The Data Quality Screening Service (DQSS) is designed to help automate the filtering of remote sensing data on behalf of science users. Whereas this process today involves much research through quality documents, followed by laborious coding, the DQSS can act as a Web Service to provide data users with data pre-filtered to their particular criteria, while at the same time guiding the user with filtering recommendations of the cognizant data experts.
The project goals are to develop an easy-to-use data screening tool for NASA’s Remote Sensing data, particularly Level 2 (swath/scene/orbit) data.
DQSS is designed to screen data using both ontologybased criteria and user selections of quality criteria (such as minimal acceptable QualityLevel). Data that do not pass the criteria are replaced with fill values, resulting in a file that has the same structure and is usable in the same ways as the original.
At the core of DQSS is an ontology that describes data fields, the quality fields for applying quality control and the interpretations of quality criteria. This allows a generalized code base that can nonetheless handle both a variety of datasets and a variety of quality control schemes. A data collection can be added to the DQSS simply by registering instances in the ontology if it follows a quality scheme that is already modeled in the ontology, so long as the data are stored in Hierarchical Data Format Version 4 or 5. New quality schemes can be added by extending the ontology and adding code for each new scheme. Note that extending DQSS to work with additional datasets requires a thorough grounding in semantic web technologies, HDF and Java.
DQSS is designed to be integrable into a variety of Web Services frameworks. The DQSS code distribution does not include a User Interface as this must usually be integrated into a data provider’s search interface. However, DQSS can also be used by end users to run from a command line, using an XML file to specify the quality criteria.