My near-term research goals are focused on the issue of trustworthiness in our data practices — a fundamental issue in research, and particularly in open science. The first goal is to understand the incentive system of narrative text and begin to apply natural language processing and machine learning algorithms to identify and extract structured methodologies. This work will benefit data rescue, long-tail data publication, and reusability and reproducibility, all while lowering the burden on researchers. The ultimate goals is to be able to provide unstructured texts for publication and knowledge transfer while simultaneously generating the structured metadata needed for data platforms — and to do that in a (semi-)automated way. The second goal is related to a more pragmatic solution for semantically enabling data values, effectively, to get at data quality information of a surface related to that semantic content. Ultimately, we want to be able to take advantage of a system built on top of point clouds to reason efficiently about data values.
CV available here: sscott_2015_cv