Skip to main content

page search

Community Organizations AGRIS
AGRIS
AGRIS
Data aggregator
Website

Location

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.

 

Members:

Resources

Displaying 3526 - 3530 of 9579

Effects of management regimes and extreme climatic events on plant population viability in Eryngium alpinum

Journal Articles & Books
December, 2012

Extreme climatic events like the 2003 summer heatwave and inappropriate land management can threaten the existence of rare plants. We studied the response of Eryngium alpinum, a vulnerable species, to this extreme climatic event and different agricultural practices. A demographic study was conducted in seven field sites between 2001 and 2010. Stage-specific vital rates were used to parameterize matrix population models and perform stochastic projections to calculate population growth rates and estimate extinction probabilities.

Use of GIS to predict potential distribution areas for wild boar (Sus scrofa Linnaeus 1758) in Mediterranean regions (SE Spain)

Journal Articles & Books
December, 2012
Spain

The wild boar is the target species selected for developing a GIS model of potential habitat for big game species, mainly using many GIS layers and kilometric abundance indices (KAI). We identify and weight environmental factors that determine the suitability for wild boar populations in a Mediterranean region, highly influenced by urban and agro-forestry activities. Marina Baja region (Spain) is selected to make a regional analysis. In the GIS modelling process, a suitability value is assigned to each pixel, which represents the habitat preference of the species.

Landslide Susceptibility Analysis of Shiv-Khola Watershed, Darjiling: A Remote Sensing & GIS Based Analytical Hierarchy Process (AHP)

Journal Articles & Books
December, 2012

In the present study, Remote Sensing Technique and GIS tools were used to prepare landslide susceptibility map of Shiv-khola watershed, one of the landslide prone part of Darjiling Himalaya, based on 9 landslide inducing parameters like lithology, slope gradient, slope aspect, slope curvature, drainage density, upslope contributing area, land use and land cover, road contributing area and settlement density applying Analytical Hierarchy Approach (AHA). In this approach, quantification of the factors was executed on priority basis by pair-wise comparison of the factors.

Analysing decadal land use/cover dynamics of the Lake Basaka catchment (Main Ethiopian Rift) using LANDSAT imagery and GIS

Journal Articles & Books
December, 2012

Development of accurate classification methods for rapidly changing catchments like that of Lake Basaka is fundamental to better understanding the catchment dynamics, which were not addressed in previous studies. Thus, the aim of this study was to map the decadal land use/cover (LUC) regimes of the Lake Basaka catchment, utilizing time series of LANDSAT images and to analyse the changes that occurred at different time periods. Both unsupervised and supervised image classification systems were utilized in Earth Resources Data Analysis System (ERDAS) Imagine (9.1).

Errors prediction for vector-to-raster conversion based on map load and cell size

Journal Articles & Books
December, 2012
China

Vector-to-raster conversion is a process accompanied with errors. The errors are classified into predicted errors before rasterization and actual errors after that. Accurate prediction of the errors is beneficial to developing reasonable rasterization technical schemes and to making products of high quality. Analyzing and establishing a quantitative relationship between the error and its affecting factors is the key to error prediction.