Data Recipes -- How-To Guides for better Supporting Data Users

Abstract:

A complicating aspect to the use of Earth science data delivered to data archive centers is that these data are commonly found in different formats and structures. It is a great challenge to support Earth science research and applications with complex and fast growing datasets. To better support data users, both online and offline data services and tools are developing and improving continuously with new technology, intended to simplify finding, downloading, and working with “big science” data. Although most data services and tools have user guides, many users still experience difficulties with accessing or reading data, due to varying levels of familiarity with data services, tools, and/or formats. The data recipe project at Goddard Earth Science Data and Information Services Center (GES DISC) was initiated in late 2012 for enhancing user support. A data recipe is a “How-To” online explanatory document, with step-by-step instructions and examples of accessing and working with real data (http://disc.sci.gsfc.nasa.gov/recipes). The current suite of recipes has been found to be very helpful, especially to first-time-users of particular data services, tools, or data products. Online traffic to the data recipe pages is significant, even though the coverage of data recipe topics is still limited. An Earth Science Data System Working Group (ESDSWG) for data recipes was established in the spring of 2014, aimed to initiate an EOSDIS-wide campaign for leveraging the distributed knowledge within EOSDIS and its user communities regarding their respective services and tools. The ESDSWG data recipe group is working on an inventory and analysis of existing data recipes and tutorials, and will provide guidelines and recommendation for writing and grouping data recipes, and for cross linking recipes to data products. This presentation gives an overview of the data recipe activities at NASA GES DISC and ESDSWG. We are seeking potential collaborators from a broader data scientist community, as well as requirements and input from the data user community, to establish a strong knowledge base for supporting Earth science data research and application implementations.