic Web standards to index goal-oriented services and assist and/or automate their selection. These features enable capabilities for interoperability and information exchange between three layers of knowledge: goal, domain and data layers. An application with an existing ontology of the agriculture domain and farm durability indicators will be proposed.
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Dantan, J., Pollet, Y., Taibi, S. (2014). A Goal-Oriented Meta-Model for Scientific Research. In: Murgante, B., et al. Computational Science and Its Applications – ICCSA 2014. ICCSA 2014. Lecture Notes in Computer Science, vol 8583. Springer, Cham. https://doi.org/10.1007/978-3-319-09156-3_53
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DOI: https://doi.org/10.1007/978-3-319-09156-3_53
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