Caterina Caracciolo

The AGROVOC Linked Dataset

Born in the early 1980s as a multilingual agricultural thesaurus, AGROVOC has steadily evolved over the last fifteen years, moving to an electronic version around the year 2000, and embracing the Semantic Web shortly thereafter. Today AGROVOC is a SKOS-XL concept scheme published as Linked Open Data, containing links as well as backlinks and references to many other Linked Datasets in the LOD cloud. In this paper we provide a brief historical summary of AGROVOC and detail its specification as a Linked Dataset.

Thesaurus maintenance, alignment and publication as linked data: the AGROVOC use case

The AGROVOC multilingual thesaurus maintained by the Food and Agriculture Organisation (FAO) of the United Nations is now published as linked data. In order to reach this goal AGROVOC was expressed in Simple Knowledge Organisation System (SKOS) and its concepts provided with dereferenceable URIs. AGROVOC is now aligned with ten other multilingual Knowledge Organisation Systems (KOS) 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. This paper extends a shorter version presented at MTSR 2011.

VocBench: A Web Application for Collaborative Development of Multilingual Thesauri

We introduce VocBench, an open source web application for editing thesauri complying with the SKOS and SKOS-XL standards. VocBench has a strong focus on collaboration, supported by workflow management for content validation and publication. Dedicated user roles provide a clean separation of competences, addressing different specificities ranging from management aspects to vertical competences on content editing, such as conceptualization versus terminology editing. Extensive support for scheme management allows editors to fully exploit the possibilities of the SKOS model, as well as to fulfill its integrity constraints. We discuss thoroughly the main features of VocBench, detail its architecture, and evaluate it under both a functional and user-appreciation ground, through a comparison with state-of-the-art and user questionnaires analysis, respectively. Finally, we provide insights on future developments.

Towards topic driven access to full text documents

We address the issue of providing topic driven access to full text documents. The methodology we propose is a combination of topic segmentation and information retrieval techniques. By segmenting the text into topic driven segments, we obtain small and coherent documents that can be used in two ways: as a basis for automatically generating hypertext links, and as a visualization aid for the reader who is presented with a small set of focused and restricted text snippets. In the presence of a concept hierarchy, or ontology, information retrieval techniques can be used to connect the segments obtained to concepts in the ontology. In this paper we concentrate on the text segmentation phase: we describe our approach to segmentation, discuss issues related to evaluation, and report on preliminary results.

Generating and retrieving text segments for focused access to scientific documents

When presented with a retrieved document, users of a search engine are usually left with the task of pinning down the relevant information inside the document. Often this is done by a time-consuming combination of skimming, scrolling and Ctrl+F. In the setting of a digital library for scientific literature the issue is especially urgent when dealing with reference works, such as surveys and handbooks, as these typically contain long documents. Our aim is to develop methods for providing a “go-read-here” type of retrieval functionality, which points the user to a segment where she can best start reading to find out about her topic of interest. We examine multiple query-independent ways of segmenting texts into coherent chunks that can be returned in response to a query. Most (experienced) authors use paragraph breaks to indicate topic shifts, thus providing us with one way of segmenting documents. We compare this structural method with semantic text segmentation methods, both with respect to topical focus and relevancy. Our experimental evidence is based on manually segmented scientific documents and a set of queries against this corpus. Structural segmentation based on contiguous blocks of relevant paragraphs is shown to be a viable solution for our intended application of providing “go-read-here” functionality.

Thesaurus Maintenance, Alignment and Publication as Linked Data: The AGROOVOC Use Case

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.

Knowledge Management at FAO: A Case Study on Network of Ontologies in Fisheries

In this chapter, we illustrate the work conducted at the Food and Agriculture Organization of the United Nations (FAO) with the creation of a network of ontologies about fisheries, developed with NeOn technologies and methodologies. The network included the main thematic areas needed to talk about fish stocks (often referred to as aquatic resources) and included data sources of various types: reference data for time series, thesauri for document indexing, actual time series, and the reuse of an existing well-known ontology maintained by FAO (the geopolitical ontology). Such a network of ontologies was also used within a prototypical web-based application. After describing the methodologies used to create the network, and its contents and features, we draw some conclusions and highlight the lessons learned during the process.

Networked Ontologies from the Fisheries Domain

In this paper we report on ongoing work concerning the creation of a network of ontologies based on metadata for time series relative to the domain of fisheries, and hint at the possibility of exploiting the network for web service applications. The results obtained so far show that the reengineering of classification systems stored as relational databases is possible, although some technical problems is still to be addressed.

GACS Core: Creation of a Global Agricultural Concept Scheme

The most frequently used concepts from AGROVOC, CABT, and NALT – three major thesauri in the area of food and agriculture – have been merged into a Global Agricultural Concept Scheme, with 15,000 concepts and over 350,000 terms in 28 languages in its beta release of May 2016. This set of core concepts (“GACS Core”) is seen as the first step towards a more comprehensive Global Agricultural Concept Scheme. In the context of a new Agrisemantics initiative, GACS is intended to serve as hub linking user-oriented thesauri with semantically more precise and specialized domain ontologies linked, in turn, to quantitative datasets. The goal is to improve the discoverability and semantic interoperability of agricultural information and data for the benefit of researchers, policy-makers, and farmers in support of innovative responses to the challenges of food security under conditions of climate change.

Preliminary Work towards Publishing Vocabularies for Germplasm and Soil Data as Linked Data

The agINFRA project focuses on the production of interoperable data in agriculture, starting from the vocabularies and Knowledge Organization Systems (KOSs) used to describe and classify them. In this paper we report on our first steps in the direction of publishing agricultural Linked Open Data (LOD), focusing in particular on germplasm data and soil data, which are still widely missing from the LOD landscape, seemingly because information managers in this field are still not very familiar with LOD practices.