Why not one big database? : principles for data ownership

"This paper supercedes an earlier version, WP#2518-93 published in December 1992 under the title "Ownership principles for distributed database design."Includes bibliographical references (p. 36-39).Supported by the MIT Industrial Performance Center. Supported by the Advanced Research Projects Agency. F30602-93-C-0160Marshall Van Alstyne, Erik Brynjolfsson, Stuart E. Madnick

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

Today, a myriad of data is generated via connected devices and digital applications. In order to benefit from these data, companies have to develop their capabilities related to big data and analytics (BDA). A critical factor that is often cited concerning the “soft” aspects of BDA is data ownership, i.e., clarifying the fundamental rights and responsibilities for data. IS research has investigated data ownership for operational systems and data warehouses, where the purpose of data processing is known. In the BDA context, defining accountabilities for data is more challenging because data are stored in data lakes and used for previously unknown purposes. Based on four case studies, we identify ownership principles and three distinct types: data, data platform, and data product ownership. Our research answers fundamental questions about how data management changes with BDA and lays the foundation for future research on data and analytics governance

Regulating Data as Property: A New Construct for Moving Forward

The global community urgently needs precise, clear rules that define ownership of data and express the attendant rights to license, transfer, use, modify, and destroy digital information assets. In response, this article proposes a new approach for regulating data as an entirely new class of property. Recently, European and Asian public officials and industries have called for data ownership principles to be developed, above and beyond current privacy and data protection laws. In addition, official policy guidances and legal proposals have been published that offer to accelerate realization of a property rights structure for digital information. But how can ownership of digital information be achieved? How can those rights be transferred and enforced? Those calls for data ownership emphasize the impact of ownership on the automotive industry and the vast quantities of operational data which smart automobiles and self-driving vehicles will produce. We looked at how, if at all, the issue was being considered in consumer-facing statements addressing the data being collected by their vehicles. To formulate our proposal, we also considered continued advances in scientific research, quantum mechanics, and quantum computing which confirm that information in any digital or electronic medium is, and always has been, physical, tangible matter. Yet, to date, data regulation has sought to adapt legal constructs for “intangible” intellectual property or to express a series of permissions and constraints tied to specific classifications of data (such as personally identifiable information). We examined legal reforms that were recently approved by the United Nations Commission on International Trade Law to enable transactions involving electronic transferable records, as well as prior reforms adopted in the United States Uniform Commercial Code and Federal law to enable similar transactions involving digital records that were, historically, physical assets (such as promissory notes or chattel paper). Finally, we surveyed prior academic scholarship in the U.S. and Europe to determine if the physical attributes of digital data had been previously considered in the vigorous debates on how to regulate personal information or the extent, if at all, that the solutions developed for transferable records had been considered for larger classes of digital assets. Based on the preceding, we propose that regulation of digital information assets, and clear concepts of ownership, can be built on existing legal constructs that have enabled electronic commercial practices. We propose a property rules construct that clearly defines a right to own digital information arises upon creation (whether by keystroke or machine), and suggest when and how that right attaches to specific data though the exercise of technological controls. This construct will enable faster, better adaptations of new rules for the ever-evolving portfolio of data assets being created around the world. This approach will also create more predictable, scalable, and extensible mechanisms for regulating data and is consistent with, and may improve the exercise and enforcement of, rights regarding personal information. We conclude by highlighting existing technologies and their potential to support this construct and begin an inventory of the steps necessary to further proceed with this process

Alexa, Who Owns My Pillow Talk? Contracting, Collaterizing, and Monetizing Consumer Privacy Through Voice-Captured Personal Data

With over one-fourth of households in the U.S. alone now using voice-activated digital assistant devices such as Amazon’s Echo (better known as “Alexa”) and Google’s Home, companies are recording and transmitting record volumes of voice data from the privacy of people’s homes to servers across the globe. These devices capture conversations about everything from online shopping to food preferences to entertainment recommendations to bedtime stories, and even phone and appliance use. With “Big Data” and business analytics expected to be a $203 billion-plus industry by 2020, companies are racing to acquire and leverage consumer data by selling it, licensing it, and pledging it as collateral for financing. Given that data is the digital economy’s most valuable currency, it is no wonder that companies are engaging in fierce legal battles with each other for ownership, possession, and, in some cases, repossession of consumer data. Consumers themselves have asserted rights to data they allegedly generated, particularly when this data is disseminated in contravention of a company’s privacy policy – which some claim is violated by the simple act of collateralizing the company’s data assets. Courts and legislatures have attempted to balance the various stakeholders’ interests in voice data through the legal frameworks of contracts, property, secured transactions, and statutes. This comment explores some of these conflicting interests and identifies the weaknesses in the predominant legal frameworks through which the chain of ownership is currently analyzed. This comment then proposes different ways of applying existing legal principles, as well as new federal legislation, to better align and distribute these interests. This comment concludes that property law’s legal framework is better-suited to address personal data ownership than contract law alone, since it allows shared ownership with multiple concurrent users of the same asset. Adjusting the process by which security interests in voice-captured data are created and enforced may also help protect the data’s integrity while minimizing unintended transfers that may harm consumers. Ultimately, statutory relief may be necessary to protect and restore certain rights to consumers in their own personal voice data

Rights in a Cloud of Dust: The Value and Qualities of Farm Data and How Its Property Rights Should Be Viewed Moving Forward

Historically, technology growth has been slower in agriculture than other industries. However, a rising demand for food and an increase in efficient farm practices has changed this, leading to a rise in precision farming technologies. Now, entities that provide services or information to farmers need precision farming technologies to compete, and more farmers are adopting precision farming technologies. These technologies help farmers, but questions still remain about ownership rights in the data that farmers create

To share or not to share: Publication and quality assurance of research data outputs. A report commissioned by the Research Information Network

A study on current practices with respect to data creation, use, sharing and publication in eight research disciplines (systems biology, genomics, astronomy, chemical crystallography, rural economy and land use, classics, climate science and social and public health science). The study looked at data creation and care, motivations for sharing data, discovery, access and usability of datasets and quality assurance of data in each discipline

AAPOR Report on Big Data

In recent years we have seen an increase in the amount of statistics in society describing different phenomena based on so called Big Data. The term Big Data is used for a variety of data as explained in the report, many of them characterized not just by their large volume, but also by their variety and velocity, the organic way in which they are created, and the new types of processes needed to analyze them and make inference from them. The change in the nature of the new types of data, their availability, the way in which they are collected, and disseminated are fundamental. The change constitutes a paradigm shift for survey research.There is a great potential in Big Data but there are some fundamental challenges that have to be resolved before its full potential can be realized. In this report we give examples of different types of Big Data and their potential for survey research. We also describe the Big Data process and discuss its main challenges

Understanding the care.data conundrum: new information flows for economic growth

The analysis of data from electronic health records aspires to facilitate healthcare efficiencies and biomedical innovation. There are also ethical, legal and social implications from the handling of sensitive patient information. The paper explores the concerns, expectations and implications of the National Health Service (NHS) England care.data programme: a national data sharing initiative of linked electronic health records for healthcare and other research purposes. Using Nissenbaum’s contextual integrity of privacy framework through a critical science and technology studies (STS) lens, it examines the way technologies and policies are developed to promote sustainability, governance and economic growth as the de facto social values, while reducing privacy to an individualistic preference. The state, acting as a new, central data broker reappropriates public ownership rights and establishes those information flows and transmission principles that facilitate the assetisation of NHS datasets for the knowledge economy. Various actors and processes from other contexts attempt to erode the public healthcare sector and privilege new information recipients. However, such data sharing initiatives in healthcare will be resisted if we continue to focus only on the monetary and scientific values of these datasets and keep ignoring their equally important social and ethical values

Open Data, Grey Data, and Stewardship: Universities at the Privacy Frontier

As universities recognize the inherent value in the data they collect and hold, they encounter unforeseen challenges in stewarding those data in ways that balance accountability, transparency, and protection of privacy, academic freedom, and intellectual property. Two parallel developments in academic data collection are converging: (1) open access requirements, whereby researchers must provide access to their data as a condition of obtaining grant funding or publishing results in journals; and (2) the vast accumulation of 'grey data' about individuals in their daily activities of research, teaching, learning, services, and administration. The boundaries between research and grey data are blurring, making it more difficult to assess the risks and responsibilities associated with any data collection. Many sets of data, both research and grey, fall outside privacy regulations such as HIPAA, FERPA, and PII. Universities are exploiting these data for research, learning analytics, faculty evaluation, strategic decisions, and other sensitive matters. Commercial entities are besieging universities with requests for access to data or for partnerships to mine them. The privacy frontier facing research universities spans open access practices, uses and misuses of data, public records requests, cyber risk, and curating data for privacy protection. This paper explores the competing values inherent in data stewardship and makes recommendations for practice, drawing on the pioneering work of the University of California in privacy and information security, data governance, and cyber risk.Comment: Final published version, Sept 30, 201

Blockchain For Food: Making Sense of Technology and the Impact on Biofortified Seeds

The global food system is under pressure and is in the early stages of a major transition towards more transparency, circularity, and personalisation. In the coming decades, there is an increasing need for more food production with fewer resources. Thus, increasing crop yields and nutritional value per crop is arguably an important factor in this global food transition. Biofortification can play an important role in feeding the world. Biofortified seeds create produce with increased nutritional values, mainly minerals and vitamins, while using the same or less resources as non-biofortified variants. However, a farmer cannot distinguish a biofortified seed from a regular seed. Due to the invisible nature of the enhanced seeds, counterfeit products are common, limiting wide-scale adoption of biofortified crops. Fraudulent seeds pose a major obstacle in the adoption of biofortified crops. A system that could guarantee the origin of the biofortified seeds is therefore required to ensure widespread adoption. This trust-ensuring immutable proof for the biofortified seeds, can be provided via blockchain technology