Open Data as Open Educational Resources: Case studies of emerging practice

Curated on Posted on by Stefaan Verhulst

Book edited by Javiera Atenas and Leo Havemann: “…is the outcome of a collective effort that has its origins in the 5th Open Knowledge Open Education Working Group call, in which the idea of using Open Data in schools was mentioned. It occurred to us that Open Data and open educational resources seemed to us almost to exist in separate open worlds.

We decided to seek out evidence in the use of open data as OER, initially by conducting a bibliographical search. As we could not find published evidence, we decided to ask educators if they were in fact, using open data in this way, and wrote a post for this blog (with Ernesto Priego) explaining our perspective, called The 21st Century’s Raw Material: Using Open Data as Open Educational Resources. We ended the post with a link to an exploratory survey, the results of which indicated a need for more awareness of the existence and potential value of Open Data amongst educators…..

the case studies themselves. They have been provided by scholars and practitioners from different disciplines and countries, and they reflect different approaches to the use of open data. The first case study presents an approach to educating both teachers and students in the use of open data for civil monitoring via Scuola di OpenCoesione in Italy, and has been written by Chiara Ciociola and Luigi Reggi. The second case, by Tim Coughlan from the Open University, UK, showcases practical applications in the use of local and contextualised open data for the development of apps. The third case, written by Katie Shamash, Juan Pablo Alperin & Alessandra Bordini from Simon Fraser University, Canada, demonstrates how publishing students can engage, through data analysis, in very current debates around scholarly communications and be encouraged to publish their own findings. The fourth case by Alan Dix from Talis and University of Birmingham, UK, and Geoffrey Ellis from University of Konstanz, Germany, is unique because the data discussed in this case is self-produced, indeed ‘quantified self’ data, which was used with students as material for class discussion and, separately, as source data for another student’s dissertation project. Finally, the fifth case, presented by Virginia Power from University of the West of England, UK, examines strategies to develop data and statistical literacies in future librarians and knowledge managers, aiming to support and extend their theoretical understanding of the concept of the ‘knowledge society’ through the use of Open Data….(More)

The book can be downloaded here Open Data as Open Educational Resources

Predictive policing is ‘technological racism’

Curated on Posted on by Stefaan Verhulst

Shaun King at the New York Daily News: “The future is here.

For years now, the NYPD, the Miami PD, and many police departments around the country have been using new technology that claims it can predict where crime will happen and where police should focus their energies in order. They call it predictive policing. Months ago, I raised several red flags to such software because it does not appear to properly account for the presence of racism or racial profiling in how it predicts where crimes will be committed.

See, these systems claim to predict where crimes will happen based on prior arrest data. What they don’t account for is the widespread reality that race and racial profiling have everything to do with who is arrested and where they are arrested. For instance, study after study has shown that white people actually are more likely to sell drugs and do drugs than black people, but are exponentially less likely to be arrested for either crime. But, and this is where these systems fail, if the only data being entered into systems is based not on the more complex reality of who sells and purchases drugs, but on a racial stereotype, then the system will only perpetuate the racism that preceded it…

In essence, it’s not predicting who will sell drugs and where they will sell it, as much as it is actually predicting where a certain race of people may sell or purchase drugs. It’s technological racism at its finest.

Now, in addition to predictive policing, the state of Pennsylvania is pioneering predictive prison sentencing. Through complex questionnaires and surveys completed not by inmates, but by prison staff members, inmates may be given a smaller bail or shorter sentences or a higher bail and lengthier prison sentences. The surveys focus on family background, economic background, prior crimes, education levels and more.

When all of the data is scored, the result classifies prisoners as low, medium or high risk. While this may sound benign, it isn’t. No prisoner should ever be given a harsh sentence or an outrageous bail amount because of their family background or economic status. Even these surveys lend themselves to being racist and putting black and brown women and men in positions where it’s nearly impossible to get a good score because of prevalent problems in communities of color….(More)”

How big data and The Sims are helping us to build the cities of the future

Curated on Posted on by Stefaan Verhulst

The Next Web: “By 2050, the United Nations predicts that around 66 percent of the world’s population will be living in urban areas. It is expected that the greatest expansion will take place in developing regions such as Africa and Asia. Cities in these parts will be challenged to meet the needs of their residents, and provide sufficient housing, energy, waste disposal, healthcare, transportation, education and employment.

So, understanding how cities will grow – and how we can make them smarter and more sustainable along the way – is a high priority among researchers and governments the world over. We need to get to grips with the inner mechanisms of cities, if we’re to engineer them for the future. Fortunately, there are tools to help us do this. And even better, using them is a bit like playing SimCity….

Cities are complex systems. Increasingly, scientists studying cities have gone from thinking about “cities as machines”, to approaching “cities as organisms”. Viewing cities as complex, adaptive organisms – similar to natural systems like termite mounds or slime mould colonies – allows us to gain unique insights into their inner workings. …So, if cities are like organisms, it follows that we should examine them from the bottom-up, and seek to understand how unexpected large-scale phenomena emerge from individual-level interactions. Specifically, we can simulate how the behaviour of individual “agents” – whether they are people, households, or organisations – affect the urban environment, using a set of techniques known as “agent-based modelling”….These days, increases in computing power and the proliferation of big datagive agent-based modelling unprecedented power and scope. One of the most exciting developments is the potential to incorporate people’s thoughts and behaviours. In doing so, we can begin to model the impacts of people’s choices on present circumstances, and the future.

For example, we might want to know how changes to the road layout might affect crime rates in certain areas. By modelling the activities of individuals who might try to commit a crime, we can see how altering the urban environment influences how people move around the city, the types of houses that they become aware of, and consequently which places have the greatest risk of becoming the targets of burglary.

To fully realise the goal of simulating cities in this way, models need a huge amount of data. For example, to model the daily flow of people around a city, we need to know what kinds of things people spend their time doing, where they do them, who they do them with, and what drives their behaviour.

Without good-quality, high-resolution data, we have no way of knowing whether our models are producing realistic results. Big data could offer researchers a wealth of information to meet these twin needs. The kinds of data that are exciting urban modellers include:

  • Electronic travel cards that tell us how people move around a city.
  • Twitter messages that provide insight into what people are doing and thinking.
  • The density of mobile telephones that hint at the presence of crowds.
  • Loyalty and credit-card transactions to understand consumer behaviour.
  • Participatory mapping of hitherto unknown urban spaces, such as Open Street Map.

These data can often be refined to the level of a single person. As a result, models of urban phenomena no longer need to rely on assumptions about the population as a whole – they can be tailored to capture the diversity of a city full of individuals, who often think and behave differently from one another….(More)

Teaching Open Data for Social Movements: a Research Strategy

Curated on Posted on by Stefaan Verhulst

Alan Freihof Tygel and Maria Luiza Machado Campo at the Journal of Community Informatics: “Since the year 2009, the release of public government data in open formats has been configured as one of the main actions taken by national states in order to respond to demands for transparency and participation by the civil society. The United States and theUnited Kingdom were pioneers, and today over 46 countries have their own Open Government Data Portali , many of them fostered by the Open Government Partnership (OGP), an international agreement aimed at stimulating transparency.

The premise of these open data portals is that, by making data publicly available in re-usable formats, society would take care of building applications and services, and gain value from this data (Huijboom & Broek, 2011). According to the same authors, the discourse around open data policies also includes increasing democratic control and participation and strengthening law enforcement.

Several recent works argue that the impact of open data policies, especially the release of open data portals, is still difficult to assess (Davies & Bawa, 2012; Huijboom & Broek, 2011; Zuiderwijk, Janssen, Choenni, Meijer, & Alibaks, 2012). One important consideration is that “The gap between the promise and reality of OGD [Open Government Data] re-use cannot be addressed by technological solutions alone” (Davies, 2012). Therefore, sociotechnical approaches (Mumford, 1987) are mandatory.

The targeted users of open government data lie over a wide range that includes journalists, non-governmental organizations (NGO), civil society organizations (CSO), enterprises, researchers and ordinary citizens who want to audit governments’ actions. Among them, the focus of our research is on social (or grassroots) movements. These are groups of organized citizens at local, national or international level who drive some political action, normally placing themselves in opposition to the established power relations and claiming rights for oppressed groups.

A literature definition gives a social movement as “collective social actions with a socio-political and cultural approach, which enable distinct forms of organizing the population and expressing their demands” (Gohn, 2011).

Social movements have been using data in their actions repertory with several motivations (as can be seen in Table 1 and Listing 1). From our experience, an overview of several cases where social movements use open data reveals a better understanding of reality and a more solid basis for their claims as motivations. Additionally, in some cases data produced by the social movements was used to build a counter-hegemonic discourse based on data. An interesting example is the Citizen Public Depth Audit Movement which takes place in Brazil. This movement, which is part of an international network, claims that “significant amounts registered as public debt do not correspond to money collected through loans to the country” (Fattorelli, 2011), and thus origins of this debt should be proven. According to the movement, in 2014 45% of Brazil’s Federal spend was paid to debt services.

Recently, a number of works tried to develop comparison schemes between open data strategies (Atz, Heath, & Fawcet, 2015; Caplan et al., 2014; Ubaldi, 2013; Zuiderwijk & Janssen, 2014). Huijboom & Broek (2011) listed four categories of instruments applied by the countries to implement their open data policies:

  • voluntary approaches, such as general recommendations,
  • economic instruments,
  • legislation and control, and
  • education and training.

One of the conclusions is that the latter was used to a lesser extent than the others.

Social movements, in general, are composed of people with little experience of informatics, either because of a lack of opportunities or of interest. Although it is recognized that using data is important for a social movement’s objectives, the training aspect still hinders a wider use of it.

In order to address this issue, an open data course for social movements was designed. Besides building a strategy on open data education, the course also aims to be a research strategy to understand three aspects:

  • the motivations of social movements for using open data;
  • the impediments that block a wider and better use; and
  • possible actions to be taken to enhance the use of open data by social movements….(More)”

Advancing Open and Citizen-Centered Government

Curated on Posted on by Stefaan Verhulst

The White House: “Today, the United States released our third Open Government National Action Plan, announcing more than 40 new or expanded initiatives to advance the President’s commitment to an open and citizen-centered government….In the third Open Government National Action Plan, the Administration both broadens and deepens efforts to help government become more open and more citizen-centered. The plan includes new and impactful steps the Administration is taking to openly and collaboratively deliver government services and to support open government efforts across the country. These efforts prioritize a citizen-centric approach to government, including improved access to publicly available data to provide everyday Americans with the knowledge and tools necessary to make informed decisions.

One example is the College Scorecard, which shares data through application programming interfaces (APIs) to help students and families make informed choices about education. Open APIs help create an ecosystem around government data in which civil society can provide useful visual tools, making this data more accessible and commercial developers can enable even more value to be extracted to further empower students and their families. In addition to these newer approaches, the plan also highlights significant longstanding open government priorities such as access to information, fiscal transparency, and records management, and continues to push for greater progress in that work.

The plan also focuses on supporting implementation of the landmark 2030 Agenda for Sustainable Development, which sets out a vision and priorities for global development over the next 15 years and was adopted last month by 193 world leaders including President Obama. The plan includes commitments to harness open government and progress toward the Sustainable Development Goals (SDGs) both in the United States and globally, including in the areas of education, health, food security, climate resilience, science and innovation, justice and law enforcement. It also includes a commitment to take stock of existing U.S. government data that relates to the 17 SDGs, and to creating and using data to support progress toward the SDGs.

Some examples of open government efforts newly included in the plan:

  • Promoting employment by unlocking workforce data, including training, skill, job, and wage listings.
  • Enhancing transparency and participation by expanding available Federal services to theOpen311 platform currently available to cities, giving the public a seamless way to report problems and request assistance.
  • Releasing public information from the electronically filed tax forms of nonprofit and charitable organizations (990 forms) as open, machine-readable data.
  • Expanding access to justice through the White House Legal Aid Interagency Roundtable.
  • Promoting open and accountable implementation of the Sustainable Development Goals….(More)”

Testing governance: the laboratory lives and methods of policy innovation labs

Curated on Posted on by Stefaan Verhulst

Ben Williamson at Code Acts in Education: “Digital technologies are increasingly playing a significant role in techniques of governance in sectors such as education as well as healthcare, urban management, and in government innovation and citizen engagement in government services. But these technologies need to be sponsored and advocated by particular individuals and groups before they are embedded in these settings.

Testing governance cover

I have produced a working paper entitled Testing governance: the laboratory lives and methods of policy innovation labs which examines the role of innovation labs as sponsors of new digital technologies of governance. By combining resources and practices from politics, data analysis, media, design, and digital innovation, labs act as experimental R&D labs and practical ideas organizations for solving social and public problems, located in the borderlands between sectors, fields and disciplinary methodologies. Labs are making methods such as data analytics, design thinking and experimentation into a powerful set of governing resources.They are, in other words, making digital methods into key techniques for understanding social and public issues, and in the creation and circulation of solutions to the problems of contemporary governance–in education and elsewhere.

The working paper analyses the key methods and messages of the labs field, in particular by investigating the documentary history of Futurelab, a prototypical lab for education research and innovation that operated in Bristol, UK, between 2002 and 2010, and tracing methodological continuities through the current wave of lab development. Centrally, the working paper explores Futurelab’s contribution to the production and stabilization of a ‘sociotechnical imaginary’ of the future of education specifically, and to the future of public services more generally. It offers some preliminary analysis of how such an imaginary was embedded in the ‘laboratory life’ of Futurelab, established through its organizational networks, and operationalized in its digital methods of research and development as well as its modes of communication….(More)”

Viscous Open Data: The Roles of Intermediaries in an Open Data Ecosystem

Curated on Posted on by Stefaan Verhulst

François van Schalkwyk, Michelle Willmers & Maurice McNaughton in Journal: “Information Technology for Development”: “Open data have the potential to improve the governance of universities as public institutions. In addition, open data are likely to increase the quality, efficacy and efficiency of the research and analysis of higher education systems by providing a shared empirical base for critical interrogation and reinterpretation. Drawing on research conducted by the Emerging Impacts of Open Data in Developing Countries project, and using an ecosystems approach, this research paper considers the supply, demand and use of open data as well as the roles of intermediaries in the governance of South African public higher education. It shows that government’s higher education database is a closed and isolated data source in the data ecosystem; and that the open data that are made available by government is inaccessible and rarely used. In contrast, government data made available by data intermediaries in the ecosystem are being used by key stakeholders. Intermediaries are found to play several important roles in the ecosystem: (i) they increase the accessibility and utility of data; (ii) they may assume the role of a “keystone species” in a data ecosystem; and (iii) they have the potential to democratize the impacts and use of open data. The article concludes that despite poor data provision by government, the public university governance open data ecosystem has evolved because intermediaries in the ecosystem have reduced the viscosity of government data. Further increasing the fluidity of government open data will improve access and ensure the sustainability of open data supply in the ecosystem….(More)”

US Administration Celebrates Five-Year Anniversary of Challenge.gov

Curated on Posted on by Stefaan Verhulst

White House Fact Sheet: “Today, the Administration is celebrating the five-year anniversary of Challenge.gov, a historic effort by the Federal Government to collaborate with members of the public through incentive prizes to address our most pressing local, national, and global challenges. True to the spirit of the President’s charge from his first day in office, Federal agencies have collaborated with more than 200,000 citizen solvers—entrepreneurs, citizen scientists, students, and more—in more than 440 challenges, on topics ranging from accelerating the deployment of solar energy, to combating breast cancer, to increasing resilience after Hurricane Sandy.

Highlighting continued momentum from the President’s call to harness the ingenuity of the American people, the Administration is announcing:

  • Nine new challenges from Federal agencies, ranging from commercializing NASA technology, to helping students navigate their education and career options, to protecting marine habitats.
  • Expanding support for use of challenges and prizes, including new mentoring support from the General Services Administration (GSA) for interested agencies and a new $244 million innovation platform opened by the U.S. Agency for International Development (USAID) with over 70 partners.

In addition, multiple non-governmental institutions are announcing 14 new challenges, ranging from improving cancer screenings, to developing better technologies to detect, remove, and recover excess nitrogen and phosphorus from water, to increasing the resilience of island communities….

Expanding the Capability for Prize Designers to find one another

The GovLab and MacArthur Foundation Research Network on Opening Governance will launch an expert network for prizes and challenges. The Governance Lab (GovLab) and MacArthur Foundation Research Network on Opening Governance will develop and launch the Network of Innovators (NoI) expert networking platform. NoI will make easily searchable the know-how of innovators on topics ranging from developing prize-backed challenges, opening up data, and use of crowdsourcing for public good. Platform users will answer questions about their skills and experiences, creating a profile that enables them to be matched to those with complementary knowledge to enable mutual support and learning. A beta version for user testing within the Federal prize community will launch in early October, with a full launch at the end of October. NoI will be open to civil servants around the world…(More)”

Web design plays a role in how much we reveal online

Curated on Posted on by Stefaan Verhulst

European Commission: “A JRC study, “Nudges to Privacy Behaviour: Exploring an Alternative Approach to Privacy Notices“, used behavioural sciences to look at how individuals react to different types of privacy notices. Specifically, the authors analysed users’ reactions to modified choice architecture (i.e. the environment in which decisions take place) of web interfaces.

Two types of privacy behaviour were measured: passive disclosure, when people unwittingly disclose personal information, and direct disclosure, when people make an active choice to reveal personal information. After testing different designs with over 3 000 users from the UK, Italy, Germany and Poland, results show web interface affects decisions on disclosing personal information. The study also explored differences related to country of origin, gender, education level and age.

A depiction of a person’s face on the website led people to reveal more personal information. Also, this design choice and the visualisation of the user’s IP or browsing history had an impact on people’s awareness of a privacy notice. If confirmed, these features are particularly relevant for habitual and instinctive online behaviour.

With regard to education, users who had attended (though not necessarily graduated from) college felt significantly less observed or monitored and more comfortable answering questions than those who never went to college. This result challenges the assumption that the better educated are more aware of information tracking practices. Further investigation, perhaps of a qualitative nature, could help dig deeper into this issue. On the other hand, people with a lower level of education were more likely to reveal personal information unwittingly. This behaviour appeared to be due to the fact that non-college attendees were simply less aware that some online behaviour revealed personal information about themselves.

Strong differences between countries were noticed, indicating a relation between cultures and information disclosure. Even though participants in Italy revealed the most personal information in passive disclosure, in direct disclosure they revealed less than in other countries. Approximately 75% of participants in Italy chose to answer positively to at least one stigmatised question, compared to 81% in Poland, 83% in Germany and 92% in the UK.

Approximately 73% of women answered ‘never’ to the questions asking whether they had ever engaged in socially stigmatised behaviour, compared to 27% of males. This large difference could be due to the nature of the questions (e.g. about alcohol consumption, which might be more acceptable for males). It could also suggest women feel under greater social scrutiny or are simply more cautious when disclosing personal information.

These results could offer valuable insights to inform European policy decisions, despite the fact that the study has targeted a sample of users in four countries in an experimental setting. Major web service providers are likely to have extensive amounts of data on how slight changes to their services’ privacy controls affect users’ privacy behaviour. The authors of the study suggest that collaboration between web providers and policy-makers can lead to recommendations for web interface design that allow for conscientious disclosure of privacy information….(More)”

Five principles for applying data science for social good

Curated on Posted on by Stefaan Verhulst

Jake Porway at O’Reilly: “….Every week, a data or technology company declares that it wants to “do good” and there are countless workshops hosted by major foundations musing on what “big data can do for society.” Add to that a growing number of data-for-good programs from Data Science for Social Good’s fantastic summer program toBayes Impact’s data science fellowships to DrivenData’s data-science-for-good competitions, and you can see how quickly this idea of “data for good” is growing.

Yes, it’s an exciting time to be exploring the ways new datasets, new techniques, and new scientists could be deployed to “make the world a better place.” We’ve already seen deep learning applied to ocean health,satellite imagery used to estimate poverty levels, and cellphone data used to elucidate Nairobi’s hidden public transportation routes. And yet, for all this excitement about the potential of this “data for good movement,” we are still desperately far from creating lasting impact. Many efforts will not only fall short of lasting impact — they will make no change at all….

So how can these well-intentioned efforts reach their full potential for real impact? Embracing the following five principles can drastically accelerate a world in which we truly use data to serve humanity.

1. “Statistics” is so much more than “percentages”

We must convey what constitutes data, what it can be used for, and why it’s valuable.

There was a packed house for the March 2015 release of the No Ceilings Full Participation Report. Hillary Clinton, Melinda Gates, and Chelsea Clinton stood on stage and lauded the report, the culmination of a year-long effort to aggregate and analyze new and existing global data, as the biggest, most comprehensive data collection effort about women and gender ever attempted. One of the most trumpeted parts of the effort was the release of the data in an open and easily accessible way.

I ran home and excitedly pulled up the data from the No Ceilings GitHub, giddy to use it for our DataKind projects. As I downloaded each file, my heart sunk. The 6MB size of the entire global dataset told me what I would find inside before I even opened the first file. Like a familiar ache, the first row of the spreadsheet said it all: “USA, 2009, 84.4%.”

What I’d encountered was a common situation when it comes to data in the social sector: the prevalence of inert, aggregate data. ….

2. Finding problems can be harder than finding solutions

We must scale the process of problem discovery through deeper collaboration between the problem holders, the data holders, and the skills holders.

In the immortal words of Henry Ford, “If I’d asked people what they wanted, they would have said a faster horse.” Right now, the field of data science is in a similar position. Framing data solutions for organizations that don’t realize how much is now possible can be a frustrating search for faster horses. If data cleaning is 80% of the hard work in data science, then problem discovery makes up nearly the remaining 20% when doing data science for good.

The plague here is one of education. …

3. Communication is more important than technology

We must foster environments in which people can speak openly, honestly, and without judgment. We must be constantly curious about each other.

At the conclusion of one of our recent DataKind events, one of our partner nonprofit organizations lined up to hear the results from their volunteer team of data scientists. Everyone was all smiles — the nonprofit leaders had loved the project experience, the data scientists were excited with their results. The presentations began. “We used Amazon RedShift to store the data, which allowed us to quickly build a multinomial regression. The p-value of 0.002 shows …” Eyes glazed over. The nonprofit leaders furrowed their brows in telegraphed concentration. The jargon was standing in the way of understanding the true utility of the project’s findings. It was clear that, like so many other well-intentioned efforts, the project was at risk of gathering dust on a shelf if the team of volunteers couldn’t help the organization understand what they had learned and how it could be integrated into the organization’s ongoing work…..

4. We need diverse viewpoints

To tackle sector-wide challenges, we need a range of voices involved.

One of the most challenging aspects to making change at the sector level is the range of diverse viewpoints necessary to understand a problem in its entirety. In the business world, profit, revenue, or output can be valid metrics of success. Rarely, if ever, are metrics for social change so cleanly defined….

Challenging this paradigm requires diverse, or “collective impact,” approaches to problem solving. The idea has been around for a while (h/t Chris Diehl), but has not yet been widely implemented due to the challenges in successful collective impact. Moreover, while there are many diverse collectives committed to social change, few have the voice of expert data scientists involved. DataKind is piloting a collective impact model called DataKind Labs, that seeks to bring together diverse problem holders, data holders, and data science experts to co-create solutions that can be applied across an entire sector-wide challenge. We just launchedour first project with Microsoft to increase traffic safety and are hopeful that this effort will demonstrate how vital a role data science can play in a collective impact approach.

5. We must design for people

Data is not truth, and tech is not an answer in-and-of-itself. Without designing for the humans on the other end, our work is in vain.

So many of the data projects making headlines — a new app for finding public services, a new probabilistic model for predicting weather patterns for subsistence farmers, a visualization of government spending — are great and interesting accomplishments, but don’t seem to have an end user in mind. The current approach appears to be “get the tech geeks to hack on this problem, and we’ll have cool new solutions!” I’ve opined that, though there are many benefits to hackathons, you can’t just hack your way to social change….(More)”