An example of data integration in a distributed network environment Barbara Stein Museum of Vertebrate Zoology

1. An example of data integration in a distributed network environment Barbara Stein Museum of Vertebrate Zoology

6. TDWG is part of IUBS. TDWG Mission To provide an international forum for biological data projects; To develop and promote the use of standards; and To facilitate data exchange. TDWG is part of IUBS. TDWG Mission To provide an international forum for biological data projects; To develop and promote the use of standards; and To facilitate data exchange.

10. Steps in Development of MaNIS Collaborative georeferencing of locality data Creating the network software Connecting institutional databases to the network�

11. Well-documented, georeferenced collecting events are crucial to biogeographic data and biogeographic analyses clearly demonstrate the advantages of uniting information via a distributed network (Peterson et al., 1999). Geospatial mapping and modeling of collections data expose outliers in the database that either need correction if erroneous or warrant further study if valid. Georeferenced specimen localities from diverse collections increase the number and nature of questions to which biodiversity data can be successfully applied. The pie charts below show percentages of the total number of specimens from three geographic regions held by participating institutions. The pie chart of Africa represents a situation in which a large, well-known institution, in this case the Field Museum, holds a majority of specimens from a given region of the world. However, the localities represented by one museum for a given region may be incomplete or biased depending on the history of research expeditions that have been conducted. Collecting may have been confined to a local region, to a particular habitat type, or to a specific era. Data from several institutions will complement those from collections with large holdings by increasing not only the total number of specimens, but also the variety of collecting events. The pie chart of the combined holdings from Oceania illustrates that the contributions of a smaller collection, in this case the Bernice P. Bishop Museum, can be crucial to biogeographic investigations. The pie chart from Mesoamerica shows that specimens may be equally represented among a host of institutions, so that to neglect any one could result in a serious omission. The union of geographic data points from many collections ultimately will present a more complete and accurate picture of past and present species distributions. Sophisticated distribution prediction tools such as GARP (1997) demonstrate the power that combined data sets can bring to research and conservation issues (e.g., Peterson et al., 1999). Well-documented, georeferenced collecting events are crucial to biogeographic data and biogeographic analyses clearly demonstrate the advantages of uniting information via a distributed network (Peterson et al., 1999). Geospatial mapping and modeling of collections data expose outliers in the database that either need correction if erroneous or warrant further study if valid. Georeferenced specimen localities from diverse collections increase the number and nature of questions to which biodiversity data can be successfully applied. The pie charts below show percentages of the total number of specimens from three geographic regions held by participating institutions. The pie chart of Africa represents a situation in which a large, well-known institution, in this case the Field Museum, holds a majority of specimens from a given region of the world. However, the localities represented by one museum for a given region may be incomplete or biased depending on the history of research expeditions that have been conducted. Collecting may have been confined to a local region, to a particular habitat type, or to a specific era. Data from several institutions will complement those from collections with large holdings by increasing not only the total number of specimens, but also the variety of collecting events. The pie chart of the combined holdings from Oceania illustrates that the contributions of a smaller collection, in this case the Bernice P. Bishop Museum, can be crucial to biogeographic investigations. The pie chart from Mesoamerica shows that specimens may be equally represented among a host of institutions, so that to neglect any one could result in a serious omission. The union of geographic data points from many collections ultimately will present a more complete and accurate picture of past and present species distributions. Sophisticated distribution prediction tools such as GARP (1997) demonstrate the power that combined data sets can bring to research and conservation issues (e.g., Peterson et al., 1999).

13. Steps in Development of MaNIS Collaborative georeferencing of locality data Creating the network software Connecting institutional databases to the network�

16. Steps in Development of MaNIS Collaborative georeferencing of locality data Creating the network software Connecting institutional databases to the network�