Legal and Technical Long Term Aspects of Big Data

and Knowledge Banji Adenusi

September 2015

Delivered at the Information Science, Security and Computing Class EULISP 2015, Leibniz University Hannover

Outline •  Big data phenomenon

•  Infographics

•  Technical aspects

•  Legal aspects

•  Video: An intro to the legal implication of big data

•  Further Reading

Big Data Phenomenon

“Big data is high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation.”

- Gartner IT Glossary

A misnomer and industry jargon for large data or information that represents an exponential increase in the scale and scope of knowledge about a given subject matter.

”Big Data Word Bubble" by Rachel Serpa

“data sets that are too large and complex to manipulate or interrogate with standard methods or tools”

- Oxford English Dictionary

An umbrella term

The next frontier for innovation, competition and productivity

– McKinsey Global Institute

”Big Data Word Bubble" by Rachel Serpa

Volume

•  Amount of data (data at scale)

•  Datasets between 1TB and 1PB or more

Velocity

•  Many forms of data and data sources

•  Structured, semi-structured and un-structured data

Variety •  Data in motion •  Real time data

creation, streaming and analyses

Veracity

•  Valuable but uncertain information

•  Creating context for uncertainty (data fusion & optimization)

In the same manner in which social media has shaped the world around us, Big Data will similarly have a substantial impact on our present-day reality.

Infographics ”Big Data Word Bubble" by Rachel Serpa

Evolution of Big Data – An IBM Expose´

”Infographic" by IBM Big Data & Analytics Hub ”Big data infographic" by Wikibon blog

Technical Aspects of Big Data

Heterogeneity of data Inconsistency and incompleteness Scale & timeliness Collaboration Privacy

Data volume scaling faster than compute resources. Processor technology, move towards cloud computing and transformative change of the I/O technology. The larger the data set to be processed, the longer it will take to analyze.

Machines expect homogenous, structured data. Human information is however heterogeneous and unstructured.

Managing data privacy is both a technical and sociological issue. Location based services typically broadcast user data without permission.

Human collaboration is necessary for big data, especially for data analyses and interpretation. Crowd-sourced data can contain errors and uncertainty

What happens if one or more pieces of information is unavailable? Even after data cleaning and error correction, some incompleteness and some errors in data are likely to remain

Legal Aspects • Central concern is with respect to Intellectual Property rights and ownership in relation to data Data Creator

•  Central concern is in relation to privacy and data protection. Is consent of the individual required in data mining, use and re-use?

The User/customer

•  Motivated by profit and monetary gains, and establishing monopolies.

The corporation

• Data creation & exploitation • What is copyrightable (mass digitization projects)? • Database rights? • Property rights? • Liability for incorrect data

Ownership & IP Rights

• Digital data (right to be forgotten) • Scope of lawful data processing • Personality rights? • Privacy by design (PbD) • Need for consent? • EC Directive 95/46/EC

Data Protection & Privacy • Free and unrestricted access

to market • Issues around primary and secondary market • A common legal framework? • Draft EC Trade Secrets Directive 2013

Competition & regulation

An intro to the legal implications of Big Data

https://youtu.be/-ub0KO55Y1g?t=3

Further Reading •  Laney, Douglas. 3D Data Management: Controlling Data Volume, Velocity and Variety (PDF). Gartner. Retrieved 10 September 2015 at

http://blogs.gartner.com/doug-laney/files/2012/01/ad949-3D-Data-Management-Controlling-Data-Volume-Velocity-and-Variety.pdf

•  Computing Research Association. White Paper on Challenges and Opportunities with Big Data. 2015. Last accessed on 10 September 2015 at

http://cra.org/ccc/wp-content/uploads/sites/2/2015/05/bigdatawhitepaper.pdf

•  McKinsey Global Institute. Big data: The next frontier for innovation, competition, and productivity. 2011. Last accessed on 10 September 2015 at

http://www.mckinsey.com/insights/business_technology/big_data_the_next_frontier_for_innovation

•  World Economic Forum. Big Data, Big Impact: New Possibilities for International Development. 2012. Last accessed on 10 September 2015 at

http://www3.weforum.org/docs/WEF_TC_MFS_BigDataBigImpact_Briefing_2012.pdf

•  Ascent. Digital Preservation in the Age of Cloud and Big Data. 2015. Last accessed on 10 September 2015 at

https://atos.net/content/dam/global/ascent-whitepapers/ascent-whitepaper-digital-preservation-in-the-age-of-cloud-and-big-data.pdf

•  NESSI. White Paper on Big Data A New World of Opportunities. 2012. Last accessed on 10 September 2015.

http://www.nessi-europe.com/Files/Private/NESSI_WhitePaper_BigData.pdf