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 Its content includes unique grey literature such as unpublished scientific and technical reports, theses, conference papers, government publications, and more.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 7881 - 7885 of 9579Snowblind: the importance of climate information for recreational real estate
Seasonal climate forecasting systems have made substantial gains in recent years. Since climate forecasting technologies are quite new, it is difficult to value them by studying the impacts of existing systems. In pursuing the research necessary to develop and refine these technologies it is worthwhile to know if they have any benefit before their implementation. In this manuscript I determine that there is robust pre-implementation evidence that new vegetation index forecasting technologies could provide non-zero benefits in ranchette markets in Arizona.
Contracting for Environmental Property Rights: The Case of Vittel
Based on an authentic case of contracting for environmental property rights, our paper shows several implications of applying the Coases propositions. The case study adds empirical content to basic transaction costs concepts by analyzing the design and implementation of a contractual arrangement between a pollutee a bottler of mineral water Vittel and several polluting farmers.
Dynamics of Phosphorus Fertilization and Liming Under Land Tenure Insecurity
This article solves and characterizes optimal decision rules to invest in irreversible land improvements conditional on land tenure insecurity. Economic model is a normative dynamic programming model with known parameter for the one period returns and transition equations. The decision rules are solved numerically conditional on alternative scenarios on the likelihood that the lease contract and, thus, farmer access to land is either renewed or expires. The model parameters represent Finnish soil quality and production conditions.
Modeling Urban Sprawl and Land Use Change in a Coastal Area-- A Neural Network Approach
Complexity of urban systems necessitates the consideration of interdependency among various factors for land use change modeling and prediction. The objective of this study is to explore the applicability of computational neural networks in modeling urban sprawl and land use change coupled with geographic information systems (GIS) in Hilton Head Island, South Carolina. We are particularly interested in the capabilities of neural networks to identify land use patterns, to model new development, and to predict future change. A binary logistic regression model is estimated comparison.
Deforestation and Shade Coffee in Oaxaca, Mexico: Key Research Findings
More than three-quarters of Mexico's coffee is grown on small plots shaded by the existing forest. Because they preserve forest cover, shade coffee farms provide vital ecological services including harboring biodiversity and preventing soil erosion. Unfortunately, tree cover in Mexico's shade coffee areas is increasingly being cleared to make way for subsistence agriculture, a direct result of the unprecedented decline of international coffee prices over the past decade.