Tuesday, December 20, 2016
NIAID Scientists Advocate for Public Data Reuse and Crowdsourcing
New technologies are propelling increases in the volume and diversity of publicly available data, which can potentially be reused to address a variety of research questions. In the Dec. 20 issue of Immunity, NIAID researchers and their colleague from NIH’s Center for Information Technology advocate and outline strategies for broader data reuse and crowdsourcing in the immunology community. They review available data mining and analysis resources and tools and note the importance of developing platforms that are accessible to scientists without computational and statistical expertise.
The paper also highlights the “OMiCC Jamboree,” an exercise that the NIAID team conducted earlier this year to assess whether biologists without formal computational training could effectively use OMiCC, a free online crowdsourcing tool developed at NIAID, to explore public gene expression data. The Jamboree experience illustrates how OMiCC can facilitate data reuse, user education, and crowdsourcing, the researchers say. In addition, the data, annotation, and analysis results generated by the Jamboree, published separately under an open peer review model, provide a resource for the scientific community to explore autoimmune disease gene expression signatures.
Expanding the Immunology Toolbox: Embracing Public-Data Reuse and Crowdsourcing: Immunity
Expanding the Immunology Toolbox: Embracing Public-Data Reuse and Crowdsourcing
New technologies have been propelling dramatic increases in the volume and diversity of large-scale public data, which can potentially be reused to answer questions beyond those originally envisioned. However, this often requires computational and statistical skills beyond the reach of most bench scientists. The development of educational and accessible computational tools is thus critical, as are crowdsourcing efforts that utilize the community’s expertise to curate public data for hypothesis generation and testing. Here we review the history of public-data reuse and argue for greater incorporation of computational and statistical sciences into the biomedical education curriculum and the development of biologist-friendly crowdsourcing tools. Finally, we provide a resource list for the reuse of public data and highlight an illustrative crowdsourcing exercise to explore public gene-expression data of human autoimmune diseases and corresponding mouse models. Through education, tool development, and community engagement, immunologists will be poised to transform public data into biological insights.