Driven by recent trends across various government and industry sectors, universities around the world seem to be in the midst of a global shift towards large-scale, interdisciplinary, data-driven research focussed on tackling Grand Challenges; ambitious but achievable goals that harness science, technology, and innovation to solve national and global problems in health, climate studies, urban development, science, and society. Nowhere is this more evident than in the US where a number of White House Office of Science and Technology Policy initiatives have set global trends in big-data challenges in universities and research labs alike. In 2012 the US Administration announced its US$200 million dollar Big Data Research and Development Initiative, to drive scientific discovery and growth in research applications and to build capacity in transformational and digital technologies. In 2013, the Grand Challenges of the 21st Century initiative was launched to foster collaboration between organisations, industries, and research universities. This past September, the OSTP announced a new Smart Cities initiative that will see US$160 million federal investment in smart cities research, including intelligent transport and urban design, impacts on climate, economic growth and improved service delivery in cities. The rise of data science and interdisciplinary research institutes reflects this shift in attitudes and priorities of government and national funding bodies that view "big-data" as being a valuable commodity and the rapid emergence of new tools and technologies for crunching through increasingly large amounts of data, as assets that should be exploited.
In November 2013, the Gordon and Betty More Foundation announced a bold new partnership to harness the potential of data scientists and big data for basic research and scientific discovery. They launched three interdisciplinary Data Science Institutes at New York University, the University of California – Berkeley and the University of Washington with funding from the Gordon and Betty Moore Foundation and Alfred P. Sloan Foundation. This is five-year, $37.8 million cross-institutional effort to bring data science to the forefront of cross-disciplinary academic research.
More recently, the UK announced its Internet of Things (IoT) Initiative to establish Britain as the global leader in the development and deployment of cutting edge internet technologies. The UK Government has invested £24 million in IoT research, with £9.4 million coming from the Engineering and Physical Sciences Research Council (EPSERC) to kickstart new research programs at leading UK institutions. The additional ~£14 million in funding comes from industry partners, businesses, NGOs and the nine partner universities (~£4 million). The research consortium (PETRAS IoT Hub) is led by University College London (UCL), with Imperial College London, Lancaster University, University of Oxford, University of Warwick, Cardiff University, University of Edinburgh, University of Southampton, and University of Surrey.
Since then, a number of data science institutes, interdisciplinary research centres and data-focussed co-operative research centres (Australian CRCs) have popped up around the world. Many have industry partners, including NVIDIA, Siemens, Intel, Microsoft, IBM Research, NSF and NASA.
Mapping the rise of data science institutes around the world has been on my to do list for quite a while. My last six months at Swinburne was spent working with the Deputy Vice-Chancellor (Research & Development) to establish a small number of interdisciplinary research institutes at Swinburne. The reasoning for the new model was similar to the motivations behind other data science institutes; interdisciplinary research institutes bring together a variety of expertise across the University, they foster new ideas and collaborations, can be used to drive growth in key areas, they provide a forum for showcasing innovative research and better engaging with industry, and they can exploit the power of "data–driven discovery". My role as project manager was to coordinate the various working groups involved in the process, develop establishment and secondment policies for the Institutes (and revise those for existing research centres), develop the management and governance structures, and co-author and present (with the DVC–R&D) the Swinburne Institutes Model Proposal to the various stakeholders across the University. Throughout the process we looked at governance and management structures of a number of data science institutes around the world, their funding models, core research activities, and the industry partners supporting them.
Mapping these institutes is an interesting exercise for a number of reasons;
- It shows how the trend has spread across the world,
- It raises awareness that these institutes exist – only a handful have received significant attention from the press, and
- It's useful for identifying potential collaborations and industry partners.
Carto is a great choice for mapping, purely because of it's ease and simplicity in design.
The data for the the various data science and interdisciplinary research Institutes was taken from institute webpages. The header images come from each institutes Twitter profiles (no image means no Twitter profile). It's interesting to note that social media plays a significant role in raising awareness of each institute. Only a handful of institutes have received significant attention in the press. These tend to be those at high profile universities (e.g. Berkeley, Caltech, University of Washington), or funded by major initiatives.
I also included technology companies that are hiring researchers as data scientists. There is a growing trend of hiring researchers directly from well known data science institutes, or via programs such as Insight Data Fellows, Science to Data Science and Data Incubator. A second SQLite database was created for this data. To date the map includes just a handful of companies (~20/100) that currently hiring (or have previously hired) data scientists. The list of companies is taken from the Insight Data science Fellows alumni web page. Gathering the data takes time, so this is a work in progress. I'll keep adding to this over the next few months.
the map of data-science institutes around the world
Data to Decisions CRC, Melbourne and Adelaide / The UNSW Big Questions Institute, University of New South Wales / Institute for Future Environments (IFE), Queensland University of Technology / Institute of Health and Biomedical Innovation (IHBI), Queensland University of Technology / Advanced Analytics Institute, University of Technology Sydney / Centre for Data Science, Monash University
U.S.A. & Canada (13)
Berkeley Institute for Data Science (BIDS), University of California / Center for Data Science (CDS), New York University / eScience Institute, University of Washington / The Institute for Data Intensive Engineering and Science (IDIES), Johns Hopkins University / Centre for Data-Driven Discovery, Caltech / Goergen Institute for Data Science, University of Rochester / Data Science Institute, Columbia University / Data Science Institute, University of Virginia / Michigan Institute for Data Science, University of Michigan / Data Science at IQSS, Harvard University / Institute for Data Science, Carleton University / MIT Institute for Data, Systems and Society, Massachusetts Institute of Technology / Stanford Data Science Initiative (SDSI), Stanford University
Europe & Middle East (15)
Oxford e-Research Centre, University of Oxford / Data Science Institute, Imperial College London / Alan Turing Institute, British Library / UCL Big Data Institute (University College London) / Data Science Institute, University of Lancaster / Institute for Analytics and Data Science, University of Essex / Data Science Institute, University of Bournemouth, / Data Science Center Tilburg, University of Tilburg / Tel Aviv University Data Science Center, Tel Aviv University / Leiden Centre for Data Science, Universiteit Leiden / InterDisciplinary Institute of Data Science, Università della Svizzera italiana / Data ScienceTech Institute / Edinburgh Data Science, University of Edinburgh /Warwick Data Science Institute (WDSI), University of Warwick