Data ownership revisited: clarifying data accountabilities in times of big data and analytics

Figures & data

Table 1. Disciplinary perspectives on ownership and data ownership.

Discipline	Ownership concept	Objectives of data ownership
Law	Enablement and protection of rights with respect to one’s property (external) and identity (internal).	Ensure data privacy, while holding firms accountable for fraudulent data use.
Economics	Allocation of ownership rights for economic goods and their effect on market equilibriums as well as welfare.	Distribute property rights for data in the way that increases output and consumer welfare, while protecting individual privacy.
Management	Allocation of property rights to maintain an organisation’s survival and increase its value (Firm is owner of the data it collects and creates)	Define a firm’s accountability and assess its risk undertaking through data collection and monetisation.
Management information systems	Allocation of decision rights for IT artefacts to achieve a desired outcome.	Assign decision control rights for data among different organisational entities to increase value generation through data.

Table 2. Data ownership paradigms and discourses.

The socio-organisational context	The data ownership paradigm (Loshin, 2001)	Example	The related philosophical perspective on ownership (Hart, 2002)
Individual	Subject as owner	A private person accuses a company of selling his or her personal data to a third party	Libertarian theory: Ownership does not limit the freedom of others
Organization	Consumer as owner	A sales team uses customer phone numbers that are essential for its daily operation	First occupancy theory: Ownership by being the first to possess an object
	Reader as owner	A consultancy collects information on industry trends to extend its knowledge base
	Enterprise as owner	An enterprise creates, processes (adds value), and distributes data about its products	Labour theory: Ownership through value adding, either by own labour or owning labour
	Funding organisation as owner	A company pays a research company to collect panel data
	Purchaser/Licensor as owner	A company buys an address list of potential customers
	Creator/Generator as owner	A research firm invests in collecting qualitative data for a market study	Personality theory: Ownership through personal will to invest in an object
	Compiler as owner	A business intelligence department builds a central data warehouse
	Packager as owner	A web agency designs and formats a web page for a customer
	Decoder as owner	A company synthesises information from DNA data
Everyone	Everyone as owner	A crowdsourced collection of geo-information in a public database	Utility theory: Ownership maximises the benefits for all involved parties

Table 3. Selected cases.

Case name	Industry	Size	Key informants (years in the company)	Big data and analytics context
Company A	Fast-moving consumer goods	Revenue: 50 USDB to 100 USDB Employees: ~80,000	Manager: data governance (>10y), Enterprise data architect (1–5y)	Organisation: central data and analytics management organisation Infrastructure: central big data platform for innovation and industrialisation of analytics use cases
Company B	Public transportation and mobility infrastructure	Revenue: 1 USDB to 50 USDB Employees: ~35,000	Leader: Business information management (>10y), Data governance manager (6–10y), Big data platform architect (1–5y)	Organisation: central data management organisation and central/decentralised data science team Infrastructure: corporate data lake for data exploration/experimentation and the operation of analytics use case
Company C	Manufacturing	Revenue: 1 USDB to 50 USDB Employees: ~90,000	Director: Data architecture and engineering (6–10y), Project manager: Data platform (3y)	Organisation: corporate data management organisation and central platform team Infrastructure: central data platform to enable digital innovations and scale the operation of data products
Company D	Healthcare and life science	Revenue: 1 USDB to 50 USDB Employees: ~50,000	Leaders: Head of Data Products and Solutions (>10y), Global Enterprise Data Strategy Lead (1–5y)	Organisation: federated organisation with data and analytics centre of excellence and staff in line of business Infrastructure: Multiple data platforms serving specific analytics needs and an enterprise-wide data platform

Table 4. Data ownership in company A.

Data owner type	Description	Organizational assignment
Data source owner	“Primary decision-maker about the data entities under his responsibility and accountable for the overall integrity, data lifecycle and data quality of data created in his ownership”. “Provides approval for data usage in data product”. “Fulfils service-level agreements for data products”.	Head of a business function: director level or above
Platform owner	“Maintains the data sanity and business context while data are going through the technology stack”. “Oversees and controls work in data labs”. “He is accountable for the availability of data pipelines”.	Head of the digital analytics team
Data product owner	“Addresses the business need for data driven by analytics use cases”. “Accountable for the output of the technology stack”. “He ensures business value of data product over its lifetime”.	Head of a business function: director level or above

Table 5. Data ownership in company B.

Data owner type	Description	Organizational assignment
Data owner	“Responsible for data quality, definition, classification, security, compliance, and data lifecycle of data attribute, set of attributes, or dataset”. “Controls reading access to his data through data feed on big data platform and ensures compliant use through the provision of no-join policies under the respect of interests of existing and future data users”.	Business role
Owner of the data lake	“Accountable for the standardisation of the overall big data solution architecture. Proves compliance of analytics solutions”. “Gives information on planned extensions of the data lake”. “Ensures that new and valuable data are onboarded to the data lake according to the business need and potential. For this, he proactively searches for new data sources, valuates their business potential, and initiates the onboarding process”.	Big data solution architect
Owner of the data lab/data app/user home	“Manages access to the data lab, app, or user home, and is accountable for any activity (operational activity or data privacy) on it over its lifetime”. “Data scientists must comply with conduct of ethics when working with data in a data lab”.	Business role for the data app Technical role for the data lab/user home

Table 6. Data ownership in company C.

Data owner type	Description	Organizational assignment
Data domain manager	“Controls and monitors the data management for his domain”.	Business role: lower management
	“Receives requests for data processing and provides data for data usage”.
	“Reports errors and suggests improvements”.
Infrastructure owner	“Develops and operates the data platform”.	Corporate IT role: Head of the data platform team
	“Oversees the implementation and availability of data pipelines to onboard data to the data hub and to provision data to data solutions”.
Business logic owner	“Accountable for a data application over its lifetime, which includes compliant implementation, the maintenance of the data application, and support of users”.	Business or/and IT role: lower management

Table 7. Data ownership in company D.

Data owner type	Description	Organizational assignment
Data owner	“Data owner has a strong contributory role in governing the data in the means of their purposeful, compliant, ethical use as well as their quality”.	Organizational unit that has primary use of a dataset
	“Data owner is accountable for the careful delegation of responsibilities for supporting processes, systems and uses”.
Data product owner	“Data product owners […] oversee a portfolio or bundle of use cases which might result or can be bundled to a product”.	Data organisation
Business owner	“The data product owner is complemented with a business owner, someone who has skin in the game and makes sure that their staff are really using the data product, e.g., in digital sales”.	Line of business: team leader
Data platform owner	“Data platform owner prioritises all the requirements coming from all areas and own the platform, and basically give the direction how the platform will develop further”.	Data organisation

Table 8. Data ownership types in the context of big data and analytics.

Data owner type	Responsibilities	Support in cases	Exemplary statement
Data owner	Accountable for quality and lifecycle of data in his domain of responsibility.	A, B, C, D	“[…] accountable for the overall integrity, data lifecycle, and data quality of data created in his ownership”. (A)
	Fulfils quality requirements for data in his domain of responsibility for data products.	A, D	“Fulfils service-level agreements for data products”. (A)
	Ensures compliant access and use of data in his domain of responsibility by handling requests, providing access, and approving usage.	A, B, C, D	“Controls reading access […] ensures compliant use through the provision of no-join policies […]”. (B)
Data platform owner	Ensures data quality on the platform by managing data pipelines to onboard and provision data.	A, C	“Oversees the implementation and availability of data pipelines to onboard data to the data hub and to provision data to data solutions”. (C)
	Accountable for onboarding of valuable data according to a business need and potential.	B	“Ensures that new and valuable data are onboarded to the data lake according to the business need and potential”. (B)
	Responsible for the development and operation of the data platform. Approves compliance of data products according to data platform standards.	B, C, D	“Data platform owner prioritises all the requirements coming from all areas and own the platform, and basically give the direction how the platform will develop further”. (D)
Data product owner	Ensures that a data product addresses a business need and generates business value over its lifetime.	A, D	“He ensures business value of a data product over its lifetime”. (A)
	Accountable for a data product over its lifetime, including use case portfolio management, development, maintenance, and user support.	A, C, D	“Accountable for a data application over its lifetime, which includes compliant implementation, maintenance of the data application, and support of users”. (C)
	Ensures compliant access and use of data product.	B	“Manages access to data lab, app, or user home and is accountable for any activity […] on it over its lifetime”. (B)

Loshin, D. (2001). Enterprise knowledge management: The data quality approach. Morgan Kaufmann.

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Hart, D. (2002). Ownership as an issue in data and information sharing: A philosophically based review. Australasian Journal of Information Systems, 10(1). https://doi.org/10.3127/ajis.v10i1.440

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