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Data Ownership

Overview#

Data Ownership is complex within the digital world.

Data Ownership

The Data Origin may need to share Data Ownership with the distribution chain of the data.

The first step toward open information markets is to give people Data Ownership. The simplest approach to defining what it means to "own your own data" is to go back to Old English Common Law for the three basic tenets of ownership, which are the rights of:

  • possession: You have a right to possess your data. Companies should adopt the role of a Swiss bank account for your data. You open an account (anonymously, if possible), and you can remove your data whenever you’d like.
  • use: You, the data owner, must have full control over the use of your data. If you’re not happy with the way a company uses your data, you can remove it. All of it. Everything must be opt-in, and not only clearly explained in plain language, but with regular reminders that you have the option to opt out.
  • disposal: You have a right to dispose or distribute your data. If you want to destroy it or remove it and redeploy it elsewhere, it is your call.

Data Ownership refers to both the possession of and responsibility for information.

Data Ownership is different#

When you sell an "Real" property, like a car, it is no longer yours. The new buyer can do anything they want with it and it will not affect you. Personal data is always going to be about you and the way your Personal data used will always matter to you.

This means normal property rights, or ownership, is generally no a useful way of thinking about the relationship between you and your Personal data about you. You need to always have rights about what is done with your Personal data.

Data Ownership Is Still New [1]#

There's just one little niggle with this ownership contract of ours: it was never designed to account for data. Historically speaking, the idea of even owning data is relatively new. The earliest copyright laws—which granted the Data Origin of a work exclusive rights to duplication and distribution of said work—first appeared in the early 18th century. It would still be hundreds of years, however, before the concept of "data" as we understand it even began to develop.

Ownership implies power as well as control. The control of information includes not just the ability to access, create, update, package, derive benefit from, sell or delete data, but also the right to delegate these privileges to others (Loshin, 2002).

Implicit in having control over access to data is the ability to delegate data with colleagues that promote advancement in a field of investigation (the notable exception to the unqualified sharing of data would be research involving human subjects). Scofield (1998) suggest replacing the term 'ownership' with 'stewardship', "because it implies a broader responsibility where the user must consider the consequences of making changes over 'his' data".

According to Garner (1999), individuals having Intellectual Property have Intellectual Property Rights to control intangible objects that are products of human intellect. The range of these products encompasses the fields of art, industry, and science. Research data is recognized as a form of Intellectual Property and subject to protection by U.S. law.

Paradigm of Ownership [2] #

David Loshin, in his book Enterprise knowledge management: The data quality approach . Morgan Kaufmann, 2001, described what he called the Paradigm of Ownership not with the intent of establishing who the legitimate Data Ownership should be, but to accent the complexity of ownership issues and to identify the list of parties laying a potential claim to data:
  • Creator – The party that creates or generate data
  • consumers – The party that uses the data owns the data
  • Compiler - This is the entity that selects and compiles information from different information sources
  • Enterprise - All data that enters the Enterprise or is created within the Enterprise is completely owned by the Enterprise (more in Law of agency)
  • Funder - the user that commissions the data creation claims ownership
  • Decoder - In environments where information is "locked" inside particular encoded formats, the party that can unlock the information becomes an owner of that information (Data Processor)
  • Packager (Data Processor) - the party that collects information for a particular use and adds value through formatting the information for a particular market or set of consumers
  • Reader as owner - the value of any data that can be read is subsumed by the reader and, therefore, the reader gains value through adding that information to an information repository
  • Subject as owner (Data subject) - the Data subject of the data claims ownership of that data, mostly in reaction to another party claiming ownership of the same data
  • Purchaser/Licenser as Owner – the individual or organization that buys or licenses data may stake a claim to ownership
These parties are generally considered the Data Provenance All of these Entities are at least Stakeholders in the data. In the copyright law of the United States, a work made for hire (law of agency) is a work subject to copyright that is created by an employee as part of their job, or some limited types of works for which all parties agree in writing to the Work For Hire designation. If a work is covered by law of agency, Legal Person serving as an employer not the employee is considered the legal Data Origin.

Redefining Data Ownership[3]#

Data is undeniably one of the world’s most valuable asset, and yet there lacks a clear definition of Data Ownership and an even less of a clear framework for claiming and protecting rights of ownership over this asset. Some define Data Ownership as having the right to control data and claim the profits generated from the data. The challenge is that since data can be easily copied by anyone, they could hold the same control over the data as the original owner. It is extremely difficult to clearly assert ownership and defend your rights as the legitimate owner of the data. Current solutions in the market for “secure” data exchange between two parties often rely on a trusted Third-party, such as a data Centralized Exchange. However, these “trusted” Third-party are profit-maximizing organizations with their own agendas, and are storing data in the absence of authorization, neglecting data privacy, and even engaging in data fraud.

More Information#

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