data – Page 13 – The Living Library

The Case for Accountability: How it Enables Effective Data Protection and Trust in the Digital Society

Curated on July 24, 2018 by Stefaan Verhulst

Centre for Information Policy Leadership: “Accountability now has broad international support and has been adopted in many laws, including in the EU General Data Protection Regulation (GDPR), regulatory policies and organisational practices. It is essential that there is consensus and clarity on the precise meaning and application of organisational accountability among all stakeholders, including organisations implementing accountability and data protection authorities (DPAs) overseeing accountability.

Without such consensus, organisations will not know what DPAs expect of them and DPAs will not know how to assess organisations’ accountability-based privacy programs with any degree of consistency and predictability. Thus, drawing from the global experience with accountability to date and from the Centre for Information Policy Leadership’s (CIPL) own extensive prior work on accountability, this paper seeks to explain the following issues:

The concept of organisational accountability and how it is reflected in the GDPR;
The essential elements of accountability and how the requirements of the GDPR (and of other normative frameworks) map to these elements;
Global acceptance and adoption of accountability;
How organisations can implement accountability (including by and between controllers and processors) through comprehensive internal privacy programs that implement external rules or the organisation’s own data protection policies and goals, or through verified or certified accountability mechanisms, such as Binding Corporate Rules (BCR), APEC Cross-Border Privacy Rules (CBPR), APEC Privacy Recognition for Processors (PRP), other seals and certifications, including future GDPR certifications and codes of conduct; and
The benefits that accountability can deliver to each stakeholder group.

In addition, the paper argues that accountability exists along a spectrum, ranging from basic accountability requirements required by law (such as under the GDPR) to stronger and more granular accountability measures that may not be required by law but that organisations may nevertheless want to implement because they convey substantial benefits….(More)”.

Open Science by Design: Realizing a Vision for 21st Century Research

Curated on July 23, 2018 by Stefaan Verhulst

Report by the National Academies of Sciences: “Openness and sharing of information are fundamental to the progress of science and to the effective functioning of the research enterprise. The advent of scientific journals in the 17th century helped power the Scientific Revolution by allowing researchers to communicate across time and space, using the technologies of that era to generate reliable knowledge more quickly and efficiently. Harnessing today’s stunning, ongoing advances in information technologies, the global research enterprise and its stakeholders are moving toward a new open science ecosystem. Open science aims to ensure the free availability and usability of scholarly publications, the data that result from scholarly research, and the methodologies, including code or algorithms, that were used to generate those data.

Open Science by Design is aimed at overcoming barriers and moving toward open science as the default approach across the research enterprise. This report explores specific examples of open science and discusses a range of challenges, focusing on stakeholder perspectives. It is meant to provide guidance to the research enterprise and its stakeholders as they build strategies for achieving open science and take the next steps….(More)”.

Evaluating Civic Open Data Standards

Curated on July 22, 2018August 3, 2018 by Stefaan Verhulst

Renee Sieber and Rachel Bloom at SocArXiv Papers: In many ways, a precondition to realizing the promise of open government data is the standardization of that data. Open data standards ensure interoperability, establish benchmarks in assessing whether governments achieve their goals in publishing open data, can better ensure accuracy of the data. Interoperability enables the use of off-the shelf software and can ease third party development of products that serves multiple locales.

Our project aims to determine which standards for civic data are “best” to open up government data. We began by disambiguating the multiple meanings of what constitutes a data standard by creating a standards stack.

The empirical research started by identifying twelve “high value” open datasets for which we found 22 data standards. A qualitative systematic review of the gray literature and standards documentation generated 18 evaluation metrics, which we grouped into four categories. We evaluated the metrics with civic data standards. Our goal is to identify and characterize types of standards and provide a systematic way to assess their quality…(More)”.

The Data Transfer Project

Curated on July 22, 2018August 3, 2018 by Stefaan Verhulst

About: “The Data Transfer Project was formed in 2017 to create an open-source, service-to-service data portability platform so that all individuals across the web could easily move their data between online service providers whenever they want.

The contributors to the Data Transfer Project believe portability and interoperability are central to innovation. Making it easier for individuals to choose among services facilitates competition, empowers individuals to try new services and enables them to choose the offering that best suits their needs.

Current contributors include Facebook, Google, Microsoft and Twitter.

Individuals have many reasons to transfer data, but we want to highlight a few examples that demonstrate the additional value of service-to-service portability.

A user discovers a new photo printing service offering beautiful and innovative photo book formats, but their photos are stored in their social media account. With the Data Transfer Project, they could visit a website or app offered by the photo printing service and initiate a transfer directly from their social media platform to the photo book service.
A user doesn’t agree with the privacy policy of their music service. They want to stop using it immediately, but don’t want to lose the playlists they have created. Using this open-source software, they could use the export functionality of the original Provider to save a copy of their playlists to the cloud. This enables them to import the lists to a new Provider, or multiple Providers, once they decide on a new service.
A large company is getting requests from customers who would like to import data from a legacy Provider that is going out of business. The legacy Provider has limited options for letting customers move their data. The large company writes an Adapter for the legacy Provider’s Application Program Interfaces (APIs) that permits users to transfer data to their service, also benefiting other Providers that handle the same data type.
A user in a low bandwidth area has been working with an architect on drawings and graphics for a new house. At the end of the project, they both want to transfer all the files from a shared storage system to the user’s cloud storage drive. They go to the cloud storage Data Transfer Project User Interface (UI) and move hundreds of large files directly, without straining their bandwidth.
An industry association for supermarkets wants to allow customers to transfer their loyalty card data from one member grocer to another, so they can get coupons based on buying habits between stores. The Association would do this by hosting an industry-specific Host Platform of DTP.

The innovation in each of these examples lies behind the scenes: Data Transfer Project makes it easy for Providers to allow their customers to interact with their data in ways their customers would expect. In most cases, the direct-data transfer experience will be branded and managed by the receiving Provider, and the customer wouldn’t need to see DTP branding or infrastructure at all….

To get a more in-depth understanding of the project, its fundamentals and the details involved, please download “Data Transfer Project Overview and Fundamentals”….(More)”.

Blockchain is helping build a new Indian city, but it’s no cure for corruption

Curated on July 18, 2018August 3, 2018 by Stefaan Verhulst

Ananya Bhattacharya at Quartz: “Last year, Tharigopula Sambasiva Rao entered into a deal with the state government of Andhra Pradesh. He gave up six acres of his agricultural land in his village, Sakhamuru, in exchange for 7,250 square yards—6,000 square yards of residential plots and 1,250 square yards of commercial ones.

In February this year, the 50-year-old farmer got his plots registered at the sub-registrar’s office in Thullur town of Guntur district. He booked an appointment through a government-run app and turned up with his Aadhaar number, a unique identity provided by the government of India to every citizen. Rao’s land documents, complete with a map, certificate, and carrying a unique QR code, were prepared by officials and sent directly to the registration office, all done in just a couple of hours.

Kommineni Ramanjaneyulu, another farmer from around Thullur, exchanged 4.5 acres for 10 plots. The 83-year-old was wary of this new technology deployed to streamline the land registration process. However, he was relieved to see the documents for his new assets in his native language, Telugu. There was no information gap….

In theory, blockchain can store land documents in a tamper-proof, secure network, reducing human interventions and adding more transparency. Data is solidified and the transaction history of a property is fully trackable. This has the potential to reduce, if not entirely prevent, property fraud. But unlike in the case of bitcoin, the blockchain utilised by the government agency in charge of shaping Amaravati is private.

So, despite the promise on paper, local landowners and farmers remain convinced that there’s no escaping red tape and corruption yet….

The entire documentation process for this massive exercise is based on blockchain. The decentralised distributed ledger system—central to cryptocurrencies like bitcoin and ether—can create foolproof digitised land registries of the residential and commercial plots allotted to farmers. It essentially serves as a book-keeping tool that can be accessed by all but is owned by none…

Having seen the government’s dirty tricks, most of the farmers gathered at Rayapudi aren’t buying the claim that the system is tamper-proof—especially at the stages before the information is moved to blockchain. After all, assignments and verifications are still being done by revenue officers on the ground.

That the Andhra Pradesh government is using a private blockchain complicates things further. The public can view information but not directly monitor whether any illicit changes have been made to their records. They have to go through the usual red tape to get those answers. The system may not be susceptible to hacking, but authorities could deliberately enter wrong information or refuse to reveal instances of fraud even if they are logged. This is the farmers’ biggest concern.

“The tampering cannot be stopped. If you give the right people a lot of bribe, they will go in and change the record,” said Seshagiri Rao. Nearly $700 million is paid in bribes across land registrars in India, an Andhra Pradesh government official estimated last year, and even probes into these matters are often flawed….(More)”.

How Mobile Network Operators Can Help Achieve the Sustainable Development Goals Profitably

Curated on July 17, 2018May 29, 2019 by Stefaan Verhulst

Press Release: “Today, the Digital Impact Alliance (DIAL) released its second paper in a series focused on the promise of data for development (D4D). The paper, Leveraging Data for Development to Achieve Your Triple Bottom Line: Mobile Network Operators with Advanced Data for Good Capabilities See Stronger Impact to Profits, People and the Planet, will be presented at GSMA’s Mobile 360 Africa in Kigali.

“The mobile industry has already taken a driving seat in helping reach the Sustainable Development Goals by 2030 and this research reinforces the role mobile network operators in lower-income economies can play to leverage their network data for development and build a new data business safely and securely,” said Kate Wilson, CEO of the Digital Impact Alliance. “Mobile network operators (MNOs) hold unique data on customers’ locations and behaviors that can help development efforts. They have been reluctant to share data because there are inherent business risks and to do so has been expensive and time consuming. DIAL’s research illustrates a path forward for MNOs on which data is useful to achieve the SDGs and why acting now is critical to building a long-term data business.”

DIAL worked with Altai Consulting on both primary and secondary research to inform this latest paper. Primary research included one-on-one in-depth interviews with more than 50 executives across the data for development value chain, including government officials, civil society leaders, mobile network operators and other private sector representatives from both developed and emerging markets. These interviews help inform how operators can best tap into the shared value creation opportunities data for development provides.

Key findings from the in-depth interviews include:

There are several critical barriers that have prevented scaled use of mobile data for social good – including 1) unclear market opportunities, 2) not enough collaboration among MNOs, governments and non-profit stakeholders and 3) regulatory and privacy concerns;
While it may be an ideal time for MNOs to increase their involvement in D4D efforts given the unique data they have that can inform development, market shifts suggest the window of opportunity to implement large-scale D4D initiatives will likely not remain open for much longer;
Mobile Network Operators with advanced data for good capabilities will have the most success in establishing sustainable D4D efforts; and as a result, achieving triple bottom line mandates; and
Mobile Network Operators should focus on providing value-added insights and services rather than raw data and drive pricing and product innovation to meet the sector’s needs.

“Private sector data availability to drive public sector decision-making is a critical enabler for meeting SDG targets,” said Syed Raza, Senior Director of the Data for Development Team at the Digital Impact Alliance. “Our data for development paper series aims to elevate the efforts of our industry colleagues with the information, insights and tools they need to help drive ethical innovation in this space….(More)”.

Let’s make private data into a public good

Curated on July 17, 2018August 3, 2018 by Stefaan Verhulst

Article by Mariana Mazzucato: “The internet giants depend on our data. A new relationship between us and them could deliver real value to society….We should ask how the value of these companies has been created, how that value has been measured, and who benefits from it. If we go by national accounts, the contribution of internet platforms to national income (as measured, for example, by GDP) is represented by the advertisement-related services they sell. But does that make sense? It’s not clear that ads really contribute to the national product, let alone to social well-being—which should be the aim of economic activity. Measuring the value of a company like Google or Facebook by the number of ads it sells is consistent with standard neoclassical economics, which interprets any market-based transaction as signaling the production of some kind of output—in other words, no matter what the thing is, as long as a price is received, it must be valuable. But in the case of these internet companies, that’s misleading: if online giants contribute to social well-being, they do it through the services they provide to users, not through the accompanying advertisements.

This way we have of ascribing value to what the internet giants produce is completely confusing, and it’s generating a paradoxical result: their advertising activities are counted as a net contribution to national income, while the more valuable services they provide to users are not.

Let’s not forget that a large part of the technology and necessary data was created by all of us, and should thus belong to all of us. The underlying infrastructure that all these companies rely on was created collectively (via the tax dollars that built the internet), and it also feeds off network effects that are produced collectively. There is indeed no reason why the public’s data should not be owned by a public repository that sells the data to the tech giants, rather than vice versa. But the key issue here is not just sending a portion of the profits from data back to citizens but also allowing them to shape the digital economy in a way that satisfies public needs. Using big data and AI to improve the services provided by the welfare state—from health care to social housing—is just one example.

Only by thinking about digital platforms as collective creations can we construct a new model that offers something of real value, driven by public purpose. We’re never far from a media story that stirs up a debate about the need to regulate tech companies, which creates a sense that there’s a war between their interests and those of national governments. We need to move beyond this narrative. The digital economy must be subject to the needs of all sides; it’s a partnership of equals where regulators should have the confidence to be market shapers and value creators….(More)”.

Collective Awareness

Curated on July 17, 2018August 3, 2018 by Stefaan Verhulst

A Conversation with J. Doyne Farmer at the Edge: “Economic failures cause us serious problems. We need to build simulations of the economy at a much more fine-grained level that take advantage of all the data that computer technologies and the Internet provide us with. We need new technologies of economic prediction that take advantage of the tools we have in the 21^st century.

Places like the US Federal Reserve Bank make predictions using a system that has been developed over the last eighty years or so. This line of effort goes back to the middle of the 20th century, when people realized that we needed to keep track of the economy. They began to gather data and set up a procedure for having firms fill out surveys, for having the census take data, for collecting a lot of data on economic activity and processing that data. This system is called “national accounting,” and it produces numbers like GDP, unemployment, and so on. The numbers arrive at a very slow timescale. Some of the numbers come out once a quarter, some of the numbers come out once a year. The numbers are typically lagged because it takes a lot of time to process the data, and the numbers are often revised as much as a year or two later. That system has been built to work in tandem with the models that have been built, which also process very aggregated, high-level summaries of what the economy is doing. The data is old fashioned and the models are old fashioned.

It’s a 20th-century technology that’s been refined in the 21st century. It’s very useful, and it represents a high level of achievement, but it is now outdated. The Internet and computers have changed things. With the Internet, we can gather rich, detailed data about what the economy is doing at the level of individuals. We don’t have to rely on surveys; we can just grab the data. Furthermore, with modern computer technology we could simulate what 300 million agents are doing, simulate the economy at the level of the individuals. We can simulate what every company is doing and what every bank is doing in the United States. The model we could build could be much, much better than what we have now. This is an achievable goal.

But we’re not doing that, nothing close to that. We could achieve what I just said with a technological system that’s simpler than Google search. But we’re not doing that. We need to do it. We need to start creating a new technology for economic prediction that runs side-by-side with the old one, that makes its predictions in a very different way. This could give us a lot more guidance about where we’re going and help keep the economic shit from hitting the fan as often as it does….(More)”.

Health Insurers Are Vacuuming Up Details About You — And It Could Raise Your Rates

Curated on July 17, 2018August 3, 2018 by Stefaan Verhulst

Marshall Allen at ProPublica: “With little public scrutiny, the health insurance industry has joined forces with data brokers to vacuum up personal details about hundreds of millions of Americans, including, odds are, many readers of this story. The companies are tracking your race, education level, TV habits, marital status, net worth. They’re collecting what you post on social media, whether you’re behind on your bills, what you order online. Then they feed this information into complicated computer algorithms that spit out predictions about how much your health care could cost them.

Are you a woman who recently changed your name? You could be newly married and have a pricey pregnancy pending. Or maybe you’re stressed and anxious from a recent divorce. That, too, the computer models predict, may run up your medical bills.

Are you a woman who’s purchased plus-size clothing? You’re considered at risk of depression. Mental health care can be expensive.

Low-income and a minority? That means, the data brokers say, you are more likely to live in a dilapidated and dangerous neighborhood, increasing your health risks.

“We sit on oceans of data,” said Eric McCulley, director of strategic solutions for LexisNexis Risk Solutions, during a conversation at the data firm’s booth. And he isn’t apologetic about using it. “The fact is, our data is in the public domain,” he said. “We didn’t put it out there.”

Insurers contend they use the information to spot health issues in their clients — and flag them so they get services they need. And companies like LexisNexis say the data shouldn’t be used to set prices. But as a research scientist from one company told me: “I can’t say it hasn’t happened.”

At a time when every week brings a new privacy scandal and worries abound about the misuse of personal information, patient advocates and privacy scholars say the insurance industry’s data gathering runs counter to its touted, and federally required, allegiance to patients’ medical privacy. The Health Insurance Portability and Accountability Act, or HIPAA, only protects medical information.

“We have a health privacy machine that’s in crisis,” said Frank Pasquale, a professor at the University of Maryland Carey School of Law who specializes in issues related to machine learning and algorithms. “We have a law that only covers one source of health information. They are rapidly developing another source.”…(More)”.