Crowdsourced Geographic Information in Government

Today marks the publication of the report ‘crowdsourced geographic information in government‘. The report is the result of a collaboration that started in the autumn of last year, when the World Bank Global Facility for Disaster Reduction and Recovery(GFDRR)  requested to carry out a study of the way crowdsourced geographic information is used by governments. The […]

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Third day of INSPIRE 2014 – any space for civil society and citizens?

At the last day of INSPIRE conference, I’ve attended a session about  apps and applications and the final plenary which focused on knowledge based economy and the role of inspire within it. Some notes from the talks including my interpretations and comments. Dabbie Wilson from the Ordnance Survey highlighted the issues that the OS is facing […]

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Crowdsourcing, Citizen Science and INSPIRE

The INSPIRE 2014 conference marks the middle of the implementation process of  the INSPIRE directive (Infrastructure for Spatial Information in the European Community). The directive is aimed at establishing a pan-European Spatial Data Infrastructure (SDI), and that mean lots of blueprints, pipes, machine rooms and protocols for enabling the sharing of geographic information. In GIS jargon,  blueprints translate to […]

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Upscience talk at Oxford’s Martin School

About a month ago, Francois Grey put out a suggestion that we should replace the term ‘bottom-up’  science with upscience  – do read his blog-post for a fuller explanation. I have met Francois in New York in April, when he discussed with me the ideas behind the concept, and why it is worth trying to use it. […]

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The Conservation Volunteers (TCV) volunteering impact report

Thursday marked the launch of The Conservation Volunteers (TCV) report on volunteering impact where they summarised a three year project that explored motivations, changes in pro-environmental behaviour, wellbeing and community resilience. The report is worth a read as it goes beyond the direct impact on the local environment of TCV activities, and demonstrates how involvement in environmental volunteering can […]

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The Conservation Volunteers (TCV) volunteering impact report

Thursday marked the launch of The Conservation Volunteers (TCV) report on volunteering impact where they summarised a three year project that explored motivations, changes in pro-environmental behaviour, wellbeing and community resilience. The report is worth a read as it goes beyond the direct impact on the local environment of TCV activities, and demonstrates how involvement in environmental volunteering can […]

Continue reading »

The Conservation Volunteers (TCV) volunteering impact report

Thursday marked the launch of The Conservation Volunteers (TCV) report on volunteering impact where they summarised a three year project that explored motivations, changes in pro-environmental behaviour, wellbeing and community resilience. The report is worth a read as it goes beyond the direct impact on the local environment of TCV activities, and demonstrates how involvement in environmental volunteering can […]

Continue reading »

Albert Borgmann’s Philosophy of Technology, VGI & Citizen Science

Some ideas take long time to mature into a form that you are finally happy to share them. This is an example for such thing. I got interested in the area of Philosophy of Technology during my PhD studies, and continue to explore it since. During this journey, I found a lot of inspiration and links […]

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Albert Borgmann’s Philosophy of Technology, VGI & Citizen Science

Some ideas take long time to mature into a form that you are finally happy to share them. This is an example for such thing. I got interested in the area of Philosophy of Technology during my PhD studies, and continue to explore it since. During this journey, I found a lot of inspiration and links […]

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Assertions on crowdsourced geographic information & citizen science #3

Following the two previous assertions, namely that: ‘you can be supported by a huge crowd for a very short time, or by few for a long time, but you can’t have a huge crowd all of the time (unless data collection is passive)’ (original post here) And ‘All information sources are heterogeneous, but some are more […]

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Assertions on crowdsourced geographic information & citizen science #2

Following the last post, which focused on an assertion about crowdsourced geographic information and citizen science I continue with another observation. As was noted in the previous post, these can be treated as ‘laws’ as they seem to emerge as common patterns from multiple projects in different areas of activity – from citizen science to crowdsourced […]

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Assertions on crowdsourced geographic information & citizen science #1

Looking across the range of crowdsourced geographic information activities, some regular patterns are emerging and it might be useful to start notice them as a way to think about what is possible or not possible to do in this area. Since I don’t like the concept of ‘laws’ – as in Tobler’s first law of […]

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‘Keeping the spirit alive’ – preservations of participatory GIS values in the Geoweb

During the symposium “The Future of PGIS: Learning from Practice?” which was held at ITC-University of Twente, 26 June 2013, I gave a talk titled ‘Keeping the spirit alive’ – preservations of participatory GIS values in the Geoweb, which explored what was are the important values in participatory GIS and how they translate to the […]

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Gartner’s hype cycle and citizen science

The term ‘Citizen Science’ is clearly gaining more recognition and use. It is now get mentioned in radio and television broadcasts, social media channels as well as conferences and workshops. Some of the clearer signs for the growing attention include discussion of citizen science in policy oriented conferences such as UNESCO’s World Summit on Information Society […]

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New Publication: GIS and Agent-Based models for Humanitarian Assistance

Inputs to the model
 
As the readers of the blog know, we have an interest in GIS, agent-based modeling and crowdsourcing. Now we have a paper that combines all these three elements. Its entitled “GIS and Agent-Based models for Humanitarian Assistance” and is published in Computers, Environment and Urban Systems. 
 
The model itself was written in MASON and uses extensively GeoMASON. Data comes from several different sources (both raster and vector) including OpenStreetMap and LandScan. Below you can read an abstract of the paper and see a movie of one of the scenarios.

“Natural disasters such as earthquakes and tsunamis occur all over the world, altering the physical landscape and often severely disrupting people’s daily lives. Recently researchers’ attention has focused on using crowds of volunteers to help map the damaged infrastructure and devastation caused by natural disasters, such as those in Haiti and Pakistan. This data is extremely useful, as it is allows us to assess damage and thus aid the distribution of relief, but it tells us little about how the people in such areas will react to the devastation. This paper demonstrates a prototype spatially explicit agent-based model, created using crowdsourced geographic information and other sources of publicly available data, which can be used to study the aftermath of a catastrophic event. The specific case modelled here is the Haiti earthquake of January 2010. Crowdsourced data is used to build the initial populations of people affected by the event, to construct their environment, and to set their needs based on the damage to buildings. We explore how people react to the distribution of aid, as well as how rumours relating to aid availability propagate through the population. Such a model could potentially provide a link between socio-cultural information about the people affected and the relevant humanitarian relief organizations.”

Full Reference: 

Crooks, A.T. and Wise, S. (2013), GIS and Agent-Based models for Humanitarian Assistance, Computers, Environment and Urban Systems, 41: 100-111.

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New Publication: GIS and Agent-Based models for Humanitarian Assistance

Inputs to the model
 
As the readers of the blog know, we have an interest in GIS, agent-based modeling and crowdsourcing. Now we have a paper that combines all these three elements. Its entitled “GIS and Agent-Based models for Humanitarian Assistance” and is published in Computers, Environment and Urban Systems. 
 
The model itself was written in MASON and uses extensively GeoMASON. Data comes from several different sources (both raster and vector) including OpenStreetMap and LandScan. Below you can read an abstract of the paper and see a movie of one of the scenarios.

“Natural disasters such as earthquakes and tsunamis occur all over the world, altering the physical landscape and often severely disrupting people’s daily lives. Recently researchers’ attention has focused on using crowds of volunteers to help map the damaged infrastructure and devastation caused by natural disasters, such as those in Haiti and Pakistan. This data is extremely useful, as it is allows us to assess damage and thus aid the distribution of relief, but it tells us little about how the people in such areas will react to the devastation. This paper demonstrates a prototype spatially explicit agent-based model, created using crowdsourced geographic information and other sources of publicly available data, which can be used to study the aftermath of a catastrophic event. The specific case modelled here is the Haiti earthquake of January 2010. Crowdsourced data is used to build the initial populations of people affected by the event, to construct their environment, and to set their needs based on the damage to buildings. We explore how people react to the distribution of aid, as well as how rumours relating to aid availability propagate through the population. Such a model could potentially provide a link between socio-cultural information about the people affected and the relevant humanitarian relief organizations.”

Full Reference: 

Crooks, A.T. and Wise, S. (2013), GIS and Agent-Based models for Humanitarian Assistance, Computers, Environment and Urban Systems, 41: 100-111.

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Usability, SatNavs and Which?

The Consumers’ Association Which? magazine  is probably not the first place to turn to when you look for usability studies. Especially not if you’re interested in computer technology – for that, there are sources such as PC Magazine on the consumer side, and professional magazines such as Interactions from Association for Computing Machinery (ACM) Special Interest Group on Computer-Human […]

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Spatial Data Infrastructures, Crowdsourcing and VGI

The Spatial Data Infrastructure Magazine (SDIMag.com) is a relatively new e-zine dedicated to the development of spatial  data infrastructures around the world. Roger Longhorn, the editor of the magazine, conducted an email interview with me, which is now published. In the interview, we are covering the problematic terminology used to describe a wider range of activities; the […]

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Natural Disasters and Crowdsourcing: Haiti

Natural disasters such as earthquakes and tsunamis occur all over the world, altering the physical landscape and often severely disrupting people’s daily lives. Recently researchers’ attention has focused on using crowds of volunteers to help map the infrastructure and devastation caused by natural disasters, such as those in Haiti and Pakistan. For example, in the movie below shows the response to the earthquake by the OpenStreetMap community within 12 hours of the earthquake. The white flashes indicate edits to the map (often by tracing satellite/aerial photography).
While this data is extremely useful, as it is allows us to assess damage and thus aid the distribution of relief, but it tells us little about how the people in such areas will react to the devastation, the supply of food, or the reconstruction. To address this, we are exploring how agent-based modeling can be used to explore peoples reactions. To do this we have created a prototype spatially explicit agent-based model, created using crowdsourced geographic information and other sources of publicly available data, which can be used to study the aftermath of a catastrophic event. The specific case modeled here is the Haiti earthquake of January 2010. Crowdsourced data is used to build the initial populations of people affected by the event, to construct their environment, and to set their needs based on the damage to buildings. 

The idea behind the model is to explore how people react to the distribution of aid, as well as how rumors propagating through the population and crowding around aid distribution points might lead to food riots and similar social phenomena. Such a model could potentially provide a link between socio-cultural information of the people affected and relevant humanitarian relief organizations.

<p><p>sssss</p></p>

The animation above shows one simulation run where there is the spread of  information and agent movement (red dots) around one center (blue dot). While the chart below shows how over time the density of agents around the food station increases over time.

The idea behind such a model is one can take crowdsourced information and fuse it into an agent-based model and see how people will react to the distribution of food centers. For example, the movie below shows how agents find out about four (hypothetical) different food centers and decide whether or not to go to them in a 6 by 8km area of Port-au-Prince.

Spread of information and agent movement (red dots) in a 6 by 8km area of Port-au-Prince.
More details about this model to come……
Continue reading »

Natural Disasters and Crowdsourcing: Haiti

Natural disasters such as earthquakes and tsunamis occur all over the world, altering the physical landscape and often severely disrupting people’s daily lives. Recently researchers’ attention has focused on using crowds of volunteers to help map the infrastructure and devastation caused by natural disasters, such as those in Haiti and Pakistan. For example, in the movie below shows the response to the earthquake by the OpenStreetMap community within 12 hours of the earthquake. The white flashes indicate edits to the map (often by tracing satellite/aerial photography).
While this data is extremely useful, as it is allows us to assess damage and thus aid the distribution of relief, but it tells us little about how the people in such areas will react to the devastation, the supply of food, or the reconstruction. To address this, we are exploring how agent-based modeling can be used to explore peoples reactions. To do this we have created a prototype spatially explicit agent-based model, created using crowdsourced geographic information and other sources of publicly available data, which can be used to study the aftermath of a catastrophic event. The specific case modeled here is the Haiti earthquake of January 2010. Crowdsourced data is used to build the initial populations of people affected by the event, to construct their environment, and to set their needs based on the damage to buildings. 

The idea behind the model is to explore how people react to the distribution of aid, as well as how rumors propagating through the population and crowding around aid distribution points might lead to food riots and similar social phenomena. Such a model could potentially provide a link between socio-cultural information of the people affected and relevant humanitarian relief organizations.

<p><p>sssss</p></p>

The animation above shows one simulation run where there is the spread of  information and agent movement (red dots) around one center (blue dot). While the chart below shows how over time the density of agents around the food station increases over time.

The idea behind such a model is one can take crowdsourced information and fuse it into an agent-based model and see how people will react to the distribution of food centers. For example, the movie below shows how agents find out about four (hypothetical) different food centers and decide whether or not to go to them in a 6 by 8km area of Port-au-Prince.

Spread of information and agent movement (red dots) in a 6 by 8km area of Port-au-Prince.
More details about this model to come……
Continue reading »

#Earthquake: Twitter as a Distributed Sensor System

Our work on using social media continues to develop and we have recently had a paper accepted in Transactions in GIS, entitled “#Earthquake: Twitter as a Distributed Sensor System“. Below we present our abstract and some of the results.

Social media feeds are rapidly emerging as a novel avenue for the contribution and dissemination of information that is often geographic. Their content often includes references to events occurring at, or affecting specific locations. Within this paper we analyze the spatial and temporal characteristics of the twitter feed activity responding to a 5.8 magnitude earthquake which occurred on the East Coast of the United States (US) on August 23, 2011. We argue that these feeds represent a hybrid form of a sensor system that allows for the identification and localization of the impact area of the event. By contrasting this to comparable content collected through the dedicated crowdsourcing ‘Did You Feel It?’ (DYFI) website of the US Geological Survey we assess the potential of the use of harvested social media content for event monitoring. The experiments support the notion that people act as sensors to give us comparable results in a timely manner, and can complement other sources of data to enhance our situational awareness and improve our understanding and response to such events.

The movie below show geolocated tweets with references to the earthquake through keyword (earthquake or earth and quake) and hashtag search (#earthquake or #quake) for the first hour after the earthquake.

The following images give a glimpse at some of our analysis.

Response pattern as function of distance from epicenter for the first 400 seconds after the earthquake. At the top we see a plot of (reaction time, distance) of all tweets during that period. At the bottom we show the histogram of the number of tweets as a function of distance.
Locations of the 40 tweets in the shaded area of the figure above overlaid over the USGS CDI scale map. Tweet locations are marked as green circles. Color-coding in the graph is ranging from red (high perceived intensity) to yellow (lower perceived intensity). The dashed line shows a distance of approximately 950 km (8.5 degrees of angular distance) from the epicenter.

The movie below gives you an idea of some of the tweet content:

Full reference to this paper is:

Crooks, A. T.,  Croitoru, A.,  Stefanidis, A. and Radzikowski, J. (acepted) “#Earthquake: Twitter as a Distributed Sensor System” Transactions in GIS.

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#Earthquake: Twitter as a Distributed Sensor System

Our work on using social media continues to develop and we have recently had a paper accepted in Transactions in GIS, entitled “#Earthquake: Twitter as a Distributed Sensor System“. Below we present our abstract and some of the results.

Social media feeds are rapidly emerging as a novel avenue for the contribution and dissemination of information that is often geographic. Their content often includes references to events occurring at, or affecting specific locations. Within this paper we analyze the spatial and temporal characteristics of the twitter feed activity responding to a 5.8 magnitude earthquake which occurred on the East Coast of the United States (US) on August 23, 2011. We argue that these feeds represent a hybrid form of a sensor system that allows for the identification and localization of the impact area of the event. By contrasting this to comparable content collected through the dedicated crowdsourcing ‘Did You Feel It?’ (DYFI) website of the US Geological Survey we assess the potential of the use of harvested social media content for event monitoring. The experiments support the notion that people act as sensors to give us comparable results in a timely manner, and can complement other sources of data to enhance our situational awareness and improve our understanding and response to such events.

The movie below show geolocated tweets with references to the earthquake through keyword (earthquake or earth and quake) and hashtag search (#earthquake or #quake) for the first hour after the earthquake.

The following images give a glimpse at some of our analysis.

Response pattern as function of distance from epicenter for the first 400 seconds after the earthquake. At the top we see a plot of (reaction time, distance) of all tweets during that period. At the bottom we show the histogram of the number of tweets as a function of distance.
Locations of the 40 tweets in the shaded area of the figure above overlaid over the USGS CDI scale map. Tweet locations are marked as green circles. Color-coding in the graph is ranging from red (high perceived intensity) to yellow (lower perceived intensity). The dashed line shows a distance of approximately 950 km (8.5 degrees of angular distance) from the epicenter.

The movie below gives you an idea of some of the tweet content:

Full reference to this paper is:

Crooks, A. T.,  Croitoru, A.,  Stefanidis, A. and Radzikowski, J. (acepted) “#Earthquake: Twitter as a Distributed Sensor System” Transactions in GIS.

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‘Nobody wants to do council estates’ – digital divide, spatial justice and outliers – AAG 2012

At the 2012 Annual Meeting of the Association of American Geographers, I presented during the session ‘Information Geographies: Online Power, Representation and Voice’, which was organised by Mark Graham (Oxford Internet Institute) and Matthew Zook (University of Kentucky). For an early morning session on a Saturday, the session was well attended – and the papers […]

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Reflections on Eye on Earth summit (2): the 3 eras of public access to environmental information

As noted  in the previous post, which focused on the linkage between GIS and Environmental Information Systems,  the Eye on Earth Summit took place in Abu Dhabi on the 12 to 15 December 2011, and focused on ‘the crucial importance of environmental and societal information and networking to decision-making’.  Throughout the summit, two aspects of […]

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Harvesting ambient geospatial information from social media feeds

A paper I  recently co-authored with Anthony Stefanidis and Jacek Radzikowski from George Mason University entitled “Harvesting ambient geospatial information from social media feeds” is now available in  GeoJournal.   The abstract …

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Harvesting ambient geospatial information from social media feeds

A paper I  recently co-authored with Anthony Stefanidis and Jacek Radzikowski from George Mason University entitled “Harvesting ambient geospatial information from social media feeds” is now available in  GeoJournal.   The abstract …

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Levels of participation in citizen science and scientific knowledge production

The previous post focused on citizen science as participatory science. This post is discussing the meaning of this differentiation. It is the final part of the chapter that will appear next year in the book: Sui, D.Z., Elwood, S. and M.F. Goodchild (eds.), 2012. Volunteered Geographic Information, Public Participation, and Crowdsourced Production of Geographic Knowledge. […]

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Classification of Citizen Science activities

As part of the Volunteered Geographic Information (VGI) workshop that was held in Seattle in April 2011, Daniel Sui, Sarah Elwood and Mike Goodchild announced that they will be editing a volume dedicated to the topic, planned to be published at the beginning of next year. My contribution to this volume focuses on citizen science, […]

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Observing from afar or joining the action: OSM and GIScience research

At the State of the Map (EU) 2011 conference that was held in Vienna from 15-17 July, I gave a keynote talk on the relationships between the OpenStreetMap  (OSM) community and the GIScience research community. Of course, the relationships are especially important for those researchers who are working on volunteered Geographic Information (VGI), due to […]

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OpenStreetMap and Ordnance Survey Meridian 2 comparison – 2008 – 2011

In March 2008, I started comparing OpenStreetMap in England to the Ordnance Survey Meridian 2, as a way to evaluate the completeness of OpenStreetMap coverage. The rational behind the comparison is that Meridian 2 represents a generalised geographic dataset that is widely use in national scale spatial analysis. At the time that the study started, […]

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GISRUK 2011 talk – Participatory GIS, Volunteered Geographic Information and Citizen Science

GIS Research UK (GISRUK) is a long running conference series, and the 2011 instalment was hosted by the University of Portsmouth at the end of April. During the conference, I was asked to give a keynote talk about Participatory GIS. I decided to cover the background of Participatory GIS in the mid-1990s, and the transition […]

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