Principal Investigator David Karger
Co-investigators Stephen Buckley , Samuel Madden , Kent Larson , Alex 'Sandy' Pentland
Project Website http://livinglab.mit.edu.ezproxy.canberra.edu.au/
A key issue today is that data is siloed, whether its personal data, data inside an organization, or data sharing across different organizations. Data discovery and integration is difficult and presents complex technical, organizational and policy challenges. A Living Lab allows MIT to be a microcosm for many big data efforts whether in government or in industry. One of our goals is to work with MIT in opening up repositories of information on campus that contain the data needed to discover valuable new insights about important topics such as wellness, innovation, learning and sustainability. MIT is well positioned to take a leadership role in demonstrating not only how organizations can leverage data in the future, but how we collect, manage, and use personal information, from setting appropriate privacy policies to demonstrating systems that can implement it in practice.
Why a living lab for data?
Exploring technical issues and social implications of big data(*) Impacts and benefits of big data with a plethora of new applications(*) Large scale access control, data integration, data governance, analytics, and visualization(*) Understanding incentives and drivers of data collection(*) Demonstrating new approaches to managing data privacy
Leading efforts to safely develop and use big data(*) Enabling innovation and ownership by providing members of the MIT community appropriate access to their own data(*) Developing and demonstrating organizational best practices for collecting and managing information(*) Demonstrating systems that provide useful services to the MIT Community(*) Architecting services so that they are extensible and adaptable by industry and others
Living labs is developing a scalable data management platform, allowing us to collect and integrate multiple types of data including: personal data or “small data” (collected by smart phones, activity tracking devices, or new wearable sensors); MIT data (wifi data, campus maps, event data etc); as well as external data types (social media data, transportation data, weather, city data etc).