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Community Organizations AGRIS
AGRIS
AGRIS
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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 1201 - 1205 of 9579

Prior Knowledge-Based Automatic Object-Oriented Hierarchical Classification for Updating Detailed Land Cover Maps

Journal Articles & Books
декабря, 2015

Automatic information extraction from optical remote sensing images is still a challenge for large-scale remote sensing applications. For instance, artificial sample collection cannot achieve an automatic remote sensing imagery classification. Based on this, this paper resorts to the technologies of change detection and transfer learning, and further proposes a prior knowledge-based automatic hierarchical classification approach for detailed land cover updating. To establish this method, an automatic sample collection scheme for object-oriented classification is presented.

Report in Brief: Assessing Botanical Capacity to Address Grand Challenges in the United States

Journal Articles & Books
декабря, 2015
United States of America

Botanical capacity plays a fundamental role in solving the grand challenges of the next century, including climate change, sustainability, food security, preservation of ecosystem services, conservation of threatened species, and control of invasive species. Yet critical components of botanical education, research, and management are lacking across government, academic, and private sectors.

Novel Semi-Supervised Land Cover Classification Technique of Remotely Sensed Images

Journal Articles & Books
декабря, 2015

This research article addresses the problem of land-cover classification from the multi-spectral remotely sensed images using a novel self-training based semi-supervised learning (SSL) technique. The proposed system, instead of using a single classifier, builds an ensemble of classifiers with the hope that the ensemble system will have a lesser generalization error than any of its members.

Land cover changes in an abandoned agricultural land in the Northern Apennine (Italy) between 1954 and 2008: Spatio-temporal dynamics

Journal Articles & Books
декабря, 2015
Italy

We report the spatio-temporal dynamics of land cover changes from 1954 to 2008 in a hilly mountainous area in the Italian northern Apennine, and ecological factors and processes associated with these dynamics. Land cover patches were mapped and analysed at three time periods (1954, 1980 and 2008). Changes over time were detected by analysing a combination of multitemporal source data from airborne images and from field surveys. Relationships between cover classes and environmental variables were analysed for the year 2008.

Effects of forest certification on the ecological condition of Mediterranean streams

Journal Articles & Books
декабря, 2015

Forest certification, a proxy for sustainable forest management, covers more than 10% of the world's forests. Under forest certification, forest managers and landowners must comply with environmental, economic and social management standards aiming to promote forest conservation. Despite an increasing area of certified forests, there is a dearth of data on how forest certification is affecting the conservation of forest ecosystems and associated habitats.