Thesaurus Maintenance, Alignment and Publication as Linked Data

The AGROVOC multilingual thesaurus maintained by the Food and Agriculture Organization of the United Nations (FAO) is now published as linked data. In order to reach this goal AGROVOC was expressed in Simple Knowledge Organization System (SKOS), and its concepts provided with dereferenceable URIs. AGROVOC is now aligned with ten other multilingual knowledge organization systems related to agriculture, using the SKOS properties exact match and close match. Alignments were automatically produced in Eclipse using a custom-designed tool and then validated by a domain expert. The resulting data is publicly available to both humans and machines using a SPARQL endpoint together with a modified version of Pubby, a lightweight front-end tool for publishing linked data.
This paper describes the process that led to the current linked data AGROVOC and discusses current and future applications and directions.

Contributed by Caterina Caracciolo, Ahsan Morshed, Armando Stellato, Gudrun Johannsen, Yves Jaques and Johannes Keizer.


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Subject Classification with DITA Markup for Agricultural Learning Resources. A Case Example in Agroforestry

Technical documentation and training materials are important elements in helping to accelerate the use and impact of agricultural research for development. The creation and delivery of these resources can be enhanced through content enrichment and the production and reuse of modular components. This process can be further improved by integrating rich semantic descriptions with resource metadata and domain-specific markup combined with the consistent use of controlled vocabulary. The Darwin Information Typing Architecture (DITA) supports both the integration of metadata as well as markup for technical as well as learning and training content. DITA also includes mechanisms for adding the semantics of taxonomy and ontology definitions for classifying content.


This paper explores the potential use of enriching agroforestry learning resources with DITA markup through descriptive metadata and subject classification.

Contributed by Thomas Zschocke.


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