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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 AGROVOCFAO’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 CGIARGFAR 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 Its content includes unique grey literature such as unpublished scientific and technical reports, theses, conference papers, government publications, and more.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.

 

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Resources

Displaying 1751 - 1755 of 9579

Examining the effect of diverse management strategies on landscape scale patterns of forest structure in Pennsylvania using novel remote sensing techniques

Journal Articles & Books
December, 2014
United States of America

We used novel remote sensing techniques to compare the landscape-scale patterns of forest structure in Pennsylvania, USA under the management of four different agencies with varying primary objectives, including production forestry, wildlife habitat, recreation, and private ownership. We (i) developed a forest structure classification scheme using publicly available LiDAR and orthographic aerial imagery data, (ii) mapped the forest structure across twenty forested landscapes, and (iii) compared the landscape-scale forest structure patterns among the four forest management types.

Geospatial comparison of four models to predict soil erodibility in a semi-arid region of Central India

Journal Articles & Books
December, 2014

The soil erodibility factor of RUSLE is one of the important indicators of land degradation. It can be measured either directly under natural or simulated rainfall condition or indirectly estimated by empirical models. A geospatial variation of this factor is essential for prioritization of reclamation measures. However, geospatial upscaling of soil erodibility factor is very uncertain because of its dynamic nature and dependent on the parameters used in the model.

Participatory Evaluation of Monitoring and Modeling of Sustainable Land Management Technologies in Areas Prone to Land Degradation

Journal Articles & Books
December, 2014

Examples of sustainable land management (SLM) exist throughout the world. In many cases, SLM has largely evolved through local traditional practices and incremental experimentation rather than being adopted on the basis of scientific evidence. This means that SLM technologies are often only adopted across small areas. The DESIRE (DESertIfication mitigation and REmediation of degraded land) project combined local traditional knowledge on SLM with empirical evaluation of SLM technologies.

Impacts of landscape fragmentation on simulated precipitation fields in the Amazonian sub-basin of Ji-Paraná using the Eta model

Journal Articles & Books
December, 2014

Numerical studies on impacts of landscape fragmentation due to land use and land cover change (LUCC) on precipitation fields over the Ji-Paraná basin in the Amazon region are carried out using atmospheric Eta model. Experiments consider historical data about LUCC over the basin from 1978 to 2000 and compare simulations under LUCC conditions with simulations under pristine conditions. In agreement with previous observational studies, model results do not show statistically significant impacts on precipitation in the region.

Sustainable Land Management (SLM) Practices in Drylands: How Do They Address Desertification Threats?

Journal Articles & Books
December, 2014

Managing land sustainably is a huge challenge, especially under harsh climatic conditions such as those found in drylands. The socio-economic situation can also pose challenges, as dryland regions are often characterized by remoteness, marginality, low-productive farming, weak institutions, and even conflict. With threats from climate change, disputes over water, competing claims on land, and migration increasing worldwide, the demands for sustainable land management (SLM) measures will only increase in the future.