Abstract
The trajectory of future food production and consumption is currently being sculpted by an amalgamation of diverse technological advancements. These include, but are not limited to, big data, mobile technologies, robotics, remote-sensing services, virtual and augmented reality, distributed computing, the Internet of Things (IoT), adaptive systems, and Semantic Web technologies. This burgeoning field is variously termed as Smart Food Systems, Digital Agriculture, e-Agriculture, Agriculture 4.0, and Smart Agriculture. Despite its pivotal role in global sustenance, agriculture remains one of the world’s least digitized sectors. However, it stands to gain immensely from digitization, underscoring the importance of research in this domain.
SemanticWeb applications have found their niche in various facets of agriculture and smart food systems. They are instrumental in ensuring data interoperability, sharing, and reuse. Controlled vocabularies, which are systematic arrangements of concepts curated by specific communities, cater to their unique data description needs. By formalizing these vocabularies in standard SemanticWeb languages like RDF and OWL, we not only facilitate their reuse by other communities but also enable machines to conduct more precise data analyses.
The “SmartFood” theme resonated with a diverse audience, including researchers,
industry professionals, farmers, and consumer advocacy groups. These stakeholders share a common vision: the belief that Semantic technologies, epitomized by controlled vocabularies, ontologies, and data platforms, are central to devising solutions for this sector. Additionally, sustainable business models in the realm of data-driven agri-food were a focal point of discussion in this forum. For this workshop, the paper review process was executed in a single-blind fashion. Each submission underwent a stringent review by at least three and at most five experts in the field. Out of the five papers submitted, three met the rigorous standards set by the committee and were subsequently approved for presentation.
SemanticWeb applications have found their niche in various facets of agriculture and smart food systems. They are instrumental in ensuring data interoperability, sharing, and reuse. Controlled vocabularies, which are systematic arrangements of concepts curated by specific communities, cater to their unique data description needs. By formalizing these vocabularies in standard SemanticWeb languages like RDF and OWL, we not only facilitate their reuse by other communities but also enable machines to conduct more precise data analyses.
The “SmartFood” theme resonated with a diverse audience, including researchers,
industry professionals, farmers, and consumer advocacy groups. These stakeholders share a common vision: the belief that Semantic technologies, epitomized by controlled vocabularies, ontologies, and data platforms, are central to devising solutions for this sector. Additionally, sustainable business models in the realm of data-driven agri-food were a focal point of discussion in this forum. For this workshop, the paper review process was executed in a single-blind fashion. Each submission underwent a stringent review by at least three and at most five experts in the field. Out of the five papers submitted, three met the rigorous standards set by the committee and were subsequently approved for presentation.
| Original language | English |
|---|---|
| Title of host publication | Advances in Conceptual Modeling |
| Subtitle of host publication | ER 2023 Workshops, CMLS, CMOMM4FAIR, EmpER JUSMOD, OntoCom, QUAMES, and SmartFood Lisbon, Portugal, November 6–9, 2023 Proceedings |
| Publisher | Springer Nature |
| Pages | 295-297 |
| Number of pages | 3 |
| Edition | 1 |
| ISBN (Electronic) | 978-3-031-47112-4 |
| ISBN (Print) | 978-3-031-47111-7 |
| Publication status | Published - 26 Oct 2023 |
Publication series
| Name | Lecture Notes in Computer Science |
|---|---|
| Publisher | Springer Cham |
| Volume | 14319 |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Keywords
- n/a OA procedure