DISTRIBUTION OF MONOGRAPHIC DATA-SETS OF CALLIANDRA, INGA, LEUCAENA, PARKINSONIA AND PINUS IN ELECTRONIC FORMAT - A MODEL FOR THE FUTURE DISSEMINATION OF BOTANICAL DATA.
Project Background
It is widely accepted that herbaria in developing countries, while expected to play a crucial role as information providers, are frequently compromised through lack of support and in-house capability. Many have difficulty curating their collection effectively and providing reliable information to the scientific and wider development community.
Given these constraints, herbarium curators have looked for ways to increase in-house efficiency and to improve their ability to provide accurate, up to date and useful information. Appropriate database technology has proved popular and successful. As well as assisting with routine curation, databases can be used to build up a clearer perspective on the overall collections in an herbarium taking both a taxonomic and geographic perspective.
Demand for assistance with information management databases and their implementation has been clearly demonstrated by interaction with herbaria in developing countries to date and by the success of database projects already implemented.
In Latin America, specific requests for database implementation have been received from all the national herbaria in Central American countries (except Belize) as well as herbaria in Argentina, Brazil - Amazonia, Brazil North East, Colombia and Mexico.
Project Objectives
Optimised techniques for the transfer and exchange of botanical data between herbaria and other research institutes, using data for key forestry and agro-forestry genera as examples, developed and disseminated.
Intended Outputs
- A series of BRAHMS monographic data-sets on disk for the genera Calliandra, Inga, Leucaena, Parkinsonia and Pinus, distributed and implemented.
- Software to access these data-sets and integrate the data into existing herbarium databases.
- Documentation fully describing the data-sets and the procedures to access them including data-specific tutorial materials.
- Advertising material for each data-set.
- Survey of product value.