AGROVOC: The linked data concept hub for food and agriculture

Subirats-Coll, Imma; Kolshus, Kristin; Turbati, Andrea; Stellato, Armando; Mietzsch, Esther; Martini, Daniel; Zeng, Marcia Lei

doi:10.1016/j.compag.2020.105965

Cited by 20 publications

(16 citation statements)

References 8 publications

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“…Every discipline requires diverse data formats with some form of data integration and interoperability. Hence, research under this subtopic revolves around the integration of OGD sources in certain fields, such as agriculture (Subirats-Coll et al. , 2022), smart cities (Van de Vyvere and Colpaert, 2022) and the property industry (Karamanou et al.…”

Section: Resultsmentioning

confidence: 99%

Towards a taxonomy of research areas in open government data

Mohamad¹,

Sylvester

Campbell‐Meier

2023

OIR

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PurposeThis study aimed to develop a taxonomy of research areas in open government data (OGD) through a bibliometric mapping tool and a qualitative analysis software.Design/methodology/approachIn this study, the authors extracted metadata of 442 documents from a bibliographic database. The authors used a bibliometric mapping tool for familiarization with the literature. After that, the authors used qualitative analysis software to develop taxonomy.FindingsThis paper developed taxonomy of OGD with three research areas: implementation and management, architecture, users and utilization. These research areas are further analyzed into seven topics and twenty-eight subtopics. The present study extends Charalabidis et al. (2016) taxonomy by adding two research topics, namely the adoption factors and barriers of OGD implementations and OGD ecosystems. Also, the authors include artificial intelligence in the taxonomy as an emerging research interest in the literature. The authors suggest four directions for future research: indigenous knowledge in open data, open data at local governments, development of OGD-specific theories and user studies in certain research themes.Practical implicationsEarly career researchers and doctoral students can use the taxonomy to familiarize themselves with the literature. Also, established researchers can use the proposed taxonomy to inform future research. Taxonomy-building procedures in this study are applicable to other fields.Originality/valueThis study developed a novel taxonomy of research areas in OGD. Taxonomy building is significant because there is insufficient taxonomy of research areas in this discipline. Also, conceptual knowledge through taxonomy creation is a basis for theorizing and theory-building for future studies.

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Section: Resultsmentioning

confidence: 99%

Towards a taxonomy of research areas in open government data

Mohamad¹,

Sylvester

Campbell‐Meier

2023

OIR

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“…They help in sharing data used as model inputs for model calibration and documentation. The agronomic community has developed many controlled vocabularies and ontologies such as AGROV OC (Subirats-Coll et al, 2022) from FAO or AGROPORTAL (Jonquet et al, 2018). Some ontologies are very specific, such as OntoHydroAgro, which is dedicated to the impact of climatic changes and agricultural activities on water resources (Bonacin et al, 2016).…”

Section: Integrating New Knowledge and Facilitating Interoperabilitymentioning

confidence: 99%

Advances in integrating different models assessing the impact of climate change on agriculture

Bergez¹,

Constantin²,

Debaeke³

et al. 2023

Burleigh Dodds Series in Agricultural Science

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The impact of climate change on the agricultural sector is causing considerable concern worldwide. Using modelling and simulation to analyse the impact of and ways to mitigate climate change is challenging. However, over the last few decades modelling approaches have evolved to tackle this problem. This chapter presents the various advances of integrating different models that assess the effects of climate change on agriculture. Based on an ‘ideal’ modelling archetype, we discuss different solutions such as: i) a complete and balanced integration of models; ii) coupling sub-models; iii) integrating new knowledge and facilitating inter-operability; iv) integrating behaviours and decision-making to adapt to climate change; v) incorporating inter- and intra-species diversity into models; vi) from white to black box models and vii) ensemble modelling. The chapter includes examples of all these solutions. The last section explains why these modelling solutions may be insufficient and discusses future trends in modelling.

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“…Research under this subtopic revolves around the integration of open data in various fields, such as agriculture (Subirats-Coll et al, 2022), smart cities (Van de Vyvere & Colpaert, 2022) and the property industry (Karamanou et al, 2022). Data interoperability is significant for developers integrating two data sources to build data-driven applications and services.…”

Section: Data Integration and Interoperabilitymentioning

confidence: 99%

“…In the third point, the informants reveal that open data is meaningful in certain start-up industries. Open data discourses emerge in smart cities (Lnenicka et al, 2022;Lodato et al, 2021;Matheus et al, 2020), agriculture (Andrade et al, 2021;Subirats-Coll et al, 2022), smart farming (Wolfert et al, 2017), transportation (Da Silva et al, 2022), and businesses (Jeon et al, 2022). It is essential to note that not all industries are ready for open data.…”

Section: B) Political Willingnessmentioning

confidence: 99%

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Exploring Open Data Affordances for Entrepreneurial Opportunity Recognition

Mohamad

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<p><strong>Start-up entrepreneurs have an interest in open data in practice. However, open data for start-up entrepreneurship is a concept that has not been thoroughly investigated. Also, there is a lack of understanding of how start-up entrepreneurs utilise open data for entrepreneurial opportunity recognition. Hence, the research explores open data affordances for entrepreneurial opportunity recognition amongst start-up entrepreneurs in Malaysia. The research developed three theoretically based research questions from affordance theory. The first research question revolves around the perceived affordances of open data to find business opportunities. The second research question is about open data actualisation for entrepreneurial opportunity recognition. The third research question investigates facilitating conditions which enable entrepreneurs to actualise open data for entrepreneurial opportunity recognition. This qualitative research employed online semi-structured interviews supported with documentary evidence as the primary data source. Thirty online semi-structured interviews were conducted with twenty-four start-up entrepreneurs who were CEOs, founders, and co-founders. Six interviews were conducted to triangulate the data: three representatives from open data providers, a former president of a start-up association, and two representatives from start-up accelerator programmes. The findings indicate that start-up entrepreneurs have positive, negative, and mixed perceptions regarding open data affordances. Start-up entrepreneurs actualise open data for product building, creating values with existing products, and using open data for research and strategy. The findings highlight facilitating conditions required for opportunity recognition to emerge from open data. These facilitating conditions are in five areas: data quality, start-up readiness, the interdependence of stakeholders, open data enablers, and broader contexts. Several notable unexpected findings include discovering sandbox and quadruple helix programmes as emerging open data enablers. The study also contributes to the empirical evidence on a possible open data misconception among start-up entrepreneurs. This study developed a novel theoretical framework for the research topic. This research is significant to practitioners to improve open data initiatives. Researchers can apply or extend the theoretical framework in this research as a foundation for future studies.</strong></p>

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AGROVOC: The linked data concept hub for food and agriculture

Cited by 20 publications

References 8 publications

Towards a taxonomy of research areas in open government data

Towards a taxonomy of research areas in open government data

Advances in integrating different models assessing the impact of climate change on agriculture

Exploring Open Data Affordances for Entrepreneurial Opportunity Recognition

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