We provide a comprehensive report on public sentiment towards big data as part of work package 2 of the Big data roadmap and cross-disciplinarY community for addressing socieTal Externalities (BYTE) project. The BYTE project aims to assist European science and industry in capturing the positive externalities and diminishing the negative externalities associated with big data in order to gain a greater share of the big data market by 2020. Public sentiments play a role in science and industry gaining a greater share in the big data market.
Public sentiments include perceptions of, and aspirations for, information practices relating to big data. The public sentiments towards big data practices are relevant to big data actors operating in the case study areas examined by the EU-FP7 funded BYTE project, including:
- Environmental data
- Crisis informatics
- Transport data
- Utilities/ Smart cities data
- Cultural data
- Energy data
- Health data
Big data practices supporting the collection, storage and use of personal data have become a part of everyday life at all levels of society and users have raised concerns in relation to these processes. Particular concerns are the privacy and security of personal data, as well as a general distrust of those handling big data, particularly private sector companies. We find these sentiments to be particularly important because they can indicate the extent to which the public, as a major source of data, willingly contribute to the big data process currently, and how willing they may continue to be.
We examine practices such as data collection, data storage, data sharing (including selling) and data analysis. There tends to be more negative sentiment towards the information practices that the general public has a stronger connection with, such as the point of collection, as they play an active role at this initial stage. Whilst there does not appear to be any overwhelmingly negative sentiments about specific practices that follow the collection of their data, aside from privacy invasive practices, this may be because users tend to be less informed about, and more removed from, specific big data practices such as data analysis, data storage and the selling and sharing of data.
What these perceptions mean for companies and organisations is the need to foster a growing awareness to better inform their users with more transparent policies concerning the subsequent use of the data, as well as the benefits that can flow from information technology practices.
We also consider public aspirations towards big data by looking at what relevant information can tell us about how members of the public would like big data to operate in a manner that causes the least number of negative implications for them. Personal benefit is the strongest incentive for being in favour of the collection and use of personal data by government and companies. This is particularly true when a tangible public benefit is readily identified, such as when data use produces improvements in public security or where developments in health care treatment and diagnostics are achieved. Conversely, if the public see little benefit from sharing their data and little confidence that they will see benefits in future, this may hinder the amounts of data available to big data actors into the future thereby, threatening the longevity of the European big data industry.
The big data industry can benefit by fostering a more positive interaction between big data actors and users. We suggest that one of the ways in which this can be achieved is through the recognition of public aspirations, particularly the delivery of benefits and transparent practices, by incorporating them big data practices and policies. This is also reflected in the suggestions we make in relation to a good practice framework that takes into account privacy and security concerns.
The big data industry must find ways to ensure that citizens, as a major data source, continue to comfortably and securely contribute to large data sets. Positive public sentiments towards big data are imperative to the continuation of data processing activities processes, and the future of big data as a value adding institution/ process.
This research is funded by the European Union under grant number 619551.