Creating Actionable Data from an Optical Depth Measurement Network using RDF

The AEROCAN sunphotometery network has, for more than a decade, generated optical indicators of aerosol concentration and size on a regional and national scale. We believe this optical information can be rendered more “actionable” to the health care community by developing a technical and interpretative information-sharing geospatial strategy with that community. By actionable data we mean information that is presented in manner that can be understood and then used in the decision making process. The decision may be that of a technical professional, a policy maker or a machine. The information leading up to a decision may come from many sources; this means it is particularly important that data are well defined across knowledge fields, in our case atmospheric science and respiratory health science. As part of the AEROCAN operational quality assurance (QA) methodology we have written automatic procedures to make some of the AEROCAN data more accessible or “actionable”. Tim Berners-Lee has advocated making datasets, “Linked Data”, available on the web with a proper structural description (metadata). We have been using RDF (Resource Description Framework) to enhance the utility of our sunphotometer data; the resulting self-describing representation is structured so that it is machine readable. This allows semantically based queries (e.g., via SPARQL) on our dataset that in the past were only viewable as passive Web tables of data.