Ontology-Based Representation of Scientific Laws on Beef Production and Consumption

Kulicki, Piotr; Trypuz, Robert; Trójczak, Rafał; Wierzbicki, Jerzy; Woźniak, Alicja

doi:10.1007/978-3-319-03437-9_42

Cited by 5 publications

(6 citation statements)

References 8 publications

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“…Many theoretical and practical applications of animal nutrition, ruminant research, and other related disciplines have been developed to improve livestock productivity. The mature concepts and parameter systems of livestock production have standardized and centralized livestock characteristics, so as to achieve accurate management (62). However, for ruminant animals, the nonstandard terminology, high specificity of experimental data, and lack of data annotation mean the data on production and environmental impacts are highly uncertain and cannot be shared in a standardized way (63).…”

Section: Developing a Domain Ontology And Global Database For Ruminan...mentioning

confidence: 99%

Global Strategies to Minimize Environmental Impacts of Ruminant Production

Chang

2022

Annu. Rev. Anim. Biosci.

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Demand for ruminant products (dairy products, beef, and sheep meat) is increasing rapidly with population and income growth and the acceleration of urbanization. However, ruminant animals exert the highest environmental impacts and consume the most resources in the livestock system. Increasing studies have focused on various measures to reduce ammonia, greenhouse gas emissions, and resource depletion from ruminant production to consumption. This review offers supply- and demand-side management strategies to reduce the environmental impact of ruminant products and emphasizes the mitigation potential of coupling livestock production with cultivation and renewable energy. On a global scale, more attention should be paid to the green-source trade and to strengthening global technology sharing. The success of these strategies depends on the cost effectiveness of technology, public policy, and financial support. Future studies and practice should focus on global database development for sharing mitigation strategies, thus facilitating technology innovations and socioeconomic feasibility. Expected final online publication date for the Annual Review of Animal Biosciences, Volume 10 is February 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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Section: Developing a Domain Ontology And Global Database For Ruminan...mentioning

confidence: 99%

Global Strategies to Minimize Environmental Impacts of Ruminant Production

Chang

2022

Annu. Rev. Anim. Biosci.

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“…As mentioned above, the project's KB is structured according to Science ontology (see [2], [3] for the formal structure of the ontology and [4] for the philosophical sources of the ontology). The ontology is expressed in OWL and is composed of two parts: TBox and ABox.…”

Section: Ontology Of Scientific Lawsmentioning

confidence: 99%

“…4 The TBox of Science ontology can be browsed here: http://onto.kul.pl/webprotege/. 5 The way the laws are represented in Science has been widely described in [2], [3].…”

Section: Ontology Of Scientific Lawsmentioning

confidence: 99%

“…Another way to facilitate access to the content of a paper is using so called highlights which are "a short collection of bullet points that convey the core findings and provide readers with a quick textual overview of the article". 2 There are also semantic solutions addressing this problem. For example, the authors of the Nanopublication and the Micropublications projects have created models to represent statements and argumentation from scientific papers.…”

Section: Introductionmentioning

confidence: 99%

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Knowledge transfer from agri-food scientific papers to a knowledge base

Trójczak

Trypuz

Mazurek

et al. 2015

Annals of Computer Science and Information Systems

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Abstract-We address the problem of the access to the results of scientific publications in the agri-food domain. We focus on the description of main contributions of the papers treating them as accepted or rejected beliefs of their authors expressed in the form of scientific laws. We define the structure of different kinds of scientific laws present in the domain in the form of an ontology. The main concern of the paper is a process in which we proceed from the abstracts of papers to the ontological representation of laws. Moreover, we present examples of SPARQL queries which show how the resulting knowledge base can be used. Among the uses we point out discovering new scientific hypotheses and incoherencies among scientific laws.

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“…Furthermore, they can find in their plots some unknown plants and want to know if they are weed plants or auxiliary plants for their crops. These kind of information can be extracted from scientific sources as presented in [10]. To answer to these information needs, farmers needs to query several datasets that describe living organisms.…”

Section: Introductionmentioning

confidence: 99%

Cross-Querying LOD Datasets Using Complex Alignments: An Application to Agronomic Taxa

Thiéblin

Amarger

Hernandez

et al. 2017

Metadata and Semantic Research

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Farmers have new information needs to change their agricultural practices. The Linked Open Data is a considerable source of knowledge, separated into several heterogeneous and complementary datasets. This paper presents a process to query LOD datasets from a known ontology using complex alignments. The approach was applied on Agro-nomicTaxon, a taxonomic classification ontology, to query Agrovoc and DBpedia.

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Ontology-Based Representation of Scientific Laws on Beef Production and Consumption

Cited by 5 publications

References 8 publications

Global Strategies to Minimize Environmental Impacts of Ruminant Production

Global Strategies to Minimize Environmental Impacts of Ruminant Production

Knowledge transfer from agri-food scientific papers to a knowledge base

Cross-Querying LOD Datasets Using Complex Alignments: An Application to Agronomic Taxa

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