Technology Infusion for the Decadal Survey Era: Data Quality Capability Needs Based on information derived from the NASA Technology Infusion Working Group's decadal survey mission use cases, this session will explore candidate technologies and infusion strategies that could be applied to meet the technology needs of data systems for the decadal survey era missions. We focus on three key challenges arising from the use cases that relate to Data Quality: – How to communicate a clear, consistent, coherent model / terminology for Data Quality to the user community – How to develop a community consensus on the quality of datasets – Assessing the quality of custom data products (on demand)

Example Infusion Strategy: Local Space/Time Search Infusion of space/time search into processing workflow to prepare, discover, access, and stage local data. Use cases: need internal access to locally staged geospatial data within a data system – SMAP: look up locally staged ECMWF models and DEMs as ancillary geospatial data needed for workflow processing – InSAR processing: look up relevant raw frame (Level-0) data to generate swaths to form SLCs and then geocoded interferogram. Typical steps for infusion of a space/time search technology – Assess local data for available geospatial metadata – Setup data ingestion mechanism into search system metadata extraction and data storage – Setup query interface mechanism with constraints for space + time and perhaps keyword – Retrieve data based on metadata search results. – Stage found data for processing workflow.

Example Infusion Strategy: Data Quality Model How to communicate a clear, consistent, coherent model / terminology for Data Quality to the user community Use cases: need to address communication of data quality model with community – Data Producer: need to articulate ‘clear quality’ for accuracy (this is hard to determine); SMAP example (objective meas of DQ); known errors in measurements (but not how users use the info) – Users: application/edu use case to determine what part of the quality model they need to see (a huge number of cases needed) Typical steps for infusion of a semantic web based approach – Evaluate technology like UncertaintyML – Develop lots of use cases to cover variation in needs (user/producer); be sure to capture all that the producers can determine – Distill into ontology, terminology (hierarchy of uncertainty) – Communicate to user community – training; explore methods to communicate with science community on ‘science technology’ (no forum exists across disciplines for evaluation) – ?

Example Infusion Strategy: Dataset Quality How to develop a community consensus on the quality of datasets Use cases: need to address how to define and then acquire dataset quality via community consensus – Data Producer: ? – Users: capture how user uses dataset for a specific purpose and how well (quality) it worked (a social-based quality measure); examples of comments and what you learn about them; determine value of assessing relevancy of comments Typical steps for infusion of a collaboration/social media approach – ?

custom data products How to assess the quality of custom (e.g. on demand) data products