7th Agricultural Ontology Services (AOS) Workshop 2006
1. Introduction
The Seventh Agricultural Ontology Services Workshop (AOS) on the “Ontology-based knowledge discovery: Using metadata and ontologies for improving access to agricultural information” was organized by Food and Agriculture Organization (FAO) in collaboration with the Fifth International Conference of the Asian Federation for Information Technology in Agriculture, from 10 to 11 November, 2006 at the Indian Institute of Sciences (Bangalore), India.
2. The Agricultural Ontology Service Workshop
2.1 Background
The benefits of ontologies can only be fully exploited if they are used efficiently within information systems for extraction or discovery of ‘embedded’ knowledge. In today’s exponentially growing information world, there is a mounting need to extract the most important information in the shortest possible time. It has become vital to have systems that are able to provide the most relevant results, while sieving through mushrooming information systems, websites, publications, forums, blogs etc. Although cataloguing and indexing resources are important steps, it is becoming increasingly difficult to accomplish these tasks due to the lack of skilled personnel, the cost of cataloguing and the rapid growth of the available information resources.
Considerable work has been done to date in the area of knowledge capture through the use of subject and process ontologies in the agricultural domain. The AOS project covers, under its name, ontologies on Food and Nutrition, Food Safety, Animal and Plant Health, Fisheries, etc., each of which captures knowledge in a specific domain area of agriculture. The complete multilingual AGROVOC Thesaurus, in the process of being made available in the form of an ontology, is rich with translations, synonyms and relations. All of these ontologies have been used in information systems to provide improved access to information. However, much of this can be further enhanced through the efficient use of ontologies for extracting the unknown and hidden pieces of knowledge, not only for providing efficient search results to the users but also for iteratively improving the ontology itself. We can achieve this only through the explicit formalization of domain knowledge through its elicitation from experts and by linking the ontologies to actual or instance data.
The workshop brought together heads of agricultural academic and research institutions, policy makers, agricultural researchers, faculty members, library and information professionals, computer professionals.
2.2 Objectives
The goal of the Seventh AOS workshop was to provide a platform for implementers to demonstrate how ontologies can extract and acquire additional knowledge from existing agricultural information systems. It aimed to bring together research communities, with special focus on agriculture, who are interested in efficiently capturing knowledge and in creating representations and formalizations that can be useful for reasoning and knowledge discovery.
2.3 Management
The workshop was held in correlation with the Fifth International Conference of Asian Federation for Information Technology in Agriculture and was held at the Indian Institute of Sciences, Bangaluru, India.
2.4 Participants
The workshop brought together more than 30 key persons in Library and Information services, Researchers and Research Information Managers, providers of extension services and Computer and system administrators in agricultural research, technology and extension institutions.
2.5 Topics and Presentations of the Workshop
The workshop included of 5 series of presentations on the following topics:
- Knowledge acquisition methods
- Knowledge elicitation techniques
- Ontology application
- Ontology modelling
- Rules in ontologies
3. Conclusions and Recommendations
The work on semantic standards is now ongoing in many different areas of agricultural information management, stretching from the organization of open archives in scientific publishing, over e-government projects to the management of remote sensing information and it’s linking to crop management. Further exchange about these developments is fruitful and necessary. Experiences with the implementation of new semantic methodologies like the use of RDFS and OWL needs to be exchanged, evaluated and promoted. It is vital to stress the importance of semantics and semantic technology not only within one application or within one community but also to keep in mind the interoperability between different communities in our area. The collaboration within the Agricultural Ontology Service Initiative needs to be brought on a more formal platform. It was proposed to set up a consortium to manage the AOS Initiative. Additionally, it was considered essential to define relationships between the AOS Initiative and other standard setting bodies like ISO and consortia like the Plant and Gene Ontology.
Presentations of the Seventh Agricultural Ontology Service (AOS) Workshop
- Takuji Kiura,Hitoshi. Toritani,Daisuke Horyu,Atsushi Yamakawa,Seishi Ninomiya:Application of web ontology to harvest estimation of rice in Thailand
- Seishi Ninomiya, Atsushi Yamakawa, Xinwen Yu: Dynamic Integrations of Crop Data and Corresponding Meteorological Data based on A Standardized Data Exchange Framework
- Gauri Salokhe: Examples of Ontology Applications
- ARD Prasad: Heuristic Approach for Automatic Metadata Capture of E-books/Journals
- Shigenobu TACHIZUKA, Masahiko NAGAI, Ryosuke SHIBASAKI:Implementation of Semantic Network Dictionary Systemfor Global Observation Data
- Dr. Devika P. Madalli, Nabonita Guha: Incorporating ARGOVOC in DSpace-based Agricultural Repositories
- Dr. A.K.Choubey, Dr. Meenakshi Mahajan: Metadata Framework for Agricultural Resources Information System (AgRIS)
- Gauri Salokhe: NeOn Project Lifecycle support for Networked Ontologies
- Dr. Chang Chun: Organizing and Implementing on theThesauri Mapping Project
- Rajni Jain, S. Minz, P. Adhiguru: Rough Set based Decision Tree for Identifying Vulnerable and Food Insecure Households
- Johannes Keizer: The Agricultural Ontology Service and its Vision
- Gauri Salokhe:The AOS/CS Workbench
- Francois Pinet, Pierre Ventadour, Thomas Brun, Petraq Papajorgji,Catherine Roussey, Frederic Vigier: Using UML for Ontology construction: a case study in Agriculture