A Researcher-oriented Automated Data Ingestion Tool for rapid data Processing, Visualization and Preservation. (December 2017) - Hacker, Thomas; Dyke, Shirley; Ozdagli, Ali Irmak; Marshall, Gemez; Thompson, Christopher; Rohler, Brian; Yeum, Chul Min
Highlights: Motivation, architecture, and function of Experiment Dashboard (ED) software prototype are described. ED provided automated data ingestion, aligning with typical researcher laboratory procedures. ED was demonstrated for optical measurement applications in a structural engineering laboratory. Abstract: A select number of scientific communities have been quite successful in evolving the culture within their community to encourage publishing and to provide resources for re-using well-documented data. These data have great potential for analysis and knowledge generation beyond the purposes for which they were collected and intended. However, there are still barriers in this process. To explore this problem, we have developed a prototype tool: the Experiment Dashboard (ED), with the objective of demonstrating the ability and potential of enabling automated data ingestion from typical research laboratories. This innovative prototype was developed to create a novel system and artifact to explore the possibilities of allowing researchers in laboratories across the nation to link their data acquisition systems directly to structured data repositories for data and metadata ingestion. The prototype functions with commonly used data acquisition software at the data source and the HUBzero scientific gateway at the data sink. ED can be set up with minimal effort and expertise. In this paper, we describe the motivation and purposes for the prototype, the architecture we devised and functionality of this tool, and provide a demonstration of the tool for optical measurements in a structural engineering laboratory. The goal of this paper is to articulate and show through our prototype a vision for future cyberinfrastructure for empirical disciplines that rely on the rapid collection, analysis, and dissemination of valuable experimental data. We also discuss lessons learned that may be useful for others seeking to solve similar problems.