Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 438106
Title Towards conceptual representation and invocation of scientific computations
Author(s) Rijgersberg, H.; Top, J.L.; Wielinga, B.
Source International Journal of Semantic Computing 6 (2012)4. - ISSN 1793-351X
DOI https://doi.org/10.1142/S1793351X12500079
Department(s) Consumer Science & Intelligent Systems
Publication type Refereed Article in a scientific journal
Publication year 2012
Abstract Computers are central in processing scientific data. This data is typically expressed as numbers and strings. Appropriate annotation of bare data is required to allow people or machines to interpret it and to relate the data to real-world phenomena. In scientific practice however, annotations are often incomplete and ambiguous let alone machine interpretable. This holds for reports and papers, but also for spreadsheets and databases. Moreover, in practice its often unclear how the data has been created. This hampers interpretation, reproduction and reuse of results and thus leads to suboptimal science. In this paper we focus on annotation of scientific computations. For this purpose we propose the ontology OQR (the Ontology of Quantitative Research). It includes a way to represent generic scientific methods and their implementation in software packages, invocation of these methods and handling of tabular datasets. This ontology promotes annotation by humans, but also allows automatic, semantic processing of numerical data. It allows scientists to understand the selected settings of computational methods and to automatically reproduce data generated by others. A prototype application demonstrates this can be done, illustrated by a case in food research. We evaluate this case with a number of researchers in the considered domain
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