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At the present time, big data is largely comprised of two types of data resources:
Dark data – which refers to vast, un-used and un-mined lakes of data
Data exhaust – which refers to the residual data that is the product of the completion of other processes, services, etc. – e.g., location data from navigation services, etc.
Dark data may be comprised of data exhaust, and some data exhaust may lie dormant as dark data.
However, the key to uncovering new information, capturing innovation and identifying efficiencies is to transform these data into Found data.
Found data (adapted from the Financial Times article “Big data: Are we making a big mistake?”, 28 March 2014) – Data elements that, when linked or processed, yield new connections and insights
However, we must always be aware of the negative impacts that could result from these mobilisations – e.g., potential for discrimination, spurious relationship that could lead to poor decision-making, etc.
BYTE aims to support stakeholders in mobilising big data and taking advantage of the associated opportunities, whist diminishing the potential negative externalities that could also result.
Production of a roadmap outlining a plan of action to enable European scientists and industry to capture a proportionate share of the big data market.
Provision of assistance to industry in capturing positive externalities (efficiencies, new business models, etc.) and addressing potential negative externalities before beginning a project, initiative or programme.
A series of clear and precise future research needs and policy steps
Bullet one – how we define an externality – as an “impact”
Public opinion surveys reveal that citizens are concerned about many of these issues, especially privacy and data protection.
The aim of the community is to be as large as possible. As such, we welcome all of the other projects, networks and initiatives into the BYTE big data community.
Bringing together social scientists with practitioners across industrial sectors
BYTE will gather information from big data projects, initiatives, etc. and disseminate this information to other, related organisations, including standards organisations, policy projects, technology initiatives, etc.