What is AGRIS?
AGRIS (International System for Agricultural Science and Technology) is a global public database providing access to bibliographic information on agricultural science and technology. The database is maintained by CIARD, and its content is provided by participating institutions from all around the globe that form the network of AGRIS centers (find out more here). One of the main objectives of AGRIS is to improve the access and exchange of information serving the information-related needs of developed and developing countries on a partnership basis.
AGRIS contains over 8 million bibliographic references on agricultural research and technology & links to related data resources on the Web, like DBPedia, World Bank, Nature, FAO Fisheries and FAO Country profiles.
More specifically
AGRIS is at the same time:
A collaborative network of more than 150 institutions from 65 countries, maintained by FAO of the UN, promoting free access to agricultural information.
A multilingual bibliographic database for agricultural science, fuelled by the AGRIS network, containing records largely enhanced with AGROVOC, FAO’s multilingual thesaurus covering all areas of interest to FAO, including food, nutrition, agriculture, fisheries, forestry, environment etc.
A mash-up Web application that links the AGRIS knowledge to related Web resources using the Linked Open Data methodology to provide as much information as possible about a topic within the agricultural domain.
Opening up & enriching information on agricultural research
AGRIS’ mission is to improve the accessibility of agricultural information available on the Web by:
- Maintaining and enhancing AGRIS, a bibliographic repository for repositories related to agricultural research.
- Promoting the exchange of common standards and methodologies for bibliographic information.
- Enriching the AGRIS knowledge by linking it to other relevant resources on the Web.
AGRIS is also part of the CIARD initiative, in which CGIAR, GFAR and FAO collaborate in order to create a community for efficient knowledge sharing in agricultural research and development.
AGRIS covers the wide range of subjects related to agriculture, including forestry, animal husbandry, aquatic sciences and fisheries, human nutrition, and extension. Its content includes unique grey literature such as unpublished scientific and technical reports, theses, conference papers, government publications, and more. A growing number (around 20%) of bibliographical records have a corresponding full text document on the Web which can easily be retrieved by Google.
Members:
Resources
Displaying 9176 - 9180 of 9579Towards an Analytical Framework for Assessing Property Rights to Natural Resources: A Case Study in the Communal Areas of Zimbabwe
A taxonomy for describing property rights to natural resources is described and applied in a Zimbabwean case study. The taxonomy allows: tenures to be systematically compared and contrasted; incentives for natural resource management to be identified; and the evolution of tenure to natural resources to be assessed.
BEYOND MOBILITY: THE ROLE OF FUZZY ACCESS RIGHTS AND COMMON PROPERTY CONSIDERATIONS IN SEMI-ARID AFRICAN PASTORALIST SYSTEMS
We model the ill-defined nature of grazing access using fuzzy set theory. We also model common property considerations. Within this framework, we examine when the traditional system results in higher returns and/or lower variance for herders than land privatization or a standard common property regime.
IRRIGATION DISTRICT ADOPTION OF WATER CONSERVING RATE STRUCTURES
A binary choice model was used to identify the attributes that influence irrigation district adoption of conservation rate structures. Using principles of rate design and irrigation district administration as a framework, measures of irrigation district rate structure objectives and physical and economic conditions were developed. The factors investigated characterize the constraints under which districts operate, value and cost of water, quantity of water delivered and revenue risk for districts. Rate structure adoption was predicted with over 75% accuracy.