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 Its content includes unique grey literature such as unpublished scientific and technical reports, theses, conference papers, government publications, and more.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 2451 - 2455 of 9579Sub-pixel mapping of remotely sensed imagery with hybrid intra- and inter-pixel dependence
Sub-pixel mapping of remotely sensed imagery is often performed by assuming that land cover is spatially dependent both within and between image pixels. Intra- and inter-pixel dependencies are two widely used approaches to represent different land-cover spatial dependencies at present. However, merely using intra- or inter-pixel dependence alone often fails to fully describe land-cover spatial dependence, making current sub-pixel mapping models defective.
How can city planners improve health and reduce mortality in Alameda County, California? A cross-sectional analysis
BACKGROUND: Dramatic disparities in a range of health outcomes persist in Alameda County, California. Age-standardised mortality rates range from 300 to 1300 deaths per 100 000 across census tracts in this county, with life expectancies lagging by 10 years in the most disadvantaged census tracts. Finding factors at the community level that affect neighbourhood health levels is a key step towards addressing these inequalities. Walking to work may be one of these factors, and is something that local policy makers could effectively act upon through city planning and maintenance initiatives.
Uncertainty in ecosystem mapping by remote sensing
The classification of remotely sensed images such as aerial photographs or satellite sensor images for deriving ecosystem-related maps (e.g., land cover, land use, vegetation, soil) is generally based on clustering of spatial entities within a spectral space. In most cases, Boolean logic is applied in order to map landscape patterns. One major concern is that this implies an ability to divide the gradual variability of the Earth's surface into a finite number of discrete non-overlapping classes, which are considered to be exhaustively defined and mutually exclusive.
Local-level determinants of wildcat occupancy in Northeast Scotland
We studied the influence of food abundance, land cover and disturbance on European wildcat (Felis silvestris silvestris Schreber, 1777) presence in Scotland. Wildcat records were collected using camera trapping, and prey data were assessed through linear transects and small mammal trapping. Surveys were carried out in three study areas in northeast Scotland. Wildcat occupancy was best predicted by a combination of food and land cover variables.
evil of sluits: A re-assessment of soil erosion in the Karoo of South Africa as portrayed in century-old sources
Deep, linear gullies are a common feature of the present landscape of the Karoo of South Africa, where they were known locally in the early twentieth century as ‘sluits’. Recent research has shown that many of these features are now stable and are no longer significant sediment sources, although they are efficient connectors in the landscape. Because most of the gully networks predate the first aerial photographs, little is known in the scientific literature about the timing of their formation.