Georeferencing Lecture 27 January 2009

Welcome to the DanBIF introductory lecture on modern geo-referencing of biological collections and databases.

The lecture introduces advanced geo-referencing techniques applied to biodiversity data in general and regarding digitisation of biological collections in particular. You will be introduced to the techniques needed to add or complete the geographic information stored with the biological collections' specimens and/or in other databases holding biodiversity information.

The lecture is given by the world leading expert on the subject, Mr. John R. Wieczorek from the University of California, Berkeley. He among other things is the Lead Programmer for the Mammal Networked Information System (MaNIS), the Ornithological Information System (ORNIS), the Réseau de la Biodiversité de Madagascar (REBIOMA), and BioGeomancer. He consults for the HerpNET and the FishNet II projects, serves in the Geospatial Information Interest Group and the Darwin Core Task Group of the Biodiversity Information Standards Taxonomic Database Working Group (TDWG), and has served on the GBIF Data Access and Database Interoperability Science Subcommittee. More info on John Wieczorek through link: http://www.gbif.org/documents/enprizebio-abstract. 

For registration, please send an email to Lotte Endsleff.

In order to gain the most from the lecture, we recommended reading the following background material:
Required: Read MaNIS/HerpNet/ORNIS Georeferencing Guidelines
Recommended: Read Georeferencing for Dummies
Suggested: Read Best Practices

Organiser: DanBIF – Danish Biodiversity Information Facility – Danish participant node of GBIF

Some useful georeferencing resources:

Georeferencing Resources (HerpNet)

Georeferencing Links (ORNIS)

Background: Good geo-referencing & BioGeomancer

Geo-referencing is the process of converting text descriptions of locations to computer-readable geographic locations, such as a GIS system uses. Although this can be done by hand with maps and some guesswork, the BioGeomancer project (see below) provides the tools to improve the results for organizations to effectively geo-reference large amounts of data by:

• automating the geo-referencing of bulk data,

• intelligent application training (learning) from existing geo-references,

• accessing map and place-name gazetteers,

• generating the computer-readable geographic locations and

• error descriptions according to accepted standards and providing tools for validating these.

With standards-based geo-referenced locations, your data can be contributed to mapping and geographic search applications, such as portals and applications with intensive data requirements for pattern prediction or other data mining applied methods. These applications allow users to use map-based interfaces to review, query and interact with their own data enriched in this way by intelligent combinations with data from other sources, such as environmental data.

Well geo-referenced relevant biological collection data is in high demand. Mapping species occurrence data is fundamental to describing and analysing biotic distributions. This information is also critical for conservation planning, reserving selection, monitoring, and the examination of the potential effects of climate change on biodiversity.

A gazetteer is a geographical dictionary or directory, an important reference for information about places and place names, used in conjunction with a map or a full atlas.

The BioGeomancer Project is a worldwide collaboration of natural history and geospatial data experts. The primary goal of the project is to maximize the quality and quantity of biodiversity data that can be mapped in support of scientific research, planning, conservation, and management. The project promotes discussion, manages geospatial data and data standards, and develops software tools in support of this mission.

The BioGeomancer consortium aims to develop the online workbench, web services, and desktop applications that will provide geo-referencing for collectors, curators and users of natural history specimens, including software tools to allow natural language processing of archival data records that were collected in many different formats. The tools developed here are meant to be interoperable with data demanding applications like the GBIF data-portal.