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 Its content includes unique grey literature such as unpublished scientific and technical reports, theses, conference papers, government publications, and more.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 7971 - 7975 of 9579Factors influencing the role of non-wood forest products and services
Expansion of China's Cities and Agricultural Production
In China, there is a growing debate on the role of cultivated land conversion on food security. This paper examines the changes of the area of cultivated land and its potential agricultural productivity in China using satellite images. We find that between 1986 and 2000, China recorded a net increase of cultivated land (+1.9%), which almost offset the decrease in average potential productivity, or bioproductivity (-2.2%). Therefore, we conclude that conversion of cultivated land did not hurt China's national food security.
Institutions and properties of the transaction: influences on land rental contract design in Poland
The article analyses influences on the design of land rental contracts in Poland. Attention is paid to the effect of both the properties of the transaction as identified in Transaction Cost Economics (asset-specificity, uncertainty, frequency) and the features of the institutional environment (legal as well as customary rules) as studied by the Economics of Property Rights. The conclusion is that institutional influences have a very strong effect and should not be disregarded in the explanation of contract choice.
Spatial Econometrics Revisited: A Case Study of Land Values in Roanoke County
Omitting spatial characteristics such as proximity to amenities from hedonic land value models may lead to spatial autocorrelation and biased and inefficient estimators. A spatial autoregressive error model can be used to model the spatial structure of errors arising from omitted spatial effects. This paper demonstrates an alternative approach to modeling land values based on individual and joint misspecification tests using data from Roanoke County in Virginia. Spatial autocorrelation is found in land value models of Roanoke County.