The National Institute of Health (NIH) is determined to reduce the cost and time it takes to discover viable therapeutic targets, which drive the changes in the molecular networks leading to the signs and symptoms of Alzheimer’s disease. NIH is leading the U.S. Food and Drug Administration and various other industry and academic scientists in a public-private partnership effort to create a Big Data portal for Alzheimer’s drug discovery. This Accelerating Medicine Partnership for Alzheimer’s disease (AMP-AD) Knowledge Portal is public so it will enable sharing, transparency, reproducibility, and analysis of large biomedical datasets. The hope is that it will shorten the time between discovery of potential drug targets to development […]
The goal of the Computing Community Consortium (CCC) is to catalyze the computing research community to debate longer range, more audacious research challenges; to build consensus around research visions; to evolve the most promising visions toward clearly defined initiatives; and to work with the funding organizations to move challenges and visions toward funding initiatives. The purpose of this blog is to provide a more immediate, online mechanism for dissemination of visioning concepts and community discussion/debate about them.
Archive for the ‘big science’ category
Contributions to this post were made by Lorenzo Alvisi, Computing Community Consortium (CCC) Council Member and Professor in the Department of Computer Science at UT Austin and Robbert van Renesse, Principal Research Scientist in the Department of Computer Science at Cornell University. Imagine slipping into a presentation that has already started and finding a seat in the back. The speaker is pointing at her slides explaining the diagram but you can barely hear her from the back of the room. All the sudden your cell phone, which you had placed on the table when you took your seat, begins to project the speaker’s voice. Now you can watch the speaker and […]
The AAAS Science and Technology Policy Fellows at the National Science Foundation (NSF) have organized a new seminar series on Data Science, Big Data, and Internet of Things. The series is a monthly one-hour informational presentation that is open for all to attend in person or online. Michael Franklin from UC Berkeley will be the inaugural speaker tomorrow, Wednesday January 21, from 11:30am to 12:30pm EST. Franklin is the Thomas M. Siebel Professor of Computer Science and Chair of the Computer Science Division of the EECS Department at UC Berkeley. He is director of the Berkeley AMPLab, a 70+ person effort fusing scalable computing, machine learning, and human computation to make sense […]
Ever wondered what was going on in the data science community with relation to biomedical research? Ever wish to share your own knowledge about the field? No need to worry any longer! The National Institutes of Health (NIH) has a new data science blog which “is the beginning of a more coordinated and push-oriented communication strategy.” The purpose is to distribute information to the data science community “to foster an ecosystem that enables biomedical research to be conducted as a digital enterprise that enhances health, lengthens life, and reduces illness and disability.” The Associate Director for Data Science (ADDS) Phil E. Bourne, contributed the blog’s first post with his 2014 review of […]
The National Institutes of Health (NIH) Big Data to Knowledge (BD2K) program has announced two new funding opportunities for FY15 funding. NIH Big Data to Knowledge (BD2K) Initiative Research Education: Massive Open Online Course (MOOC) on Data Management for Biomedical Big Data (R25) RFA-LM-15-001 This FOA will support the creation of a massive open online course (MOOC) that can be used by librarians, faculty, students and others to learn concepts, approaches and best practices in the area of data management, and also used in conjunction with local training activities about the management of biomedical Big Data. One award is expected. Application receipt date is March 17, 2015. NIH Big Data to Knowledge […]
Data sets are growing rapidly. Yahoo, Google, and Amazon, work with data sets that consist of billions of items. The size and scale of data, which can be overwhelming today, will only increase as the Internet of Things matures. Data sets are also increasingly complex. It is becoming more important to increase the pool of qualified scientists and engineers who can find the value from the large amount of big data. The National Academies released a report on training students to extract value from big data based on a Committee on Applied and Theoretical Statistics (CATS) workshop that occurred in April 2014. From the report: Training students to be capable in exploiting big data requires experience […]