Federal Big Data Summit Report - June 2016August 2016
Topics: Data (General), Government Agency Operations
The most recent installment of the Federal Big Data Summit, held on June 30, 2016, included five MITRE-ATARC (Advanced Technology Academic Research Center) Collaboration Sessions. These collaboration sessions allowed industry, academic, government, and MITRE representatives the opportunity to collaborate and discuss challenges the government faces in big data research and technologies. The goal of these sessions was to create a forum to exchange ideas and develop recommendations to further the adoption and advancement of big data techniques and best practices within the government.
Participants representing government, industry, and academia addressed five challenge areas in big data: the Intersection of Big Data and the Internet of Things (IoT); Driving Innovation with Big Data; Progress toward Prescriptive Analytics; Data Privacy: Challenges and Solutions; and Using Big Data and Analytics in Health Care.
This white paper summarizes the discussions in the collaboration sessions and presents recommendations for government and academia while identifying orthogonal points between challenge areas. The sessions identified detailed actionable recommendations for the government and academia which are summarized below:
- The government is taking on more and more data and new agencies are using data to drive their mission. This increasing dependency means agencies need to be fully prepared to take on data and should be planning for a data-driven future. Agencies need to have big data architectures, development sandboxes, and storage strategies in place.
- Big data is a rapidly expanding field in need of standards and regulations that can keep up with the technology. Standards are necessary for inter-agency communication and to establish trust and confidence in data science.
- Federal agencies also need to be prepared and have standards in place related to data privacy. Agencies are trusted with sensitive data, including health data. Individual identities need to be protected and information should be securely encrypted.