Instructors: Dav Clark, Javier Rosa & guests from industry, the social sector and academia
We identified 4 islands - Moorea, Kauai, Friday Harbor (San Juan Island), and the Galapagos islands - to demonstrate the proejct idea. After reading an article on biodiversity studies, we defined a metric for completeness and collected biodiveristy data on birds regarding these islands. Using leaflet.js for maps, we constructed a simple tool for comparing the bird biodiversity among the islands. The tool is static, but it demonstrates the project’s intent of allowing biodiversity analysis and comparisons to promote data sharing and research collaboration.
This will be phase 1 of a larger project to construct species lists, food webs and associated citations.
As large biodiversity collections and environmental data are accessible online, global research communities have an unprecedented access to (siloed) datasets. Now that methods are within reach that allow to combine and process biodiversity data at global scales, institutions can start to re-examine existing data to coordinate data collection efforts, evolve data sharing strategies and discover methods to efficiently sustain our (island) ecosystems. A first step toward integrating the data is to provide a side-by-side comparison of existing data associated with active island ecostation communities to stimulate knowledge sharing and collaboration.
Ecostation biodiversity data summaries are derived from openly available biodiversity data repositories (e.g. GBIF, iDigBio, GloBI). Initially only species lists and associated food webs are compiled for participating ecostations using automated data processing algorithms. For each ecostation, the completeness of the lists and webs are estimated. Also, the similarity of the lists and webs are calculated across the spatially separated island ecosystems to highlight ecological likeliness.
By providing EDAM, spatially and institutionally disjoint projects now have a data-driven method to see how much ecological data is available for specific spatio-taxonomic spaces. We hope that comparing available ecological data across ecostations will help stimulate collaboration between scientists, technologists, educators, local governments and research foundations to help better understand and sustain ecosystems around us.
In order to archieve EDAM Phase I, we need to:
|Jorrit Poelen||@jhpoelen||freelance software engineer building open tools for open data|
|Jonathan Wang||@jonathanwang017||junior studying CS / Stats|
|Nisreen Hejab||@nhejab||Ph.D student in Biophysics/Structural Biology|
|Carlo Liquido||@koalaboy808||Graduate student in School of Information|
|Jong-kai Yang||@GitOnion||Graduate student in School of Information|
|Vedant Saran||@vedants||Freshman studying EE/CS|
Given that the data is already available and the limited scope of needed data processing capabilities, a first prototype of EDAM Phase I is estimated to take 2-3 months for a group of digitally literate graduate students with allocation of ~10hrs a week. The outcome of this project will help define future funding to further develop advanced phases of the EDAM project.