Data Ownership in the Big Data Context

Who own the data in the Big Data context? What does ownership in the Big Data context mean?


Data Ownership –

Ann Racuya-Robbins 2016 06 10

Data ownership means that the data subject owns the majority of the revenues generated from data that emanates/ed from or was built upon the data subject’s data. A data subject is a living being. This kind of ownership would mean that the data subject has the authority over decisions including development and disposition of the data subject’s data.

Also see the Individuals Trust Frame Work

Big Data Governance

Big Data Governance

However large and complex Big Data ultimately emerges to become in terms of data volume, velocity, variety and variability, Big Data Governance will in some important conceptual and actual dimensions be much larger. Data Governance will need to persist across the data lifecycle; at rest, in motion, in incomplete stages and transactions all the while serving the privacy and security of the young and the old, individuals as companies and companies as companies—to be an emergent force for good. It will need to insure economy, and innovation; enable freedom of action and individual and public welfare. It will need to rely on standards governing things we do not yet know while integrating the human element from our humanity with strange new interoperability capability. Data Governance will require new kinds and possibilities of perception yet accept that our current techniques are notoriously slow. For example, even as of today we have not yet scoped-in data types.

The reason we, so many of us, are gathering our energies and the multiplexity of our perspectives is that we know Big Data without Big Data Governance will be less likely to be a force for good. It may come to be said that the best use of Big Data is Big Data Governance.

What concept or concepts are powerful enough to organize, cohere and form an actionable way forward? Are we brave enough to push forward a few concepts for our discussion?  Some think data provenance, curation and conformance are the way forward. I agree with those that think this ground deserves a fifth V — Value.

The Human Trust Experience in an Era of Big Data

Consumer, Manager, Domain Expert Proposal
Subtopic: Unmet Big Data requirements

Ann Racuya-Robbins Image
tHTRX Logo graphic

1. Title
The Human Trust Experience (HTX) in an Era of Big Data

2. Point of Contact (Name, affiliation, email address, phone)
Ann Racuya-Robbins
World Knowledge Bank: Human Trust Experience Initiative

3. Working Group URL

4. Proposed panel topic: Unmet Big Data requirements

5. Abstract
The Human Trust Experience Initiative’s mission is to use Big Data to explore and lay the ground work for understanding the parameters, characteristics, attributes, information architecture, and reference and interaction models of the human trust experience in motion and at rest. Central premises of this work to be evaluated and interpreted are that:
• The human trust experience is foundational to Privacy, to the uptake of ICT innovation, education and the challenges of democratic governance.
• The human trust experience is a central component of all human labor and to individual and community well-being and survival.
• The human trust experience can be a measure and standard by which we understand and prioritize problem solving.

6. Working Group summary
• Create the human trust experience use case.
• Create the human trust experience context.
• Create a semiotics and information architecture of the human trust experience.
• Facilitate through CMS conversation about the tHTRX in a Big Data context.

7. Number of Participants, data working group began, frequency of meetings
December 2013

8. Target Audience
Individuals, Consumers and Producers of Big Data, Businesses, Government

9. Current initiatives
The Human Trust Experience Initiative

10. Specific Big Data Challenges:
Value, Valuation, Contextual Veracity, Identity, Pseudonymity, Anonymity, Privacy, Vetting, Contextual Vetting

11. Urgent research needs

12. Related Projects or Artifacts The Human Trust Experience: Informed Valuation Project

13. Big Data metrics (describe your data to make a Big impression)
Search, discovery, revelation, creation and analysis of the human trust experience from cyberspace data.

14. Keywords
human trust experience, value, valuation, informed valuation, informed contextual value, informed contextual valuation, contextual veracity, identity, pseudonymity, anonymity, privacy, risk management