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 495371
Title Improving access to big data in agriculture and forestry using semantic technologies
Author(s) Lokers, Rob; Randen, Yke Van; Knapen, Rob; Gaubitzer, Stephan; Zudin, Sergey; Janssen, Sander
Source In: Metadata and Semantics Research. - Springer Verlag (Communications in Computer and Information Science ) - ISBN 9783319241289 - p. 369 - 380.
Event 9th Metadata and Semantics Research Conference, MTSR 2015, Manchester, 2015-09-09/2015-09-11
DOI http://dx.doi.org/10.1007/978-3-319-24129-6_32
Department(s) Alterra - Earth informatics
Publication type Peer reviewed book chapter
Publication year 2015
Keyword(s) Agriculture - Big data - Forestry - Metadata - Semantic technologies
Abstract

To better understand and manage the interactions of agriculture and natural resources, for example under current increasing societal demands and climate changes, agro-environmental research must bring together an ever growing amount of data and information from multiple science domains. Data that is inherently large, multi-dimensional and heterogeneous, and requires computational intensive processing. Thus, agro-environmental researchers must deal with specific Big Data challenges in efficiently acquiring the data fit to their job while limiting the amount of computational, network and storage resources needed to practical levels. Automated procedures for collection, selection, annotation and indexing of data and metadata are indispensable in order to be able to effectively exploit the global network of available scientific information. This paper describes work performed in the EU FP7 Trees4Future and SemaGrow projects that contributes to development and evaluation of an infrastructure that allows efficient discovery and unified querying of agricultural and forestry resources using Linked Data and semantic technologies.

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