The European Student Parliament organizes debates around different topics. Smart cities is one of them. What is behind the Smart City concept, how a Smart City can become MyCity, and how a map of this Smart City would look like - those are topics of the expert hearing and the follow-up debate
Future of our city - Smart Cities and Knowledge Maps
1. DANS is an institute of KNAW and NWO
Data Archiving and Networked ServicesData Archiving and Networked Services
Future of our city
Andrea Scharnhorst
June 21, 2014
Expert hearing at the European student parliament
2. Andrea Scharnhorst – “science located”
•Head of Research&Innovation at DANS: Data Archiving and Networked Services
Institute
•Scientific coordinator of the Computational Humanities programme at the eHumanities
group of the Royal Netherlands Academy of Arts and Sciences (KNAW)
20012000 2010
@scharnhorsta
ResearchGate; Mendeley;
Academics.edu; LinkedIn
www.knowescape.org
3. Cities as complex systems
Batty, M. (2005). Cities and complexity: Understanding cities with cellular
automata, agent-based models, and fractals. Cambridge, Mass: MIT Press.
Schweitzer, F. (2003). Brownian agents and active particles: Collective
dynamics in the natural and social sciences. Berlin: Springer.
Pictures reproduced from Frank Schweitzer’s book
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5. Cities and social movement
1895-1993 Source: Wikipedia Dan Linsey
Comprehensive
knowledge
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http://amsterdamsmartcity.com/
7. ANALYZING THE DYNAMICS OFANALYZING THE DYNAMICS OF
INFORMATION AND KNOWLEDGEINFORMATION AND KNOWLEDGE
Browse a collection
or a database
Map size, structure, composition
and evolution of the collection
Locate your search on such an
interactive knowledge map
• Domain overview for students, interdisciplinary
teams, lay experts and funding agencies
• Tools for scholars of history and philosophy of
science and bibliometrics
• Overview of BigData collections (incl. social media)
Given the explosion of information how to navigate
to find what is needed?
8. Informa on Professionals/
Informa on Scien sts
Social Scien sts
Computer Scien sts
Physics/Mathema cs
Digital Humani es
Information professionals
•Collections, Information retrieval
•WG 1 Phenomenology of knowledge spaces
• WG 4 Data curation & navigation
Social scientists
•Simulating user behavior
•WG 2 Theory of knowledge
spaces
•WG 4 Data curation & navigation
Computer scientists
•Semantic web, data models
•WG 1 Phenomenology of Knowledge Spaces
•WG 4 Data curation &navigation
Physicists, mathematicians
Digital humanities scholars
•Collections, interactive design
•WG 3 Visual analytics – knowledge maps
•WG 4 Data curation & navigation
Participating communitiesParticipating communities
• Structure & evolution of
complex knowledge
spaces, big data mining
• WG 2 Theory of
knowledge spaces
• WG 3 Visual analytics –
knowledge maps
Editor's Notes
When I first got the invitation to act as expert for this topic, I hesitated. I’m not an urban planner, architect, infrastructure person – in fact I’m an information scientists and this is my footprint in academia
I came across the topic of a “Smart City” in different contexts.
Cities have always attracted the attention and curiosity of scientists who wanted to know how cities grow and why they grow – this kind of statistical social science forms actually a bridge between different areas in the social sciences, ICT and physics.
Smart Cities is actual about living in a city in the digital age
Let me explain this a bit.
Complex mathematical models can explain how cities grow, why we see segregation of different populations in a city, and so one
But they all need data
Smart cities is about DATA
But it is also about how to use DATA, how to be able to understand DATA and probably increasingly in the future also how many DATA to give.
Don’t be mistaken – the big data dreams build on harvesting your/our personal traces. Like all other technology is can be used and misused.
Sometimes I play with an app, which allows to search visually through wikipedia, search for associations, paths which lead me from one known island to another. When typing in Smart Cities in LearnDiscovery there are many paths to go: to digital city, to creative industries, to the Internet of Things, to collective intelligence, and from there to network analysis – and to complexity; but there is one link MESH cities which leads to synergetics (my early home) and from there to Buckminster Fuller, which I discovered only relative recently, due to a pointer of a colleague of mine Charles van den Heuvel, who was one of the organizers of a conference Analogous Spaces : where architects and information scientists met, 2009 in Ghent. Buckminster Fuller belongs right to this interface: he was an architect, but he also designed a World Game. I have never played this game – still would do this; but I read some of his texts – and it is all about comprehensive knowledge – and education to acquire this. Knowledge as power, if you wish and knowledge needed to be able to be an active part of problem solving – in your capacity of a citizen and independent of your actual profession.
Amsterdamsmartcity is about both: projects with citizen in daily life (54) from health care to wifi, from energy to education – and big data, live stream, smart data analysis – City Dashboard by the Waag Society.
What data we need to orient ourselves in real spaces (urban, rural) and abstract space (the information we need daily, mundane, professional) is also the topic of a so-called COST Action. Knowescape brings together very different communities – and we mainly strive to make maps about collections – BUT we started workshops on Knowledge Maps – which are very open ended what concerns its target map. Sofia and I decided in the preparation of this meeting that it would be cool to run such a workshop with you… instead of having me talking all the time.
By the way, COST Action are great vehicle for ESR = Early stage researcher to visit other labs. Most of the Actions – all – run a Short Term Scientific Mission programmes, many have open calls, all are eager to support the “learning by travelling” for apprentices of academia – I can tell more afterwards.