Puneet Kishor presented at AGU2010 in San Francisco, CA.
Abstract: Large-scale terrestrial ecosystem modeling is highly parameterized, and requires lots of historical data. Routine model runs can easily utlize hundreds of Gigabytes, even Terabytes of data on tens, perhaps hundreds of parameters. It is a given that no one modeler can or does collect all the required data. All modelers depend upon other scientists, and governmental and research agencies for their data needs. This is where data accessibility and interoperability become crucial for the success of the project. Having well-documented and quality data available in a timely fashion can greatly assist a project's progress, while the converse can bring the project to a standstill, leading to a large amount of wasted staff time and resources. Data accessibility is a complex issue -- at best, it is an unscientific composite of a variety of factors: technological, legal, cultural, semantic, and economic. In reality, it is a concept that most scientists only worry about when they need some data, and mostly never after their project is complete. The exigencies of the vetting, review and publishing processes overtake the long-term view of making one's own data available to others with the same ease and openness that was desired when seeking data from others. This presentation describes our experience with acquiring data for our carbon modeling efforts, dealing with federal, state and local agencies, variety of data formats, some published, some not so easy to find, and documentation that ranges from excellent to non-existent. A set of indicators are proposed to place and determine the accessibility of scientific data -- those we are seeking and those we are producing -- in order to bring some transparency and clarity that can make data acquisition and sharing easier. The paper concludes with a proposal to utilize a free, open and well-recognized data marks such as CC0 (CC-Zero), Public Domain Dedication License, and CC-BY created by Creative Commons that would advertise the openness of scientific data to everyone.



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