Finding data is one thing. Getting it ready to use is another. EcoData Retriever does the work so that you can focus on doing science.
Most ecological datasets do not adhere to any agreed-upon standards in format, data structure or method of access. As a result acquiring and utilizing available datasets can be a time consuming and error prone process. The EcoData Retriever automates the tasks of finding, downloading, and cleaning up ecological data files, and then stores them in a local database. The automation of this process reduces the time for a user to get most large datasets up and running by hours, and in some cases days. Small datasets can be downloaded and installed in seconds and large datasets in minutes. The program also cleans up known issues with the datasets and automatically restructures them into standard formats before inserting the data into your choice of database management systems (Microsoft Access, MySQL, PostgreSQL, and SQLite, on Windows, Mac and Linux).
If you use the EcoData Retriever, please use the following citation:
Morris, Benjamin D., and Ethan P. White. 2013. “The EcoData Retriever: Improving Access to Existing Ecological Data.” PLoS ONE 8 (6) (jun): 65848. doi:10.1371/journal.pone.0065848.
Publications using the EcoData Retriever
Locey, K.J. and D.J. McGlinn. 2013. Efficient algorithms for sampling feasible sets of macroecological patterns. PeerJ PrePrints 1:e78v1 http://doi.org/10.7287/peerj.preprints.78v1
Locey, K.J. and E.P. White. 2013. How species richness and total abundance constrain the distribution of abundance. Ecology Letters. 16:1177-1185. http://doi.org/10.1111/ele.12154
Coyle, J.R., A.H. Hurlbert, and E.P. White. 2013. Opposing mechanisms drive richness patterns of core and transient bird species. The American Naturalist 181: E83-90. http://doi.org/10.1086/669903
White, E.P., K.M. Thibault, and X. Xiao. 2012. Characterizing species-abundance distributions across taxa and ecosystems using a simple maximum entropy model. Ecology. http://doi.org/10.1890/11-2177.1