Large quantities of ecological and environmental data are increasingly available thanks to initiatives sponsoring the collection of large-scale data and efforts to increase the publication of already collected datasets. As a result, progress in ecology is increasingly limited by the speed at which we can organize and analyze data. To help improve ecologists' ability to quickly access and analyze data we have been developing two projects:
1. The EcoData Retriever is a software package that downloads publicly available ecological datasets, cleans up known issues, restructures them into standard database formats, and installs them into major database management systems (Microsoft Access, MySQL, PostgreSQL, and SQLite). Once the EcoData Retriever has loaded the data into the database it is easy to connect to the database using standard tools (e.g., MS Access, Filemaker, etc.).
2. The Ecological Data Wiki is a simple web based system that is designed to improve communication among ecologists regarding what data sets are available, how to obtain them, and how to best use them to address important questions in ecology. It uses the power of social media and collaborative technologies to allow scientists to combine their expertise in finding and utilizing ecology's data.
These tools are designed to “just work” and to require little to no technical expertise on the part of the users. As such they are designed to make access to ecological data easier for all ecologists. The EcoData Retriever automatically installs on all major operating systems and setting up a new dataset is as simple as selecting it from the available list. This automation reduces the time for a user to get most large datasets up and running by hours, and in some cases days. Users can also add datasets that are not available by providing the relevant information in a simple text file. The Ecological Data Wiki is an entirely web based system that can be easily edited by anyone using an integrated editor that is simple and intuitive and does not require any knowledge of special codes or tags. Searching for existing data on the site is as simple as selecting the terms describing the type of data the user is looking for and clicking the search button.