Big data for good

Martí Cuquet, Guillermo Vega-Gorgojo, Hans Lammerant, Rachel Finn, Umair ul Hassan.
D9.5 BYTE Project, 28 February 2017.
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The following document contains a summary of the externalities found in the BYTE case studies, the risks and opportunities of big data from a legal perspective, and the potential social benefits it can bring. The BYTE project is a multi-disciplinary study of the societal impacts of big data in seven European sectors aimed to define a roadmap and create a community that address and optimise these impacts. The goal of this Big data for good document is to present a concise summary of the BYTE results to support the community building process.

The BYTE project has observed positive and negative externalities in its case studies:

Crisis informatics examines the use of social media data to assist in humanitarian relief efforts during crisis situations.

Culture examines a pan-European cultural heritage organisation that acts as an aggregator of medata of European cultural heritage organisations.

Energy focuses on the impact of big data in exploration and production of oil and gas in the Norwegian Continental Shelf.

Environment, conducted in the context of an earth observation data portal (EarthObvs), a global-scale initiative for better understanding and controlling the environment, to benefit society through better-informed decision-making.

Healthcare focuses on the use of genetic data as it is utilised by a public health data driven research organisation.

Smart city focuses on the creation of value from potentially massive amounts of urban data that emerges through the digitalised interaction of a city’s users, i.e. of citizens and businesses, with the urban infrastructure.

Transport focuses on the increased availability and use of data in the maritime industry.

The externalities are divided into economic, social and ethical, legal and political externalities, and affect areas such as improved efficiency, innovation and decision making, changing business models, dependency on public funding, participation, equality, discrimination and trust, data protection and intellectual property rights, private and public tensions and losing control to actors abroad.

A special focus is given to the risks and opportunities coming from the legal framework and how to counter the negative impacts of big data, and also to the potential social benefits when data is used responsibly.

Big data practices affect the interactions between actors, and legal frameworks need to adapt to avoid negative externalities. To this aim, objectives of legal frameworks have to be clarified and evaluated to see if the framework is still effective, individual mechanisms have to be substituted by collective or aggregate ones, and as much as possible of the decision- making has to be moved to the design phase. Recommendations in these directions are presented for four specific legal frameworks: copyright and database protection, protection of trade secrets, privacy and data protection and anti-discrimination.

The potential social benefit is exemplified in six different domains: improved decision making and event detection, including efficient resource allocation; data-driven innovations, including new business models; direct social, environmental and other citizen benefits; citizen participation, transparency and public trust; privacy-aware data practices; and big data for identifying discrimination.

To conclude and capture these benefits, several best practices are suggested. These involve public investments and funding programs to solve the scarcity of European big data infrastructures, promote research and innovation in big data, open more government data and persuade big private actors to release some of their data as well, so data partnerships can be built around them, promoting of new data sources, business models and interoperability, and education policies to provide both highly skilled data scientists and engineers and generally data-savvy professionals and citizens.

@techreport{Cuquet2016_big,
  author = {Cuquet, Martí and Vega-Gorgojo, Guillermo and Lammerant, Hans and Finn, Rachel and ul Hassan, Umair},
  title = {Big data for good},
  institution = {BYTE Project},
  month = feb,
  year = 2017,
  number = {D9.5},
  type = {Project deliverable},
  doi = {10.5281/zenodo.1196862},
  url = {https://doi.org/10.5281/zenodo.1196862},
}