Setting up a Global Linked Data Catalog of Datasets for Agriculture

Pesce, Valeria; Maru, Ajit; Archer, Phil; Malapela, Thembani; Keizer, Johannes

doi:10.1007/978-3-319-24129-6_31

Cited by 4 publications

(5 citation statements)

References 3 publications

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“…However, their approach is mainly based on adhoc vocabularies and does not include standards (except from DCAT). Finally, a preliminary approach to define dataset metadata for the agriculture domain is proposed by Pesce et al [42]. They propose a small extension to DCAT that enables the provision of access metadata providing technical information on how to access the datasets.…”

Section: Zeginis Et Al / a Semantic Meta-model For Data Integration A...mentioning

confidence: 99%

A semantic meta-model for data integration and exploitation in precision agriculture and livestock farming

Zeginis

Kalampokis

Palma

et al. 2023

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At the domains of agriculture and livestock farming a large amount of data are produced through numerous heterogeneous sources including sensor data, weather/climate data, statistical and government data, drone/satellite imagery, video, and maps. This plethora of data can be used at precision agriculture and precision livestock farming in order to provide predictive insights in farming operations, drive real-time operational decisions, redesign business processes and support policy-making. The predictive power of the data can be further boosted if data from diverse sources are integrated and processed together, thus providing more unexplored insights. However, the exploitation and integration of data used in precision agriculture is not straightforward since they: i) cannot be easily discovered across the numerous heterogeneous sources and ii) use different structural and naming conventions hindering their interoperability. The aim of this paper is to: i) study the characteristics of data used in precision agriculture & livestock farming and ii) study the user requirements related to data modeling and processing from nine real cases at the agriculture, livestock farming and aquaculture domains and iii) propose a semantic meta-model that is based on W3C standards (DCAT, PROV-O and QB vocabulary) in order to enable the definition of metadata that facilitate the discovery, exploration, integration and accessing of data in the domain.

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Section: Zeginis Et Al / a Semantic Meta-model For Data Integration A...mentioning

confidence: 99%

A semantic meta-model for data integration and exploitation in precision agriculture and livestock farming

Zeginis

Kalampokis

Palma

et al. 2023

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“…Indirect in the sense that a moderating component mediates connections. Also, most often, the links are external to the portals, because the moderating component is not embedded in the data portals [ 3 , 5 – 7 , 15 – 17 ].…”

Section: Open Data Interlinkagementioning

confidence: 99%

“…When domain specific vocabularies are utilized, they are able to annotate only part of metadata: usually tags or the indication of the main dataset domain [ 3 , 5 , 17 ]. Indeed, it adds another semantic level, lifting simple strings to semantic expressions.…”

Section: Open Data Interlinkagementioning

confidence: 99%

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LigADOS: Interlinking Datasets in Open Data Portal Platforms on the Semantic Web

Figueiredo

Cordeiro²,

Campos

2021

Metadata and Semantic Research

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The fostering of data opening has been largely motivated by sets of laws on access to information, which establish the need to make data related to governmental activities available to citizens and society in general, as well as results from business processes or scientific research, also for accountability and transparency. There are several ways of making data available to the public, from a simple website to sophisticated applications for accessing the data. In this context, one of the options is the construction of an open data portal using platforms for data repositories and catalogs. In the last few years, there has been a rapid proliferation of this type of portals, with domain or organization specific datasets being widely disseminated in platforms like CKAN. In these platforms, datasets are organized in thematic groups and described by keywords and other attributes assigned by the publisher. Usually described by metadata with poor semantics, these datasets very often remain as “data silos”, with no explicit connection or data integration mechanism, making it difficult for the users to locate and interrelate relevant data sources. In contrast, the Semantic Web focuses on a way of modeling and representing data in an easier manner to establish interrelationships between data, accompanied by richer descriptors. Based on this scenario, this paper proposes LigADOS, an approach to create interconnections between datasets considering their content and related metadata. LigADOS is based on the principles of the Semantic Web and associated linked data solutions and technologies, to support rich access strategies to RDF data published using portal platforms like CKAN and others.

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“…Aloja un conjunto de ontologías enfocadas en el dominio agrícola, permite cargar diccionarios de rasgos para el mejoramiento del cultivo y la creación directa de ontologías; asimismo, permite consultar, crear, actualizar o eliminar ontologías. CIARD Ring [11]. Es un portal con servicios web semánticos que contiene 3201 conjuntos de datos y 5327 servicios de datos.…”

Section: Portales Web Agrícolasunclassified

Desarrollo de ontologías agrícolas mediante el reúso de recursos semánticos

Pech-May¹

2019

RCS

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Resumen. En México, la agricultura juega un papel muy importante debido a la dependencia económica y alimentaria. Este sector genera grandes volúmenes de datos que no son procesados y están representados en forma de texto, tablas, etc, lo que carece de significado o valor para ser utilizados en la toma de decisiones por parte de empresarios agrícolas, organismos de gobierno o investigadores delárea. Esto ha ocasionado que algunas organizaciones lideradas por la Organización de la Naciones Unidas para la Agricultura y Alimentación implementen tecnologías para estructurar y formalizar el conocimiento a través de los recursos semánticos; lo que ha llevado al desarrollo de una gran cantidad de recursos semánticos agrícolas. Sin embargo, dichos recursos han sido desarrollado con las características de un país en particular, lo que hace imposible utilizarlos en el nuestro. En este documento se analizan los recursos existentes con el objetivo de brindar una información relevante que permita serútil para la adaptación y desarrollo de nuevos recursos semánticos de los cultivos más comunes en México. Asimismo se desarrollaron tres recursos semánticos adaptados a la región de Tabasco mediante el reúso de recursos de la Organización para la Agricultura y Alimentos.Palabras clave: ontologías agrícolas, grafo de conocimiento, OWL FAO.Abstract. In Mexico, agriculture plays a very important role due to economic and food dependence. This sector generates large volumes of data that are not processed and are represented in the form of text, tables, etc., which lacks meaning or value to be used in decision-making by agricultural entrepreneurs, government agencies or researchers of the area. This has caused some organizations led by the Food and Agriculture Organization of the United Nations to implement technologies to structure and formalize knowledge through semantic resources; which has led to the development of a large amount of semantic agricultural resources. However, these resources have been developed with the characteristics of

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Setting up a Global Linked Data Catalog of Datasets for Agriculture

Cited by 4 publications

References 3 publications

A semantic meta-model for data integration and exploitation in precision agriculture and livestock farming

A semantic meta-model for data integration and exploitation in precision agriculture and livestock farming

LigADOS: Interlinking Datasets in Open Data Portal Platforms on the Semantic Web

Desarrollo de ontologías agrícolas mediante el reúso de recursos semánticos

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