Citizen Science 2019: Citizen Science: Creating Authentic Learning Opportunities for Students

The second day opened with an introduction to Kenan Fellows https://kenanfellows.org/ which is a programme to link teachers and provide STEM experience, and therefore they integrate citizen science in schools. Following this, Rachael Polmanteer, who is marine biologist turned 8th-grade science teacher, gave a keynote. Rachael is from Bath, New York (state) and she grows … Continue reading Citizen Science 2019: Citizen Science: Creating Authentic Learning Opportunities for Students

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Citizen Science & Scientific Crowdsourcing – week 2 – Google Local Guides

The first week of the “Introduction to Citizen Science and Scientific Crowdsourcing” course was dedicated to an introduction to the field of citizen science using the history, examples and typologies to demonstrate the breadth of the field. The second week was dedicated to the second half of the course name – crowdsourcing in general, and its … Continue reading Citizen Science & Scientific Crowdsourcing – week 2 – Google Local Guides

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Chapter in ‘Understanding Spatial Media’ on VGI & Citizen Science

The book ‘Understanding Spatial Media‘ came out earlier this year. The project is the result of joint effort of the editors Rob Kitchin (NUI Maynooth, Ireland), Tracey P. Lauriault (Carleton University, Canada), and Matthew W. Wilson (University of Kentucky, USA). The book is filling the need to review and explain what happened in the part 20 years, with the increase use … Continue reading Chapter in ‘Understanding Spatial Media’ on VGI & Citizen Science

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Authoritative and VGI in a Developing Country: A Comparative Case Study of Road Datasets in Nairobi

The motivation behind the paper was that while there are numerous studies comparing VGI to authoritative data in the developed world, there are very few that do so in developing world. In order to address this issue in the paper we compare the quality of authoritative road data (i.e. from the Regional Center for Mapping of Resources for Development – RCMRD) and non-authoritative crowdsourced road data (i.e. from OpenStreetMap (OSM) and Google’s Map Maker) in conjunction with population data in and around Nairobi, Kenya.

Results from our analysis show variability in coverage between all these datasets. RCMRD provided the most complete, albeit less current, coverage when taking into account the entire study area, while OSM and Map Maker showed a degradation of coverage as one moves from central Nairobi towards more rural areas. Further information including the abstract to our paper, some figures and full reference is given below.

Abstract:

With volunteered geographic information (VGI) platforms such as OpenStreetMap (OSM) becoming increasingly popular, we are faced with the challenge of assessing the quality of their content, in order to better understand its place relative to the authoritative content of more traditional sources. Until now, studies have focused primarily on developed countries, showing that VGI content can match or even surpass the quality of authoritative sources, with very few studies in developing countries. In this paper we compare the quality of authoritative (data from the Regional Center for Mapping of Resources for Development – RCMRD) and non-authoritative (data from OSM and Google’s Map Maker) road data in conjunction with population data in and around Nairobi, Kenya. Results show variability in coverage between all these datasets. RCMRD provided the most complete, albeit less current, coverage when taking into account the entire study area, while OSM and Map Maker showed a degradation of coverage as one moves from central Nairobi towards rural areas. Furthermore, OSM had higher content density in large slums, surpassing the authoritative datasets at these locations, while Map Maker showed better coverage in rural housing areas. These results suggest a greater need for a more inclusive approach using VGI to supplement gaps in authoritative data in developing nations.

Keywords: Volunteered Geographic Information; Crowdsourcing; Road Networks; Population Data; Kenya  
Road Coverage per km2
Pairwise difference in road coverage. Clockwise from top left: i) RCMRD 2011 versus Map Maker 2014; ii) RCMRD 2011 versus OSM 2011; iii) RCMRD 2011 versus OSM 2014; iv) OSM 2014 versus Map Maker 2014 (Red cells: first layer has higher coverage; Green cells: second layer has higher coverage).

Full Reference:

Mahabir, R., Stefanidis, A., Croitoru, A., Crooks, A.T. and Agouris, P. (2017), “Authoritative and Volunteered Geographical Information in a Developing Country: A Comparative Case Study of Road Datasets in Nairobi, Kenya”, ISPRS International Journal of Geo-Information, 6(1): 24, doi:10.3390/ijgi6010024.

As always any thoughts or comments about this work are welcome.

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Authoritative and VGI in a Developing Country: A Comparative Case Study of Road Datasets in Nairobi

The motivation behind the paper was that while there are numerous studies comparing VGI to authoritative data in the developed world, there are very few that do so in developing world. In order to address this issue in the paper we compare the quality of authoritative road data (i.e. from the Regional Center for Mapping of Resources for Development – RCMRD) and non-authoritative crowdsourced road data (i.e. from OpenStreetMap (OSM) and Google’s Map Maker) in conjunction with population data in and around Nairobi, Kenya.

Results from our analysis show variability in coverage between all these datasets. RCMRD provided the most complete, albeit less current, coverage when taking into account the entire study area, while OSM and Map Maker showed a degradation of coverage as one moves from central Nairobi towards more rural areas. Further information including the abstract to our paper, some figures and full reference is given below.

Abstract:

With volunteered geographic information (VGI) platforms such as OpenStreetMap (OSM) becoming increasingly popular, we are faced with the challenge of assessing the quality of their content, in order to better understand its place relative to the authoritative content of more traditional sources. Until now, studies have focused primarily on developed countries, showing that VGI content can match or even surpass the quality of authoritative sources, with very few studies in developing countries. In this paper we compare the quality of authoritative (data from the Regional Center for Mapping of Resources for Development – RCMRD) and non-authoritative (data from OSM and Google’s Map Maker) road data in conjunction with population data in and around Nairobi, Kenya. Results show variability in coverage between all these datasets. RCMRD provided the most complete, albeit less current, coverage when taking into account the entire study area, while OSM and Map Maker showed a degradation of coverage as one moves from central Nairobi towards rural areas. Furthermore, OSM had higher content density in large slums, surpassing the authoritative datasets at these locations, while Map Maker showed better coverage in rural housing areas. These results suggest a greater need for a more inclusive approach using VGI to supplement gaps in authoritative data in developing nations.

Keywords: Volunteered Geographic Information; Crowdsourcing; Road Networks; Population Data; Kenya  
Road Coverage per km2
Pairwise difference in road coverage. Clockwise from top left: i) RCMRD 2011 versus Map Maker 2014; ii) RCMRD 2011 versus OSM 2011; iii) RCMRD 2011 versus OSM 2014; iv) OSM 2014 versus Map Maker 2014 (Red cells: first layer has higher coverage; Green cells: second layer has higher coverage).

Full Reference:

Mahabir, R., Stefanidis, A., Croitoru, A., Crooks, A.T. and Agouris, P. (2017), “Authoritative and Volunteered Geographical Information in a Developing Country: A Comparative Case Study of Road Datasets in Nairobi, Kenya”, ISPRS International Journal of Geo-Information, 6(1): 24, doi:10.3390/ijgi6010024.

As always any thoughts or comments about this work are welcome.

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A Semester with Urban Analytics

This past semester I gave a new class at GMU entitled “Urban Analytics”. In a nutshell the class was about introducing students to a broad interdisciplinary field that focuses on the use of data to study cities. More specifcally the emphasis of the cla…

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A Semester with Urban Analytics

This past semester I gave a new class at GMU entitled “Urban Analytics”. In a nutshell the class was about introducing students to a broad interdisciplinary field that focuses on the use of data to study cities. More specifcally the emphasis of the cla…

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Spatial Conversation – #VGIday #COSTEnergic

The COST Energic network (see VGIBox.eu ) is running a 2 day geolocated twitter chat, titled ‘Volunteered Geographic Information Day’ so the hashtag is #VGIDay. The conversation will take place on 14th and 15th May 2015, and we are universalists – join from anywhere in the world! Joining is easy – and require 3 steps: Follow the … Continue reading Spatial Conversation – #VGIday #COSTEnergic

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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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Trackernet: The Victoria Line

I’ve been meaning to look at TfL’s Trackernet API for a while now. It works through a REST based web service which gives access to all the London Underground running boards on a line by line basis. You issue an http request of the form: http://cloud.tfl.gov.uk/TrackerNet/PredictionSummary/V and the result is an XML file containing train information for […]

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A Week in the Life of a Tile Server

Recently, BBC Look East have been running a “Broadband Speed Survey”, asking people to use an online tester to check their broadband speed, and then enter the value, along with their postcode, into SurveyMapper. This generated 16,311 responses to the survey, but for each response people get to view the map containing the latest data, […]

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Election 2010: Where Were All the Votes?

Using the General Election 2010 results spreadsheet from the Guardian Data Blog, we’ve produced three MapTube maps showing the distribution of votes for the three main parties:    The maps can be viewed on MapTube at the following link: http://www.maptube.org/election/map.aspx?s=DGxUpxGSnLKhUzLIOMHBwKeUwKZUyEDAwcCnksCjlMhBwMHAp5LAoTbd Use the red slider buttons to fade the distributions for the three parties up and down. […]

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From Tile Pyramids to Population Pyramids

It’s actually a stacked bar chart rather than a traditional population pyramid, but the image below shows male/female population by age for all the output areas in England. The red thematic overlay is total population for every OA, which can be clicked to get the age group breakdown shown in the popup window. This map […]

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