Does E-government reduce corruption? Evidence from a heterogeneous panel data model


Paper by Devid Kumar Basyal et al: “The purpose of this paper is to revisit the relationship between E-government and corruption using global panel data from 176 countries covering the period from 2003 to 2014, considering other potential determinants, such as economic prosperity (gross domestic product per capita [GDPPC]), price stability (inflation), good governance (political stability and government effectiveness) and press freedom (civil liberties and political rights) indicators. Hence, the main rationale of this study is to reexamine the conventional wisdom as to the relationship between E-government and corruption using panel data independent of any preexisting notions. …

No statistical evidence was found for the idea that E-government has a positive impact on corruption reduction following a rigorous test of the proposition. However, strong evidence was found for the positive impact of a country’s government effectiveness, political stability and economic status. There also appears to be some evidence for the effect of GDPPC and civil liberties. There is no evidence to prove that inflation and political rights have any corruption reducing the effect…

The findings of the study demonstrate that E-government is less significant for reducing corruption compared to other factors. Hence, policymakers should further focus on other potential areas such as socio-economic factors, good governance, culture and transparency to combat corruption in addition to improving digital government…(More)”.

‘Data is a fingerprint’: why you aren’t as anonymous as you think online


Olivia Solon at The Guardian: “In August 2016, the Australian government released an “anonymised” data set comprising the medical billing records, including every prescription and surgery, of 2.9 million people.

Names and other identifying features were removed from the records in an effort to protect individuals’ privacy, but a research team from the University of Melbourne soon discovered that it was simple to re-identify people, and learn about their entire medical history without their consent, by comparing the dataset to other publicly available information, such as reports of celebrities having babies or athletes having surgeries.

The government pulled the data from its website, but not before it had been downloaded 1,500 times.

This privacy nightmare is one of many examples of seemingly innocuous, “de-identified” pieces of information being reverse-engineered to expose people’s identities. And it’s only getting worse as people spend more of their lives online, sprinkling digital breadcrumbs that can be traced back to them to violate their privacy in ways they never expected.

Nameless New York taxi logs were compared with paparazzi shots at locations around the city to reveal that Bradley Cooper and Jessica Alba were bad tippers. In 2017 German researchers were able to identify people based on their “anonymous” web browsing patterns. This week University College London researchers showed how they could identify an individual Twitter user based on the metadata associated with their tweets, while the fitness tracking app Polar revealed the homes and in some cases names of soldiers and spies.

“It’s convenient to pretend it’s hard to re-identify people, but it’s easy. The kinds of things we did are the kinds of things that any first-year data science student could do,” said Vanessa Teague, one of the University of Melbourne researchers to reveal the flaws in the open health data.

One of the earliest examples of this type of privacy violation occurred in 1996 when the Massachusetts Group Insurance Commission released “anonymised” data showing the hospital visits of state employees. As with the Australian data, the state removed obvious identifiers like name, address and social security number. Then the governor, William Weld, assured the public that patients’ privacy was protected….(More)”.

The Diversity Dashboard


Engaging Local Government Leaders:  “The Diversity Dashboard is a crowd-funded data collection effort managed by ELGL and hosted on the OpenGovplatform. The data collection includes the self reported gender, race, age, and veteran status of Chief Administrative Officers and Assistant Chief Administrative Officers in local governments of all sizes and forms.

This link includes background information about the Diversity Dashboard, and access to the “Stories” module where we highlight some key findings.

From there, you can drill down into the data, looking at pre-formatted reports and creating your own reports using the submitted data.

The more local government leaders who take the survey, the bigger the dataset, the better our understanding of what the local government leadership landscape looks like. If your local government hasn’t yet completed the survey, please take the survey!…(More)”.

How Charities Are Using Artificial Intelligence to Boost Impact


Nicole Wallace at the Chronicle of Philanthropy: “The chaos and confusion of conflict often separate family members fleeing for safety. The nonprofit Refunite uses advanced technology to help loved ones reconnect, sometimes across continents and after years of separation.

Refugees register with the service by providing basic information — their name, age, birthplace, clan and subclan, and so forth — along with similar facts about the people they’re trying to find. Powerful algorithms search for possible matches among the more than 1.1 million individuals in the Refunite system. The analytics are further refined using the more than 2,000 searches that the refugees themselves do daily.

The goal: find loved ones or those connected to them who might help in the hunt. Since Refunite introduced the first version of the system in 2010, it has helped more than 40,000 people reconnect.

One factor complicating the work: Cultures define family lineage differently. Refunite co-founder Christopher Mikkelsen confronted this problem when he asked a boy in a refugee camp if he knew where his mother was. “He asked me, ‘Well, what mother do you mean?’ ” Mikkelsen remembers. “And I went, ‘Uh-huh, this is going to be challenging.’ ”

Fortunately, artificial intelligence is well suited to learn and recognize different family patterns. But the technology struggles with some simple things like distinguishing the image of a chicken from that of a car. Mikkelsen believes refugees in camps could offset this weakness by tagging photographs — “car” or “not car” — to help train algorithms. Such work could earn them badly needed cash: The group hopes to set up a system that pays refugees for doing such work.

“To an American, earning $4 a day just isn’t viable as a living,” Mikkelsen says. “But to the global poor, getting an access point to earning this is revolutionizing.”

Another group, Wild Me, a nonprofit created by scientists and technologists, has created an open-source software platform that combines artificial intelligence and image recognition, to identify and track individual animals. Using the system, scientists can better estimate the number of endangered animals and follow them over large expanses without using invasive techniques….

To fight sex trafficking, police officers often go undercover and interact with people trying to buy sex online. Sadly, demand is high, and there are never enough officers.

Enter Seattle Against Slavery. The nonprofit’s tech-savvy volunteers created chatbots designed to disrupt sex trafficking significantly. Using input from trafficking survivors and law-enforcement agencies, the bots can conduct simultaneous conversations with hundreds of people, engaging them in multiple, drawn-out conversations, and arranging rendezvous that don’t materialize. The group hopes to frustrate buyers so much that they give up their hunt for sex online….

A Philadelphia charity is using machine learning to adapt its services to clients’ needs.

Benefits Data Trust helps people enroll for government-assistance programs like food stamps and Medicaid. Since 2005, the group has helped more than 650,000 people access $7 billion in aid.

The nonprofit has data-sharing agreements with jurisdictions to access more than 40 lists of people who likely qualify for government benefits but do not receive them. The charity contacts those who might be eligible and encourages them to call the Benefits Data Trust for help applying….(More)”.

Is Open Data Working for Women in Africa?


Web Foundation: “Open data has the potential to change politics, economies and societies for the better by giving people more opportunities to engage in the decisions that affect their lives. But to reach the full potential of open data, it must be available to and used by all. Yet, across the globe — and in Africa in particular — there is a significant data gap.

This report — Is open data working for women in Africa — maps the current state of open data for women across Africa, with insights from country-specific research in Nigeria, Cameroon, Uganda and South Africa with additional data from a survey of experts in 12 countries across the continent.

Our findings show that, despite the potential for open data to empower people, it has so far changed little for women living in Africa.

Key findings

  • There is a closed data culture in Africa — Most countries lack an open culture and have legislation and processes that are not gender-responsive. Institutional resistance to disclosing data means few countries have open data policies and initiatives at the national level. In addition, gender equality legislation and policies are incomplete and failing to reduce gender inequalities. And overall, Africa lacks the cross-organisational collaboration needed to strengthen the open data movement.
  • There are barriers preventing women from using the data that is available — Cultural and social realities create additional challenges for women to engage with data and participate in the technology sector. 1GB of mobile data in Africa costs, on average, 10% of average monthly income. This high cost keeps women, who generally earn less than men, offline. Moreover, time poverty, the gender pay gap and unpaid labour create economic obstacles for women to engage with digital technology.
  • Key datasets to support the advocacy objectives of women’s groups are missing — Data on budget, health and crime are largely absent as open data. Nearly all datasets in sub-Saharan Africa (373 out of 375) are closed, and sex-disaggregated data, when available online, is often not published as open data. There are few open data policies to support opening up of key datasets and even when they do exist, they largely remain in draft form. With little investment in open data initiatives, good data management practices or for implementing Right To Information (RTI) reforms, improvement is unlikely.
  • There is no strong base of research on women’s access and use of open data — There is lack of funding, little collaboration and few open data champions. Women’s groups, digital rights groups and gender experts rarely collaborate on open data and gender issues. To overcome this barrier, multi-stakeholder collaborations are essential to develop effective solutions….(More)”.

Big Data for the Greater Good


Book edited by Ali Emrouznejad and Vincent Charles: “This book highlights some of the most fascinating current uses, thought-provoking changes, and biggest challenges that Big Data means for our society. The explosive growth of data and advances in Big Data analytics have created a new frontier for innovation, competition, productivity, and well-being in almost every sector of our society, as well as a source of immense economic and societal value. From the derivation of customer feedback-based insights to fraud detection and preserving privacy; better medical treatments; agriculture and food management; and establishing low-voltage networks – many innovations for the greater good can stem from Big Data. Given the insights it provides, this book will be of interest to both researchers in the field of Big Data, and practitioners from various fields who intend to apply Big Data technologies to improve their strategic and operational decision-making processes….(More)”.

Data infrastructure literacy


Paper by Jonathan Gray, Carolin Gerlitz and Liliana Bounegru at Big Data & Society: “A recent report from the UN makes the case for “global data literacy” in order to realise the opportunities afforded by the “data revolution”. Here and in many other contexts, data literacy is characterised in terms of a combination of numerical, statistical and technical capacities. In this article, we argue for an expansion of the concept to include not just competencies in reading and working with datasets but also the ability to account for, intervene around and participate in the wider socio-technical infrastructures through which data is created, stored and analysed – which we call “data infrastructure literacy”. We illustrate this notion with examples of “inventive data practice” from previous and ongoing research on open data, online platforms, data journalism and data activism. Drawing on these perspectives, we argue that data literacy initiatives might cultivate sensibilities not only for data science but also for data sociology, data politics as well as wider public engagement with digital data infrastructures. The proposed notion of data infrastructure literacy is intended to make space for collective inquiry, experimentation, imagination and intervention around data in educational programmes and beyond, including how data infrastructures can be challenged, contested, reshaped and repurposed to align with interests and publics other than those originally intended….(More)”

Bad Governance and Corruption


Textbook by Richard Rose and Caryn Peiffer: “This book explains why the role of corruption varies greatly between public services, between people, between national systems of governance, and between measures of corruption.

More than 1.8 billion people pay the price of bad government each year, by sending a bribe to a public official.

In developing countries, corruption affects social services, such as health care and education, and law enforcement institutions, such as the police. When public officials do not act as bureaucrats delivering services by the book, people can try to get them by hook or by crook. The book’s analysis draws on unique evidence: a data base of sample surveys of 175,000 people in 125 countries in Africa, Asia, the Middle East, Europe, and North and South America. The authors avoid one-size-fits-all proposals for reform and instead provide measures that can be applied to particular public services to reduce or eliminate opportunities for corruption….(More)”.

Open Data in Tourism


European Data Portal: “New technologies are rapidly changing the tourism industry. Data are central assets in management and marketing of tourism destinations and businesses. Data driven services became a prominent tool for tourists to plan their trips. The study “Utilizing open data in tourism” predicts great potential for Open Data to increase innovations and destination management. Several actors already use Open Data to provide services in the tourism industry, e.g. the open service called Helsinki Region Infoshare from the city of Helsinki. Malta and Montenegro, for example, are providing data sets on tourist expenditure, hotels, accommodation, restaurants, events, bicycle stations, heritage sites, or beaches.

But not only government organisations and companies use Open Data in tourism. User-generated content, such as reviews and comments spread via social networking services, supports Tourists’ decision making. The study “You will like it!”  analyses user generated Open Data to predict tourists’ perception of sights or attractions.  Thereby they are contributing to the process of predicting tourists’ future preferences, what has potential implications and benefits for the tourism industry.

Engage in the discourse of Open data in tourism, for example on 18 July: the meeting “Linked Open Data im Tourismus“for destination marketing organizations (DMOs) takes place  in Innsbruck to discuss possibilities and prerequisites for using Open Data in tourism. If you rather try out using Open Data to plan your next weekend trip, visit the European Data Portal featured data article on  “Use Open Data to prepare your holiday trip”….(More)”.

What is a data trust?


Essay by Jack Hardinges at ODI: “There are different interpretations of what a data trust is, or should be…

There’s not a well-used definition of ‘a data trust’, or even consensus on what one is. Much of the recent interest in data trusts in the UK has been fuelled by them being recommended as a way to ‘share data in a fair, safe and equitable way’ by a UK government-commissioned independent review into Artificial Intelligence (AI) in 2017. However, there has been wider international interest in the concept for some time.

At a very high level, the aim of data trusts appears to be to give people and organisations confidence when enabling access to data in ways that provide them with some value (either directly or indirectly) in return. Beyond that high level goal, there are a variety of thoughts about what form they should take. In our work so far, we’ve found different interpretations of the term ‘data trust’:

  • A data trust as a repeatable framework of terms and mechanisms.
  • A data trust as a mutual organisation.
  • A data trust as a legal structure.
  • A data trust as a store of data.
  • A data trust as public oversight of data access….(More)”