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datarev-quotes.md

This is the "data revolution": the opportunity to improve the data that is essential for decision-making, accountability and solving development challenges. This report calls on governments and the UN to act to enable data to play its full role in the realisation of sustainable development by closing key gaps in access and use of data: between developed and developing countries, between information-rich and information-poor people, and between the private and public sectors.

This report is not about how to create a data revolution – it is already happening – but how to mobilise it for sustainable development.

The data revolution is... a growing demand for data from all parts of society.

There is also a risk of growing inequality. Major gaps are already opening up between the data haves and have-nots. Without action, a whole new inequality frontier will open up, splitting the world between those who know, and those who do not. Many people are excluded from the new world of data and information by language, poverty, lack of education, lack of technology infrastructure, remoteness or prejudice and discrimination. While the use of new technologies has exploded everywhere in the last ten years, the costs are still prohibitive for many. In Nicaragua, Bolivia and Honduras, for example, the price of a mobile broadband subscription exceeds 10% of average monthly GDP per capita, compared to France and the Republic of Korea where it is less than 0.1%.ii The information society should not force a choice between food and knowledge.

More, and more open, data can help ensure that knowledge is shared, creating a world of informed and empowered citizens, capable of holding decision-makers accountable for their actions.

Data that are not used or not usable. To be useful, data must be of high quality, at a level of disaggregation that is appropriate to the issue at hand, and must be made accessible to those who want or need to use them. Too many countries still have data that are of insufficient quality to be useful in making decisions, holding governments to account or fostering innovation.

Access, too, is often restricted behind technical and/or legal barriers, or restricted by governments or companies that fear too much transparency, all of which prevent or limit effective use of data. Data buried in pdf documents, for example, are much harder for potential users to work with; administrative data that are not transferred to statistical offices; data generated by the private sector or by academic researchers that are never released or data released too late to be useful; data that cannot be translated into action because of lack of operational tools to leverage them.

The priority should always be to use data and information to improve outcomes, experiences and possibilities for people in the short and long term.

Our Vision for the Future

By 2020:

...

Civil society organisations and individuals hold governments and companies accountable using evidence on the impact of their actions, provide feedback to data producers, develop data literacy and help communities and individuals to generate and use data, to ensure accountability and make better decisions for themselves.

Call to Action

Principles & Standards

DATA USABILITY AND CURATION: Too often data is presented in ways that cannot be understood by most people. The data architecture should therefore place great emphasis on user-centred design and user friendly interfaces. Communities of “information intermediaries” should be fostered to develop new tools that can translate raw data into information for a broader constituency of non-technical potential users and enable citizens and other data users to provide feedback.

Capacity & Resources

WE RECOMMEND: that a proposal be developed for a new funding stream and innovative financing mechanisms to support the data revolution for sustainable development, for discussion at the “Third International Conference on Financing for Development”, which will take place in Addis Ababa in July 2015. The proposal should be built on the following five pillars:

  • Investment needs: An analysis of the scale of investments needed for the establishment of a modern system to monitor progress towards SDGs, especially in developing countries. This analysis, building on various attempts currently ongoing, should highlight the costs as well as opportunities for efficiency gains associated with different production systems. Particular attention should be paid to the need for investment in data to analyse the challenges facing the very poorest people and communities, and to involve them as users of data.
  • Managing funds: A proposal on how to manage and monitor new funding for the data revolution for sustainable development, taking stock of existing sources and forms of funding. This should look at how funding from a range of sources could be used most effectively, and managed and disbursed in line with national priorities to incentivise innovation, collaboration and whole systems approaches, while also encouraging creativity and experimentation and accepting that not all initiatives will succeed.
  • Private sector participation: A proposal on how to leverage the resources and creativity of the private sector, including an examination of suggestions for creating incentives for the private sector to invest given companies’ expectations of time horizon and returns.
  • Capacity development: A proposal to improve existing arrangements for fostering the necessary capacity development and technology transfer. This should include upgrading the “National Strategies for the Development of Statistics” (NSDS) to do better at coordinated and long-term planning, and in identifying sound investments and engaging non-official data producers in a cooperative effort to speed up the production, dissemination and use of data, strengthening civil society’s capacity and resources to produce, use and disseminate data.
  • Global data literacy: A proposal for a special investment to increase global data literacy. To close the gap between people able to benefit from data and those who cannot, in 2015 the UN should work with other organisations to develop an education program and promote new learning approaches to improve people’s, infomediaries’ and public servants’ data literacy. Special efforts should be made to reach people living in poverty through dedicated programmes.
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examples.md

As part of a project to engage young people in disaster risk reduction, teenagers in Rio de Janeiro have used cameras attached to kites to gather aerial images, helping to identify the presence or absence of drainage systems, the availability of sanitation facilities, and potential impediments to evacuation.

In 2014, the governments of Indonesia and the Philippines used near real-time satellite data to more effectively respond to rampant forest fires, and crack down on illegal burning by corporations.

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General education issues in developing countries:

  • Low preschool ed > inadequate preparation > low enrollment/high dropout
  • Teacher availability/quality, particularly for math
  • Math teachers may be ill equipped for stats curricula (also in developed countries)
  • High teacher/student ratios
  • Low expenditure

Definition of Data Literacy

Statistical Literacy, from ISLP, includes:

  • Knowledge of basic statistical key figures
  • Understanding concepts describing society (e.g. inflation, unemployment, GDP, etc.)
  • Basic information about research methods (from the viewpoint of both use and interpretation)
  • Basic information about visualisation (both about visualisation and interpretation)
  • Knowledge about data sources and the ability to evaluate the used data sources.

Data is useless w/o the skills talks about 3 key components for data literacy in businesses:

  1. Ready & willing to experiment (hypotheses, testing, scientific method)
  2. Adept at mathematical reasoning
  3. Able to see the big (data) picture:

You might call this “data literacy”: competence in finding, manipulating, managing, and interpreting data, including not just numbers but also text and images. Data literacy skills must spread far beyond their usual home, the IT function, and become an integral aspect of every business function and activity.

An academic perspective on data literacy from the NC Dept of Public Instruction:

Data literacy refers to one's level of understanding of how to find, evaluate, and use data to inform instruction.

Becoming data literate means developing skills that help to ask significant questions, devise sensible and efficient ways to answer these questions, and then respond to the answers with changes to learning environments and instructional practices. A data literate person considers relevant data when making important decisions. i.e., data-driven decision making

Other data literacy definitions frequently use a triptych formula:

  • find, evaluate and use data
  • find, analyze, and create practical applications using data

Perhaps there is also an ethical dimension to data literacy: the importance of respecting privacy, licensing, etc.

Statistical Activities

For Educators

But NSOs have also recognized that traditional curricula are not enough:

Now more than ever statistical education and statistical literacy for the public in general need to start acknowledging that the traditional venues are not enough and that there are many alternative venues to achieve statistical literacy for the population.

For Citizens

For Ministries

ISLP

Government Statistical Offices and Statistical Literacy - summarizes 6 countries' current efforts in promoting statistical literacy:

  • Portugal: ALEA program - resources for classroom education
  • New Zealand: 3-pronged strategy focused on skills for 1) Stats NZ itself; 2) other public ministries, and; 3) schools and small businesses
  • Canada: provides training seminars on request: for professionals (journalists, social scientists, marketers, etc). Extensive Education Outreach program - school partnerships
  • Finland: online learning resources on website; several courses aimed at teachers, librarians, other professionals; Tools for Learners (classroom support)
  • Italy: mostly online resources for classrooms
  • Australia: identifies, students, policymakers, small businesses, and general public as targets, but talks only about the Census@School program

In addition, every NSO has an education section on their website. But NSOs consistently state that they themselves cannot provide education, as they are not education specialists, but they support professional teaching through materials, curriculum development, etc.

Contacts

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