Government data does not mean data governance: Lessons learned from a public sector application audit

Curated on Posted on by Stefaan Verhulst

Paper by Nik Thompson, Ravi Ravindran, and Salvatore Nicosia: “Public sector agencies routinely store large volumes of information about individuals in the community. The storage and analysis of this information benefits society, as it enables relevant agencies to make better informed decisions and to address the individual’s needs more appropriately. Members of the public often assume that the authorities are well equipped to handle personal data; however, due to implementation errors and lack of data governance, this is not always the case. This paper reports on an audit conducted in Western Australia, focusing on findings in the Police Firearms Management System and the Department of Health Information System. In the case of the Police, the audit revealed numerous data protection issues leading the auditors to report that they had no confidence in the accuracy of information on the number of people licensed to possess firearms or the number of licensed firearms. Similarly alarming conclusions were drawn in the Department of Health as auditors found that they could not determine which medical staff member was responsible for clinical data entries made. The paper describes how these issues often do not arise from existing business rules or the technology itself, but a lack of sound data governance. Finally, a discussion section presents key data governance principles and best practices that may guide practitioners involved in data management. These cases highlight the very real data management concerns, and the associated recommendations provide the context to spark further interest in the applied aspects of data protection….(More)”

 

In The Information Debate, Openness and Privacy Are The Same Thing

Curated on Posted on by Stefaan Verhulst

 at TechCrunch: “We’ve been framing the debate between openness and privacy the wrong way.

Rather than positioning privacy and openness as opposing forces, the fact is they’re different sides of the same coin – and equally important. This might seem simple, but it might also be the key to moving things forward around this crucial debate.

Open data advocates often suggest that openness should be the default for all human knowledge. We should share, re-use and compare data freely and in doing so reap the benefits of innovation, cost savings and increased citizen participation — to name a just a few gains.

And although it might sound a little utopian, the promise is being realized in many corners of the world….But as we all know, even if we accept all the possible benefits of open data, concerns about privacy, especially personal information, still exist as a counter weight to the open data evangelists. People worry that the path of openness could lead to an Orwellian world where all our information is shared with everyone, permanently.

There is a way to turn the conversation from the face-value clash between openness and privacy to how they can be complementary forces. Gus Hosein, CEO of Privacy International, has explained that privacy is “the governing framework to control access to, collection and usage of information.” Basically, privacy laws enable knowledge and control of data about citizens and their surroundings.

Even if we accept all the possible benefits of open data, concerns about privacy, especially personal information, still exist as a counter weight to the open data evangelists.

This is strikingly similar to the argument that open data increases service delivery efficiency and personalization. Openness and privacy both share the same impulse: I want to be in control of my life, I want to know and choose whether a hospital or school is a good hospital or school and be in control of my choice of services.

Another strong thread in conversations around open data is that transparency should be proportionate to power. This makes sense on one level and seems simple enough: Politicians should be held accountable which means a heightened level of transparency.

But who is ‘powerful’, how do you define ‘power’ and who is in charge of defining this?

Politicians have chosen to run for public office and submit themselves to public scrutiny, but what about the CEO of a listed company, the leader of a charity, the anonymous owner of a Cayman-islands’ registered corporation? In practice, it is very difficult to apply the ‘transparency is proportionate to power’ rule outside democratic politics.

We need to stop making a binary distinction between freedom of information laws and data protection; between open data policies and privacy policies. We need one single policy framework that controls as well as encourages the use ‘open’ data.

The closest we get is with so-called PEPs (politically exposed persons) databases: Individuals who are the close family and kin, and close business associates of politicians. But even that defines power as derivative from political power, and not commercial, social or other forms of power.

 And what about personal data?  Should personal data ever be open?

Omidyar Network asked this question to 200 guests at a convention on openness and privacy last year. The audience was split down the middle: 50% thought personal data could never be open data. 50% thought that it should, and that foregoing the opportunity to release it would block the promise of economic gains, better services and other benefits. Open data experts, including the 1,000 who attended a recent meeting in Ottawa, ultimately disagree on this fundamental issue.

Herein lies the challenge. Many of us, including the general public, are uncomfortable with open personal data, even despite the gains it can bring….(More)”

Social Dimensions of Privacy

Curated on Posted on by Stefaan Verhulst

New book edited by Dorota Mokrosinska and Beate Roessler: “Written by a select international group of leading privacy scholars, Social Dimensions of Privacy endorses and develops an innovative approach to privacy. By debating topical privacy cases in their specific research areas, the contributors explore the new privacy-sensitive areas: legal scholars and political theorists discuss the European and American approaches to privacy regulation; sociologists explore new forms of surveillance and privacy on social network sites; and philosophers revisit feminist critiques of privacy, discuss markets in personal data, issues of privacy in health care and democratic politics. The broad interdisciplinary character of the volume will be of interest to readers from a variety of scientific disciplines who are concerned with privacy and data protection issues.

  • Takes an innovative approach to privacy which focuses on the social dimensions and value of privacy in contrast to the value of privacy for individuals
  • Addresses readers from a variety of disciplines, including law, philosophy, media studies, gender studies and political science
  • Addresses new privacy-sensitive areas triggered by recent technological developments (More)”

5 cool ways connected data is being used

Curated on Posted on by Stefaan Verhulst

 at Wareable: “The real news behind the rise of wearable tech isn’t so much the gadgetry as the gigantic amount of personal data that it harnesses.

Concerns have already been raised over what companies may choose to do with such valuable information, with one US life insurance company already using Fitbits to track customers’ exercise and offer them discounts when they hit their activity goals.

Despite a mildly worrying potential dystopia in which our own data could be used against us, there are plenty of positive ways in which companies are using vast amounts of connected data to make the world a better place…

Parkinson’s disease research

Apple Health ResearchKit was recently unveiled as a platform for collecting collaborative data for medical studies, but Apple isn’t the first company to rely on crowdsourced data for medical research.

The Michael J. Fox Foundation for Parkinson’s Research recently unveiled a partnership with Intel to improve research and treatment for the neurodegenerative brain disease. Wearables are being used to unobtrusively gather real-time data from sufferers, which is then analysed by medical experts….

Saving the rhino

Connected data and wearable tech isn’t just limited to humans. In South Africa, the Madikwe Conservation Project is using wearable-based data to protect endangered rhinos from callous poachers.

A combination of ultra-strong Kevlar ankle collars powered by an Intel Galileo chip, along with an RFID chip implanted in each rhino’s horn allows the animals to be monitored. Any break in proximity between the anklet and horn results in anti-poaching teams being deployed to catch the bad guys….

Making public transport smart

A company called Snips is collecting huge amounts of urban data in order to improve infrastructure. In partnership with French national rail operator SNCF, Snips produced an app called Tranquilien to utilise location data from commuters’ phones and smartwatches to track which parts of the rail network were busy at which times.

Combining big data with crowdsourcing, the information helps passengers to pick a train where they can find a seat during peak times, while the data can also be useful to local businesses when serving the needs of commuters who are passing through.

Improving the sports fan experience

We’ve already written about how wearable tech is changing the NFL, but the collection of personal data is also set to benefit the fans.

Levi’s Stadium – the new home of the San Francisco 49ers – opened in 2014 and is one of the most technically advanced sports venues in the world. As well as a strong Wi-Fi signal throughout the stadium, fans also benefit from a dedicated app. This not only offers instant replays and real-time game information, but it also helps them find a parking space, order food and drinks directly to their seat and even check the lines at the toilets. As fans use the app, all of the data is collated to enhance the fan experience in future….

Creating interactive art

Don’t be put off by the words ‘interactive installation’. On Broadway is a cool work of art that “represents life in the 21st Century city through a compilation of images and data collected along the 13 miles of Broadway that span Manhattan”….(More)”

Open data could save the NHS hundreds of millions, says top UK scientist

Curated on Posted on by Stefaan Verhulst

The Guardian: “The UK government must open up and highlight the power of more basic data sets to improve patient care in the NHS and save hundreds of millions of pounds a year, Nigel Shadbolt, chairman of the Open Data Institute (ODI) has urged.

The UK government topped the first league table for open data (paywall)produced by the ODI last year but Shadbolt warns that ministers’ open data responsibilities have not yet been satisfied.

Basic data on prescription administration is now published on a monthly basis but Shadbolt said medical practitioners must be educated about the power of this data to change prescribing habits across the country.

Other data sets, such as trusts’ opening times, consultant lists and details of services, that are promised to make the NHS more accessible are not currently available in a form that is machine-readable.

“These basic sets of information about the processes, the people and places in the health system are all fragmented and fractured and many of them are not available as registers that you can go to,” Shadbolt said.

“Whenever you talk about health data people think you must be talking about personal data and patient data and there are issues, obviously, of absolutely protecting privacy there. But there’s lots of data in the health service that is not about personal patient data at all that would be hugely useful to just have available as machine-readable data for apps to use.”

The UK government has led the way in recent years in encouraging transparency and accountability within the NHS by opening league tables. The publication of league tables on MRSA was followed by a 76-79% drop in infections.

Shadbolt said: “Those hospitals that were worst in their league table don’t like to be there and there was a very rapid diffusion of understanding of best practice across them that you can quantify. It’s many millions of pounds being saved.”

The artificial intelligence and open data expert said the next big area for open data improvement in the NHS is around prescriptions.

Shadbolt pointed to the publication of data about the prescription of statins,which has helped identify savings worth hundreds of millions of pounds: “There is little doubt that this pattern is likely to exist across the whole of the prescribing space.”…(More)”

Selected Readings on Data Governance

Curated on Posted on by Jos Berens

Jos Berens (Centre for Innovation, Leiden University) and Stefaan G. Verhulst (GovLab)

The Living Library’s Selected Readings series seeks to build a knowledge base on innovative approaches for improving the effectiveness and legitimacy of governance. This curated and annotated collection of recommended works on the topic of data governance was originally published in 2015.

Context
The field of Data Collaboratives is premised on the idea that sharing and opening-up private sector datasets has great – and yet untapped – potential for promoting social good. At the same time, the potential of data collaboratives depends on the level of societal trust in the exchange, analysis and use of the data exchanged. Strong data governance frameworks are essential to ensure responsible data use. Without such governance regimes, the emergent data ecosystem will be hampered and the (perceived) risks will dominate the (perceived) benefits. Further, without adopting a human-centered approach to the design of data governance frameworks, including iterative prototyping and careful consideration of the experience, the responses may fail to be flexible and targeted to real needs.

Selected Readings List (in alphabetical order)

Annotated Selected Readings List (in alphabetical order)

Better Place Lab, “Privacy, Transparency and Trust.” Mozilla, 2015. Available from: http://www.betterplace-lab.org/privacy-report.

  • This report looks specifically at the risks involved in the social sector having access to datasets, and the main risks development organizations should focus on to develop a responsible data use practice.
  • Focusing on five specific countries (Brazil, China, Germany, India and Indonesia), the report displays specific country profiles, followed by a comparative analysis centering around the topics of privacy, transparency, online behavior and trust.
  • Some of the key findings mentioned are:
    • A general concern on the importance of privacy, with cultural differences influencing conception of what privacy is.
    • Cultural differences determining how transparency is perceived, and how much value is attached to achieving it.
    • To build trust, individuals need to feel a personal connection or get a personal recommendation – it is hard to build trust regarding automated processes.

Montjoye, Yves Alexandre de; Kendall, Jake and; Kerry, Cameron F. “Enabling Humanitarian Use of Mobile Phone Data.” The Brookings Institution, 2015. Available from: http://www.brookings.edu/research/papers/2014/11/12-enabling-humanitarian-use-mobile-phone-data.

  • Focussing in particular on mobile phone data, this paper explores ways of mitigating privacy harms involved in using call detail records for social good.
  • Key takeaways are the following recommendations for using data for social good:
    • Engaging companies, NGOs, researchers, privacy experts, and governments to agree on a set of best practices for new privacy-conscientious metadata sharing models.
    • Accepting that no framework for maximizing data for the public good will offer perfect protection for privacy, but there must be a balanced application of privacy concerns against the potential for social good.
    • Establishing systems and processes for recognizing trusted third-parties and systems to manage datasets, enable detailed audits, and control the use of data so as to combat the potential for data abuse and re-identification of anonymous data.
    • Simplifying the process among developing governments in regards to the collection and use of mobile phone metadata data for research and public good purposes.

Centre for Democracy and Technology, “Health Big Data in the Commercial Context.” Centre for Democracy and Technology, 2015. Available from: https://cdt.org/insight/health-big-data-in-the-commercial-context/.

  • Focusing particularly on the privacy issues related to using data generated by individuals, this paper explores the overlap in privacy questions this field has with other data uses.
  • The authors note that although the Health Insurance Portability and Accountability Act (HIPAA) has proven a successful approach in ensuring accountability for health data, most of these standards do not apply to developers of the new technologies used to collect these new data sets.
  • For non-HIPAA covered, customer facing technologies, the paper bases an alternative framework for consideration of privacy issues. The framework is based on the Fair Information Practice Principles, and three rounds of stakeholder consultations.

Center for Information Policy Leadership, “A Risk-based Approach to Privacy: Improving Effectiveness in Practice.” Centre for Information Policy Leadership, Hunton & Williams LLP, 2015. Available from: https://www.informationpolicycentre.com/uploads/5/7/1/0/57104281/white_paper_1-a_risk_based_approach_to_privacy_improving_effectiveness_in_practice.pdf.

  • This white paper is part of a project aiming to explain what is often referred to as a new, risk-based approach to privacy, and the development of a privacy risk framework and methodology.
  • With the pace of technological progress often outstripping the capabilities of privacy officers to keep up, this method aims to offer the ability to approach privacy matters in a structured way, assessing privacy implications from the perspective of possible negative impact on individuals.
  • With the intended outcomes of the project being “materials to help policy-makers and legislators to identify desired outcomes and shape rules for the future which are more effective and less burdensome”, insights from this paper might also feed into the development of innovative governance mechanisms aimed specifically at preventing individual harm.

Centre for Information Policy Leadership, “Data Governance for the Evolving Digital Market Place”, Centre for Information Policy Leadership, Hunton & Williams LLP, 2011. Available from: http://www.huntonfiles.com/files/webupload/CIPL_Centre_Accountability_Data_Governance_Paper_2011.pdf.

  • This paper argues that as a result of the proliferation of large scale data analytics, new models governing data inferred from society will shift responsibility to the side of organizations deriving and creating value from that data.
  • It is noted that, with the reality of the challenge corporations face of enabling agile and innovative data use “In exchange for increased corporate responsibility, accountability [and the governance models it mandates, ed.] allows for more flexible use of data.”
  • Proposed as a means to shift responsibility to the side of data-users, the accountability principle has been researched by a worldwide group of policymakers. Tailing the history of the accountability principle, the paper argues that it “(…) requires that companies implement programs that foster compliance with data protection principles, and be able to describe how those programs provide the required protections for individuals.”
  • The following essential elements of accountability are listed:
    • Organisation commitment to accountability and adoption of internal policies consistent with external criteria
    • Mechanisms to put privacy policies into effect, including tools, training and education
    • Systems for internal, ongoing oversight and assurance reviews and external verification
    • Transparency and mechanisms for individual participation
    • Means of remediation and external enforcement

Crawford, Kate; Schulz, Jason. “Big Data and Due Process: Toward a Framework to Redress Predictive Privacy Harm.” NYU School of Law, 2014. Available from: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2325784&download=yes.

  • Considering the privacy implications of large-scale analysis of numerous data sources, this paper proposes the implementation of a ‘procedural data due process’ mechanism to arm data subjects against potential privacy intrusions.
  • The authors acknowledge that some privacy protection structures already know similar mechanisms. However, due to the “inherent analytical assumptions and methodological biases” of big data systems, the authors argue for a more rigorous framework.

Letouze, Emmanuel, and; Vinck, Patrick. “The Ethics and Politics of Call Data Analytics”, DataPop Alliance, 2015. Available from: http://static1.squarespace.com/static/531a2b4be4b009ca7e474c05/t/54b97f82e4b0ff9569874fe9/1421442946517/WhitePaperCDRsEthicFrameworkDec10-2014Draft-2.pdf.

  • Focusing on the use of Call Detail Records (CDRs) for social good in development contexts, this whitepaper explores both the potential of these datasets – in part by detailing recent successful efforts in the space – and political and ethical constraints to their use.
  • Drawing from the Menlo Report Ethical Principles Guiding ICT Research, the paper explores how these principles might be unpacked to inform an ethics framework for the analysis of CDRs.

Data for Development External Ethics Panel, “Report of the External Ethics Review Panel.” Orange, 2015. Available from: http://www.d4d.orange.com/fr/content/download/43823/426571/version/2/file/D4D_Challenge_DEEP_Report_IBE.pdf.

  • This report presents the findings of the external expert panel overseeing the Orange Data for Development Challenge.
  • Several types of issues faced by the panel are described, along with the various ways in which the panel dealt with those issues.

Federal Trade Commission Staff Report, “Mobile Privacy Disclosures: Building Trust Through Transparency.” Federal Trade Commission, 2013. Available from: www.ftc.gov/os/2013/02/130201mobileprivacyreport.pdf.

  • This report looks at ways to address privacy concerns regarding mobile phone data use. Specific advise is provided for the following actors:
    • Platforms, or operating systems providers
    • App developers
    • Advertising networks and other third parties
    • App developer trade associations, along with academics, usability experts and privacy researchers

Mirani, Leo. “How to use mobile phone data for good without invading anyone’s privacy.” Quartz, 2015. Available from: http://qz.com/398257/how-to-use-mobile-phone-data-for-good-without-invading-anyones-privacy/.

  • This paper considers the privacy implications of using call detail records for social good, and ways to mitigate risks of privacy intrusion.
  • Taking example of the Orange D4D challenge and the anonymization strategy that was employed there, the paper describes how classic ‘anonymization’ is often not enough. The paper then lists further measures that can be taken to ensure adequate privacy protection.

Bernholz, Lucy. “Several Examples of Digital Ethics and Proposed Practices” Stanford Ethics of Data conference, 2014, Available from: http://www.scribd.com/doc/237527226/Several-Examples-of-Digital-Ethics-and-Proposed-Practices.

  • This list of readings prepared for Stanford’s Ethics of Data conference lists some of the leading available literature regarding ethical data use.

Abrams, Martin. “A Unified Ethical Frame for Big Data Analysis.” The Information Accountability Foundation, 2014. Available from: http://www.privacyconference2014.org/media/17388/Plenary5-Martin-Abrams-Ethics-Fundamental-Rights-and-BigData.pdf.

  • Going beyond privacy, this paper discusses the following elements as central to developing a broad framework for data analysis:
    • Beneficial
    • Progressive
    • Sustainable
    • Respectful
    • Fair

Lane, Julia; Stodden, Victoria; Bender, Stefan, and; Nissenbaum, Helen, “Privacy, Big Data and the Public Good”, Cambridge University Press, 2014. Available from: http://www.dataprivacybook.org.

  • This book treats the privacy issues surrounding the use of big data for promoting the public good.
  • The questions being asked include the following:
    • What are the ethical and legal requirements for scientists and government officials seeking to serve the public good without harming individual citizens?
    • What are the rules of engagement?
    • What are the best ways to provide access while protecting confidentiality?
    • Are there reasonable mechanisms to compensate citizens for privacy loss?

Richards, Neil M, and; King, Jonathan H. “Big Data Ethics”. Wake Forest Law Review, 2014. Available from: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2384174.

  • This paper describes the growing impact of big data analytics on society, and argues that because of this impact, a set of ethical principles to guide data use is called for.
  • The four proposed themes are: privacy, confidentiality, transparency and identity.
  • Finally, the paper discusses how big data can be integrated into society, going into multiple facets of this integration, including the law, roles of institutions and ethical principles.

OECD, “OECD Guidelines on the Protection of Privacy and Transborder Flows of Personal Data”. Available from: http://www.oecd.org/sti/ieconomy/oecdguidelinesontheprotectionofprivacyandtransborderflowsofpersonaldata.htm.

  • A globally used set of principles to inform thought about handling personal data, the OECD privacy guidelines serve as one the leading standards for informing privacy policies and data governance structures.
  • The basic principles of national application are the following:
    • Collection Limitation Principle
    • Data Quality Principle
    • Purpose Specification Principle
    • Use Limitation Principle
    • Security Safeguards Principle
    • Openness Principle
    • Individual Participation Principle
    • Accountability Principle

The White House Big Data and Privacy Working Group, “Big Data: Seizing Opportunities, Preserving Values”, White House, 2015. Available from: https://www.whitehouse.gov/sites/default/files/docs/big_data_privacy_report_5.1.14_final_print.pdf.

  • Documenting the findings of the White House big data and privacy working group, this report lists i.a. the following key recommendations regarding data governance:
    • Bringing greater transparency to the data services industry
    • Stimulating international conversation on big data, with multiple stakeholders
    • With regard to educational data: ensuring data is used for the purpose it is collected for
    • Paying attention to the potential for big data to facilitate discrimination, and expanding technical understanding to stop discrimination

William Hoffman, “Pathways for Progress” World Economic Forum, 2015. Available from: http://www3.weforum.org/docs/WEFUSA_DataDrivenDevelopment_Report2015.pdf.

  • This paper treats i.a. the lack of well-defined and balanced governance mechanisms as one of the key obstacles preventing particularly corporate sector data from being shared in a controlled space.
  • An approach that balances the benefits against the risks of large scale data usage in a development context, building trust among all stake holders in the data ecosystem, is viewed as key.
  • Furthermore, this whitepaper notes that new governance models are required not just by the growing amount of data and analytical capacity, and more refined methods for analysis. The current “super-structure” of information flows between institutions is also seen as one of the key reasons to develop alternatives to the current – outdated – approaches to data governance.

Big Data Is an Economic Justice Issue, Not Just a Privacy Problem

Curated on Posted on by Stefaan Verhulst

in the Huffington Post: “The control of personal data by “big data” companies is not just an issue of privacy but is becoming a critical issue of economic justice, argues a new report issued by the organization Data Justice>, which itself is being publicly launched in conjunction with the report. ..

At the same time, big data is fueling economic concentration across our economy. As a handful of data platforms generate massive amounts of user data, the barriers to entry rise, since potential competitors have little data themselves to entice advertisers compared with the incumbents, who have both the concentrated processing power and the supply of user data to dominate particular sectors. With little competition, companies end up with little incentive to either protect user privacy or share the economic value of that user data with the consumers generating those profits.

The report argues for a threefold approach to making big data work for everyone in the economy, not just for the big data platforms’ shareholders:

  • First, regulators need to strengthen user control of their own data by both requiring explicit consent for all uses of the data and better informing users of how it’s being used and how companies profit from that data.
  • Second, regulators need to factor control of data into merger review, and to initiate antitrust actions against companies like Google where monopoly control of a sector like search advertising has been established.
  • Third, policymakers should restrict practices that harm consumers, including banning price discrimination where consumers are not informed of all discount options available and bringing the participation of big data platforms in marketing financial services under the regulation of the Consumer Financial Protection Bureau.

Data Justice itself has been founded as an organization “to promote public education and new alliances to challenge the danger of big data to workers, consumers and the public.” It will work to educate the public, policymakers and organizational allies on how big data is contributing to economic inequality in the economy. Its new website at datajustice.org is intended to bring together a wide range of resources highlighting the economic justice aspects of big data.”

Would You Share Private Data for the Good of City Planning?

Curated on Posted on by Stefaan Verhulst

Henry Grabar at NextCity: “The proliferation of granular data on automobile movement, drawn from smartphones, cab companies, sensors and cameras, is sharpening our sense of how cars travel through cities. Panglossian seers believe the end of traffic jams is nigh.
This information will change cities beyond their roads. Real-time traffic data may lead to reworked intersections and new turning lanes, but understanding cars is in some ways a stand-in for understanding people. There’s traffic as traffic and traffic as proxy, notes Brett Goldstein, an urban science fellow at the University of Chicago who served as that city’s first data officer from 2011 to 2013. “We’d be really naive, in thinking about how we make cities better,” he says, “to only consider traffic for what it is.”
Even a small subset of a city’s car data goes a long way. Consider the raft of discrete findings that have emerged from the records of New York City taxis.
Researchers at the Massachusetts Institute of Technology, led by Paolo Santi, showed that cab-sharing could reduce taxi mileage by 40 percent. Their counterparts at NYU, led by Claudio Silva, mapped activity around hubs like train stations and airports and during hurricanes.
“You start to build actual models of how people move, and where they move,” observes Silva, the head of disciplines at NYU’s Center for Science and Urban Progress (CUSP). “The uses of this data for non-traffic engineering are really substantial.”…
Many of these ideas are hypothetical, for the moment, because so-called “granular” data is so hard to come by. That’s one reason the release of New York’s taxi cab data spurred so many studies — it’s an oasis of information in a desert of undisclosed records. Corporate entreaties, like Uber’s pending data offering to Boston, don’t always meet researchers’ standards. “It’s going to be a lot of superficial data, and it’s not clear how usable it’ll be at this point,” explains Sarah Kaufman, the digital manager at NYU’s Rudin Center for Transportation….
Yet Americans seem much more alarmed by the collection of location data than other privacy breaches.
How can data utopians convince the hoi polloi to share their comings and goings? One thought: Make them secure. Mike Flowers, the founder of New York City’s Office of Data Analytics and a fellow at NYU’s CUSP, told me it might be time to consider establishing a quasi-governmental body that people would trust to make their personal data anonymous before they are channeled into government projects. (New York City’s Taxi and Limousine Commission did not do a very good job at this, which led to Gawker publishing a dozen celebrity cab rides.)
Another idea is to frame open data as a beneficial trade-off. “When people provide information, they want to realize the benefit of the information,” Goldstein says.
Users tell the routing company Waze where they are and get a smoother commute in return. Progressive Insurance offers drivers a “Snapshot” tracker. If it likes the way you drive, the company will lower your rates. It’s not hard to imagine that, in the long run, drivers will be penalized for refusing such a device…. (More).”

Survive and Thrive: How Big Data Is Transforming Health Care

Curated on Posted on by Stefaan Verhulst

at Pacific Standard: “When you step on a scale, take your temperature, or check your blood pressure, you’re using data from your body to measure your health. Advances in fitness trackers have made health quantification more accessible to casual users. But for researchers, health care providers, and people with chronic conditions, advances in tracking technology, data analysis, and automation offer significant improvements in medical treatment and quality of life.

This three-part series explores health quantification through the eyes of Rutgers University Ph.D student Maria Qadri, who has both professional and personal experience in the matter. Qadri’s research aims to help people with traumatic brain injury and Parkinson’s Disease better manage their illness, and, as a Type 1 diabetic, glucose monitoring is a major part of her own life. Below, we take a look at how number crunching and personal data factors into Qadri’s research and life….(More).”

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Donated Personal Data Could Aid Lifestyle Researchers

Curated on Posted on by Stefaan Verhulst

Anya Skatova and James Goulding at Scientific American: “In the future it will be possible to donate our personal data to charitable causes. All sorts of data is recorded about us as we go about our daily lives—what we buy, where we go, who we call on the phone and our use of the internet. The time is approaching when we could liberate that data in support of good causes. Given many people already donate precious resources such as money or even blood for the benefit of society at large, this step might not be far away.
How could donated data help our society? Data is a rich source of people’s habits—shopping data from loyalty cards, for example, can reflect our diet. If people donate their personal data for research, analysis of it can provide scope to improve everything from understandings of the dietary pre-cursors to diabetes to the impact of lifestyle on heart disease.
But there are vital issues around the collection and use of personal data that must be addressed. Donation rests on trust: would people give their data away knowing that researchers will examine it, even if anonymously? Would they want others scrutinising their diet, or their shopping habits? Would people feel their privacy was being invaded, even if they had chosen to donate to help medical research?
Who would donate data to research?
Our recent research has found that around 60% of people are willing to donate their data for uses that will benefit the public. In some ways this is not surprising. As previous research demonstrated, people help others and take part in various pro-social activities. People voluntarily give to benefit society at large: they donate money to charities, or run marathons to raise money without knowing exactly who will benefit; they give blood, bone marrow, or even organs. They often do so out of concern for the welfare of others, or in other cases for more selfish reasons, such as enhancing their reputation, professional benefit, or just to feel good about themselves….
Donating data is certainly different from donating money or blood—there is very little obvious cost to us when donating our data. Unlike blood or money, data is something for which most of us have no use, nor has it any real monetary value to those of us that generate it, but it becomes valuable when combined with the data of others.
Currently companies leverage personal data to make money because it provides them with sophisticated understanding of consumer behaviour, from which they in turn can profit. But shouldn’t our data benefit us too?…(More)”