{"id":981,"title":"GED @ … the re:publica 2014","link":"https:\/\/bst-europe.eu\/de\/globalization\/ged-viz-republica-2014-2\/","date":"6. Mai 2014","date_unix":1399398584,"date_modified_unix":1399398584,"date_iso":"2014-05-06T17:49:44+00:00","content":"

\"re:publica<\/a><\/p>\n

Making sense of our world at a time of rapidly growing complexity is becoming more and more of a challenge. At the same time, the amount of available data is exploding, providing a foundation for many insights yet to be discovered. But how do we get from data to knowledge? In this re:publica session, the role of data visualization in exploring, understanding and communicating the interdependent developments of our globalized world will be looked at from different angles.<\/p>\n

\u00a0Globalization and technological progress are the strongest drivers of worldwide societal change. On the one hand, this leads to an incredible increase in complexity that challenges our understanding of the world, creates new systemic risks and calls for a radical re-thinking of the foundations of decision-making. On the other hand, unimaginable amounts of data are becoming accessible, from real-time data such as mobile phone connections, tweets, social network evolution, local transport monitoring or sales figures to high-quality aggregated data, e.g., on trade, migration, energy use, well-being or CO2-emissions, provided by international institutions such as the UN, the OECD, the IMF or the World Bank. All these data provide a huge treasure trove of evidence that in one way or another mirrors myriads of aspects of the world we live in.<\/div>\n
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So how can we exploit this treasure trove to make sense of global developments? How do we arrive at improved ways of dealing with global complexity, at more informed debates and eventually at better decision-making, both on an individual and at a collective level? How do we get from evidence to insights, from data to knowledge?<\/p>\n

The full sequence of data-processing involves a number of (interwoven, non-linear) steps: data needs to be explored, analyzed, interpreted and communicated. Yet, humans are in fact quite bad at working with data displayed as numbers. That\u2019s why data visualization plays a crucial role in each of these steps. Moreover, visualization can help to identify new patterns and provide completely new views of topics that defy mere statistical analysis.<\/p>\n

As an example, the\u00a0Global Economic Dynamics (GED)\u00a0team at the\u00a0Bertelsmann Stiftung<\/a>\u00a0has developed\u00a0GED VIZ<\/a>, a web-tool that lets users create slideshows of interactive visualizations to be embedded in other web pages, as shown:<\/p>\n

[iframe „<iframe src=“\/\/viz.blogs.bertelsmann-stiftung.de\/globaleurope\/1853?lang=en“ width=“800″ height=“600″ style=“border: 1px solid #eee“ mozallowfullscreen=“true“ webkitallowfullscreen=“true“ allowfullscreen=“true“><a href=“\/\/viz.blogs.bertelsmann-stiftung.de\/globaleurope\/1853?lang=en“ target=“_blank“>GED VIZ Slideshow<\/a><\/iframe>“]<\/p>\n

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Instead of merely comparing the economic performance of countries (e.g., with respect to GDP, government debt or unemployment), GED VIZ focuses on showing exchange flows and relations between countries and thus helps researchers, teachers, consultants and journalists with exploring and sharing what globalization is about.<\/p>\n

The session will take a peek at GED VIZ , but leave the stage mainly to three speakers to highlight from different angles how visualization can help us to make sense of globalization: Tariq Khokhar from the World Bank will provide insights about where data comes from in the first place and the challenges data providers have to deal with; Moritz Stefaner will highlight tools he designed for the OECD to explore worldwide well-being; and Maya Ganesh will talk about how we can raise global awareness for issues rooted in local experiences. After these short talks, there will be a discussion about the role of data visualization in exploring, understanding and communicating global issues and how the future of data visualization might look.<\/p>\n

Speakers<\/h4>\n