This subcontract will support personnel at the Institute for Research on Innovation and Science (IRIS) to contribute to the completion of the proposed project. IRIS is an IRB-approved data repository that anchors a consortium of more than 30 research universities who provide unique micro-data to support research and reporting to understand, explain, and improve the public value of academic research. Personnel at IRIS who are supported under this subcontract will contribute to the development of linked data to support the proposed ?big data analytics? class in the following ways:
? Prepare, document, and share via the NYU ADRF a panel data set derived from the Bureau of Labor Statistics Quarterly Census of Employment and Wages. The dataset will be organized as a county X year X NAICS panel and will include location quotient measures of the geographic intensity of employment, establishments and revenue by two digit NAICS code. The resulting dataset and documentation will be sufficient to support analyses of the effects of local industry demand on career outcomes of SED/SDR respondents by teams participating in the proposed class.
? Prepare, document, and share via the NYU ADRF a panel dataset derived from the National Science Foundation Higher Education Research and Development (HERD) survey. This dataset will be organized as an institution X year panel and will include information on the research intensity and institutional characteristics of higher education institutions that perform federally funded research. The dataset will also include multiple NSF and NCES identifiers for institutions to facilitate institution-level linkage to SED/SDR and analysis of institutional effects on doctoral student career outcomes by teams participating in the proposed class.
? Prepare, document and share via the NYU ADRF a de-identified panel dataset derived from the Universities Measuring the EffecTs of Research on Innovation, Commercialization, and Science (UMETRICS) dataset created and maintained by IRIS. This dataset will be a coded-deidentified individual X year panel for graduate students paid by sponsored projects at every participating UMETRICS university. The dataset will include coded identifiers suitable for hashed record linkage to SED/SDR, along with indicators for blocking and measures of funding sources, intensity and team composition sufficient to enable analysis of funding effects on graduate career outcomes by teams participating in the proposed classes.
? Consult on data linkage, documentation and preparation of unified analytic datasets in the NYU ADRF to support the proposed big data analytics course.
? Participate in one day of the proposed course to introduce the UMETRICS and other IRIS provided data.