Presentation given at the South Central Chapter of the Medical Library Association Annual Meeting held October 2017 in Albuquerque, NM. Presentation won the Papers-1st place Elizabeth K. Eaton Research Award given by the South Central Chapter of the Medical Library Association (SCCMLA) and the South Central Academic Medical Libraries (SCAMeL).OBJECTIVE: As a means to embed in interdisciplinary research, the Biosciences Librarian found an opportunity to be involved in a research initiative called a Pop-Up Institute (PUI), Understanding Individual Population Variation in Biology, Medicine, and Society. This was a one-month interdisciplinary research team that would work towards 1) identify the most promising questions about individual ...
As science becomes more data-intensive and collaborative, researchers increasingly use larger and mo...
Across the disciplines, from physical sciences to social sciences to digital humanities, researchers...
Big data analysis challenges include capturing data, data storage, data analysis, search, sharing, t...
Big data includes data sets with sizes beyond the ability of commonly used software tools to capture...
The enthusiasm for big data is obscuring the complexity and diversity of data in scholarship and the...
Arcot Rajasekar, PhD, is Professor in the School of Information and Science, Chief Scientist for the...
Big Data is a live issue in e-commerce and market intelligence, e-government and politics, national ...
Big data offer a wealth of research opportunities across the scholarly disciplines. Little data simi...
Research and innovation are constant imperatives for the healthcare sector: medicine, biology and bi...
Big Data is a collection of massive and complex data sets and data volume that has characteristics s...
These slides support the oral presentations of Gordon Springer and Prasad Calyam delivered at Cyberi...
Issue of Big Data was already raised by Fremont Rider, an American Librarian from Westleyan Universi...
The emerging Age of Big Data 2.0 promises myriad imagined and yet-to-be-imagined opportunities for t...
Big Data promises huge benefits for medical research. Looking beyond superficial increases in the am...
With growing concerns that big data will only augment the problem of unreliable research, the Labora...
As science becomes more data-intensive and collaborative, researchers increasingly use larger and mo...
Across the disciplines, from physical sciences to social sciences to digital humanities, researchers...
Big data analysis challenges include capturing data, data storage, data analysis, search, sharing, t...
Big data includes data sets with sizes beyond the ability of commonly used software tools to capture...
The enthusiasm for big data is obscuring the complexity and diversity of data in scholarship and the...
Arcot Rajasekar, PhD, is Professor in the School of Information and Science, Chief Scientist for the...
Big Data is a live issue in e-commerce and market intelligence, e-government and politics, national ...
Big data offer a wealth of research opportunities across the scholarly disciplines. Little data simi...
Research and innovation are constant imperatives for the healthcare sector: medicine, biology and bi...
Big Data is a collection of massive and complex data sets and data volume that has characteristics s...
These slides support the oral presentations of Gordon Springer and Prasad Calyam delivered at Cyberi...
Issue of Big Data was already raised by Fremont Rider, an American Librarian from Westleyan Universi...
The emerging Age of Big Data 2.0 promises myriad imagined and yet-to-be-imagined opportunities for t...
Big Data promises huge benefits for medical research. Looking beyond superficial increases in the am...
With growing concerns that big data will only augment the problem of unreliable research, the Labora...
As science becomes more data-intensive and collaborative, researchers increasingly use larger and mo...
Across the disciplines, from physical sciences to social sciences to digital humanities, researchers...
Big data analysis challenges include capturing data, data storage, data analysis, search, sharing, t...