Code and Clay, Data and Dirt: Five Thousand Years of Urban Media

Curated on Posted on by Stefaan Verhulst

Book by Shannon Mattern: “For years, pundits have trumpeted the earthshattering changes that big data and smart networks will soon bring to our cities. But what if cities have long been built for intelligence, maybe for millennia? In Code and Clay, Data and Dirt Shannon Mattern advances the provocative argument that our urban spaces have been “smart” and mediated for thousands of years.

Offering powerful new ways of thinking about our cities, Code and Clay, Data and Dirt goes far beyond the standard historical concepts of origins, development, revolutions, and the accomplishments of an elite few. Mattern shows that in their architecture, laws, street layouts, and civic knowledge—and through technologies including the telephone, telegraph, radio, printing, writing, and even the human voice—cities have long negotiated a rich exchange between analog and digital, code and clay, data and dirt, ether and ore.

Mattern’s vivid prose takes readers through a historically and geographically broad range of stories, scenes, and locations, synthesizing a new narrative for our urban spaces. Taking media archaeology to the city’s streets, Code and Clay, Data and Dirt reveals new ways to write our urban, media, and cultural histories….(More)”.

Business Models For Sustainable Research Data Repositories

Curated on Posted on by Stefaan Verhulst

OECD Report: “In 2007, the OECD Principles and Guidelines for Access to Research Data from Public Funding were published and in the intervening period there has been an increasing emphasis on open science. At the same time, the quantity and breadth of research data has massively expanded. So called “Big Data” is no longer limited to areas such as particle physics and astronomy, but is ubiquitous across almost all fields of research. This is generating exciting new opportunities, but also challenges.

The promise of open research data is that they will not only accelerate scientific discovery and improve reproducibility, but they will also speed up innovation and improve citizen engagement with research. In short, they will benefit society as a whole. However, for the benefits of open science and open research data to be realised, these data need to be carefully and sustainably managed so that they can be understood and used by both present and future generations of researchers.

Data repositories – based in local and national research institutions and international bodies – are where the long-term stewardship of research data takes place and hence they are the foundation of open science. Yet good data stewardship is costly and research budgets are limited. So, the development of sustainable business models for research data repositories needs to be a high priority in all countries. Surprisingly, perhaps, little systematic analysis has been done on income streams, costs, value propositions, and business models for data repositories, and that is the gap this report attempts to address, from a science policy perspective…..

This project was designed to take up the challenge and to contribute to a better understanding of how research data repositories are funded, and what developments are occurring in their funding. Central questions included:

  • How are data repositories currently funded, and what are the key revenue sources?
  • What innovative revenue sources are available to data repositories?
  • How do revenue sources fit together into sustainable business models?
  • What incentives for, and means of, optimising costs are available?
  • What revenue sources and business models are most acceptable to key stakeholders?…(More)”

Understanding Design Thinking, Lean, and Agile

Curated on Posted on by Stefaan Verhulst

Free ebook by Jonny Schneider: “Highly touted methodologies, such as Agile, Lean, and Design Thinking, leave many organizations bamboozled by an unprecedented array of processes, tools, and methods for digital product development. Many teams meet their peril trying to make sense of these options. How do the methods fit together to achieve the right outcome? What’s the best approach for your circumstances?

In this insightful report, Jonny Schneider from ThoughtWorks shows you how to diagnose your situation, understand where you need more insight to move forward, and then choose from a range of tactics that can move your team closer to clarity.

Blindly applying any model, framework, or method seldom delivers the desired result. Agile began as a better answer for delivering software. Lean focuses on product success. And Design Thinking is an approach for exploring opportunities and problems to solve. This report shows you how to evaluate your situation before committing to one, two, or all three of these techniques.

  • Understand how design thinking, the lean movement, and agile software development can make a difference
  • Define your beliefs and assumptions as well as your strategy
  • Diagnose the current condition and explore possible futures
  • Decide what to learn, and how to learn it, through fast research and experimentation
  • Decentralize decisions with purpose-driven, collaborative teams
  • Prioritize and measure value by responding to customer demand…(More)”

There’s more to evidence-based policies than data: why it matters for healthcare

Curated on Posted on by Stefaan Verhulst

 at The Conversation: “The big question is: how can countries strengthen their health systems to deliver accessible, affordable and equitable care when they are often under-financed and governed in complex ways?

One answer lies in governments developing policies and programmes that are informed by evidence of what works or doesn’t. This should include what we would call “traditional data”, but should also include a broader definition of evidence. This would mean including, for example, information from citizens and stakeholders as well as programme evaluations. In this way, policies can be made more relevant for the people they affect.

Globally there is an increasing appreciation for this sort of policymaking that relies of a broader definition of evidence. Countries such as South Africa, Ghana and Thailand provide good examples.

What is evidence?

Using evidence to inform the development of health care has grown out of the use of science to choose the best decisions. It is based on data being collected in a methodical way. This approach is useful but it can’t always be neatly applied to policymaking. There are several reasons for this.

The first is that there are many different types of evidence. Evidence is more than data, even though the terms are often used to mean the same thing. For example, there is statistical and administrative data, research evidence, citizen and stakeholder information as well as programme evaluations.

The challenge is that some of these are valued more than others. More often than not, statistical data is more valued in policymaking. But both researchers and policymakers must acknowledge that for policies to be sound and comprehensive, different phases of policymaking process would require different types of evidence.

Secondly, data-as-evidence is only one input into policymaking. Policymakers face a long list of pressures they must respond to, including time, resources, political obligations and unplanned events.

Researchers may push technically excellent solutions designed in research environments. But policymakers may have other priorities in mind: are the solutions being put to them practical and affordable?Policymakers also face the limitations of having to balance various constituents while straddling the constraints of the bureaucracies they work in.

Researchers must recognise that policymakers themselves are a source of evidence of what works or doesn’t. They are able to draw on their own experiences, those of their constituents, history and their contextual knowledge of the terrain.

What this boils down to is that for policies that are based on evidence to be effective, fewer ‘push/pull’ models of evidence need to be used. Instead the models where evidence is jointly fashioned should be employed.

This means that policymakers, researchers and other key actors (like health managers or communities) must come together as soon as a problem is identified. They must first understand each other’s ideas of evidence and come to a joint conclusion of what evidence would be appropriate for the solution.

In South Africa, for example, the Department of Environmental Affairshas developed a four-phase process to policymaking. In the first phase, researchers and policymakers come together to set the agenda and agree on the needed solution. Their joint decision is then reviewed before research is undertaken and interpreted together….(More)”.

Transitioning Towards a Knowledge Society: Qatar as a Case Study

Curated on Posted on by Stefaan Verhulst

Book by Julia Gremm, Julia Barth, Kaja J. Fietkiewicz and Wolfgang G. Stock: “The book offers a critical evaluation of Qatar’s path from oil- and gas-based industries to a knowledge-based economy. This book gives basic information about the region and the country, including the geographic and demographic data, the culture, the politics and the economy, the health care conditions and the education system. It introduces the concepts of knowledge society and knowledge-based development and adds factual details about Qatar by interpreting indicators of the development status. Subsequently, the research methods that underlie the study are described, which offers information on the eGovernment study analyzing the government-citizen relationship, higher education institutions and systems, its students and the students’ way into the labor market. This book has an audience with economists, sociologists, political scientists, geographers, information scientists and other researchers on the knowledge society, but also all researchers and practitioners interested in the Arab Oil States and their future….(More)”.

Blockchain: Unpacking the disruptive potential of blockchain technology for human development.

Curated on Posted on by Stefaan Verhulst

IDRC white paper: “In the scramble to harness new technologies to propel innovation around the world, artificial intelligence, robotics, machine learning, and blockchain technologies are being explored and deployed in a wide variety of contexts globally.

Although blockchain is one of the most hyped of these new technologies, it is also perhaps the least understood. Blockchain is the distributed ledger — a database that is shared across multiple sites or institutions to furnish a secure and transparent record of events occurring during the provision of a service or contract — that supports cryptocurrencies (digital assets designed to work as mediums of exchange).

Blockchain is now underpinning applications such as land registries and identity services, but as its popularity grows, its relevance in addressing socio-economic gaps and supporting development targets like the globally-recognized UN Sustainable Development Goals is critical to unpack. Moreover, for countries in the global South that want to be more than just end users or consumers, the complex infrastructure requirements and operating costs of blockchain could prove challenging. For the purposes of real development, we need to not only understand how blockchain is workable, but also who is able to harness it to foster social inclusion and promote democratic governance.

This white paper explores the potential of blockchain technology to support human development. It provides a non-technical overview, illustrates a range of applications, and offers a series of conclusions and recommendations for additional research and potential development programming….(More)”.

Decoding Data Use: What evidence do world leaders want to achieve their goals?

Curated on Posted on by Stefaan Verhulst

Paper by Samantha Custer, Takaaki Masaki, and Carolyn Iwicki: “Information is “never the hero”, but it plays a supporting role in how leaders allocate scarce resources and accelerate development in their communities. Even in low- and middle-income countries, decision-makers have ample choices in sourcing evidence from a growing field of domestic and international data providers. However, more information is not necessarily better if it misses the mark for what leaders need to monitor their country’s progress. Claims that information is the “world’s most valuable resource” and calls for a “data revolution” will ring hollow if we can’t decode what leaders actually use — and why.

In a new report, Decoding Data Use: How leaders source data and use it to accelerate development, AidData reveals what 3500 leaders from 126 countries have to say about the types of data or analysis they use, from what sources, and for which purposes in the context of their work.  We analyze responses to AidData’s 2017 Listening to Leaders (LTL) Survey to offer insights to help funders, producers, advocates, and infomediaries of development data understand how to position themselves for greater impact….(more)”.

Data for Development

Curated on Posted on by Stefaan Verhulst

The 2017 volume of the  Development Co-operation Report by the OECD focuses on Data for Development:  “Big Data” and “the Internet of Things” are more than buzzwords: the data revolution is transforming the way that economies and societies are functioning across the planet. The Sustainable Development Goals along with the data revolution are opportunities that should not be missed: more and better data can help boost inclusive growth, fight inequalities and combat climate change. These data are also essential to measure and monitor progress against the Sustainable Development Goals.

The value of data in enabling development is uncontested. Yet, there continue to be worrying gaps in basic data about people and the planet and weak capacity in developing countries to produce the data that policy makers need to deliver reforms and policies that achieve real, visible and long-lasting development results. At the same time, investing in building statistical capacity – which represented about 0.30% of ODA in 2015 – is not a priority for most providers of development assistance.

There is a need for stronger political leadership, greater investment and more collective action to bridge the data divide for development. With the unfolding data revolution, developing countries and donors have a unique chance to act now to boost data production and use for the benefit of citizens. This report sets out priority actions and good practices that will help policy makers and providers of development assistance to bridge the global data divide, notably by strengthening statistical systems in developing countries to produce better data for better policies and better lives…(More)”.

Evidence-Based Policy Mistakes

Curated on Posted on by Stefaan Verhulst

Kaushik Basu at Project Syndicate: “… it is important to recognize that data alone are not enough to determine future expectations or policies. While there is certainly value in collecting data (via, for example, randomized control trials), there is also a need for deductive and inductive reasoning, guided by common sense – and not just on the part of experts. By dismissing the views and opinions of ordinary people, economists may miss out on crucial insights.

People’s everyday experiences provide huge amounts of potentially useful information. While a common-sense approach based on individual experience is not the most “scientific,” it should not be dismissed out of hand. A meteorologist might detect a coming storm by plugging data from myriad sources – atmospheric sensors, weather balloons, radar, and satellites – into complex computer models. But that doesn’t mean that the sight of gathering clouds in the sky is not also a legitimate sign that one might need an umbrella – even if the weather forecast promises sunshine.

Intuition and common sense have been critical to our evolution. After all, had humans not been able to draw reasonably accurate conclusions about the world through experience or observation, we wouldn’t have survived as a species.

The development of more systematic approaches to scientific inquiry has not diminished the need for such intuitive reasoning. In fact, there are important and not obvious truths that are best deduced using pure reason.

Consider the Pythagorean Theorem, which establishes the relation among the three sides of a right triangle. If all conclusions had to be reached by combing through large data sets, Pythagoras, who is believed to have devised the theorem’s first proof, would have had to measure a huge number of right triangles. In any case, critics would likely argue that he had looked at a biased sample, because all of the triangles examined were collected from the Mediterranean region.

Inductive reasoning, too, is vital to reach certain kinds of knowledge. We “know” that an apple will not remain suspended in mid-air, because we have seen so many objects fall. But such reasoning is not foolproof. As Bertrand Russell pointed out, “The man who has fed the chicken every day throughout its life at last wrings its neck instead, showing that more refined views as to the uniformity of nature would have been useful to the chicken.”

Of course, many policymakers – not just the likes of Erdoğan and Trump – make bad decisions not because of a misunderstanding of the evidence, but because they prefer to pursue politically expedient measures that benefit their benefactors or themselves. In such cases, exposing the inappropriateness of their supposed evidence may be the only option.

But, for the rest, the imperative must be to advocate for a more comprehensive approach, in which leaders use “reasoned intuition” to draw effective conclusions based on hard data. Only then will the age of effective evidence-based policymaking really begin….(More)”.

GovEx Launches First International Open Data Standards Directory

Curated on Posted on by Stefaan Verhulst

GT Magazine: “…A nonprofit gov tech group has created an international open data standards directory, aspiring to give cities a singular resource for guidance on formatting data they release to the public…The nature of municipal data is nuanced and diverse, and the format in which it is released often varies depending on subject matter. In other words, a format that works well for public safety data is not necessarily the same that works for info about building permits, transit or budgets. Not having a coordinated and agreed-upon resource to identify the best standards for these different types of info, Nicklin said, creates problems.

One such problem is that it can be time-consuming and challenging for city government data workers to research and identify ideal formats for data. Another is that the lack of info leads to discord between different jurisdictions, meaning one city might format a data set about economic development in an entirely different way than another, making collaboration and comparisons problematic.

What the directory does is provide a list of standards that are in use within municipal governments, as well as an evaluation based on how frequent that use is, whether the format is machine-readable, and whether users have to pay to license it, among other factors.

The directory currently contains 60 standards, some of which are in Spanish, and those involved with the project say they hope to expand their efforts to include more languages. There is also a crowdsourcing component to the directory, in that users are encouraged to make additions and updates….(More)”