Home > Public Domain Data > BioBlitz and Citizen Science: Implications for Data Users

BioBlitz and Citizen Science: Implications for Data Users

During the past few days, I had the opportunity to participate in BioBlitz 2012 at Rocky Mountain National Park, Colorado, USA.  BioBlitz (http://www.nationalgeographic.com/explorers/projects/bioblitz/bioblitz-co-2012/) is a 10-year partnership between the US National Park Service and National Geographic with 3 goals:  Highlight the diversity of national parks by conducting a taxonomic inventory, public outreach, and to inspire young people to pursue careers in science and geography.  The citizen science focus to the event reinforced the concepts that Jill Clark and I wrote about in the book The GIS Guide to Public Domain Data.   Nowhere was this clearer than when I went into the field to collect and categorize macroinvertebrates in a montane stream in the shadow of Longs Peak with 40 students aged 11 to 13.

Collecting macroinvertebrates in stream, Rocky Mountain National Park

Collecting macroinvertebrates in stream, Rocky Mountain National Park.

After collecting the data over a period of five hours, the macroinvertebrate data was then identified by the students according to a detailed classification chart.  I was very impressed by the students’ diligence and teamwork.  The data was  then  input into a web-GIS called FieldScope, created by National Geographic and based in part on Esri technology, and viewable that evening online by anyone on the web.

Citizen science data being input into FieldScope

Citizen science data being input into FieldScope.

All told, hundreds of students, over 100 scientists, and thousands of the general public collected data for two days, resulting in over 400 bird, fungi, macroinvertebrate, animal, and vascular plant species that had never been documented in this particular national park before.

As citizen science projects gain in popularity, enabled by powerful yet easy-to-use web-GIS and field collection instruments, the challenge becomes:  How can data collected by a wide variety of people with a wide variety of backgrounds be managed and cataloged in such a way that is not only useful, but also, through metadata, allows people to understand who collected it, and how it was collected, categorized, and input into the GIS?

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