applied gis - monash university...bello, i.e. & ojigi, l.m. (2013) – collaborative web mapping...

Applied GIS a free, international, refereed e-journal

(ISSN: 1832-5505)

URL:

http://www.appliedgis.net

MANAGING EDITOR:

Ray Wyatt – [email protected]

Volume 9, Number 2

December, 2013

CONTENTS:

All papers published during 2013 are part of Volume 9.

Each paper constitutes one Number.

Hence this paper should be cited as:

Bello, I.E. & Ojigi, L.M. (2013) – Collaborative web mapping and volunteered geographic information: a study in Nigeria, Applied GIS, 9(2), 1-17

http://www.appliedgis.net/

mailto:[email protected]


1

Collaborative web mapping and volunteered geographic information:

a study in Nigeria

Innocent E. Bello

Lazarus M. Ojigi

Mission Planning, Information Technology & Data Management Department,

National Space Research and Development Agency (NASRDA), PMB 437 Garki 2, Abuja,

Nigeria

[email protected], [email protected] [email protected]

Abstract - This paper evaluates developments in mapping - from traditional, desktop cartography through to Collaborative Web Mapping (CWM), and it uses an experimental example from a developing country, Nigeria. We examine the status and limitations of CWM as a viable tool that freely contributes towards using globally assessed and free Web Mapping Platforms (WMPs) such as Google Maps, Google Earth, OpenStreetMap, Bing Maps and Yahoo! Maps. Here we use Google Map Maker Web 2.0 to conduct an experimental mapping analysis using 50 volunteered staff drawn from different departments of the National Space Research and Development Agency (NASRDA) and the Centre for Satellite Technology Development (CSTD) in Abuja, Nigeria. We find that Geographic Information (GI) experts are faster at data integration, while the reverse is the case for non-GI experts due to limited knowledge of geo-spatial data management. We then describe how Focus Group Discussions (FGDs) revealed that all participants are willing to optimistically contribute towards a global map by using a free web mapping medium. Finally, we explain that limitations to the advancement of integrating Volunteered Geographic Information (VGI) in most developing countries like Nigeria include poor knowledge of geo-spatial data and analytical methods, unstable electric power supply, slow but high-cost Internet facilities, inadequate computer systems and lack of personal volunteerism.

Keywords - Cartography, Collaborative Web Mapping, Mapping, Volunteered Geographic Information, Web 2.0.

1. Introduction

The limitations of traditional cartography in geographic analysis have long been known. If manually drawn maps are to be adjusted for reliable and effective communication of updated content, the services of a highly skilled professional is usually required (Openshaw, 1989). This partly explains why, in the interests of greater clarity, a number of cartographic conventions have been developed, including the rendering of water by a blue colour, forests





2

by dark green and built-up areas by red, grey or pink (Bertin, 1983; Olomo, 1997). Such conventions have been strengthened by the fact that in the 19th century all topographic maps were produced with the objective of infantry warfare in mind (Kraak & Ormeling, 2010). Nevertheless, it is a known fact that, hitherto, classical maps were not very accurate due to errors in measurement and presentation (Onokerhoraye, 1994), and early Geographic Information System (GIS) technology was not well advanced because most geo-spatial datasets existed in different formats.

Yet more recently, technology has enhanced the capture of such geospatial data as points, lines and polygons for effective representation and communication to users at different measurement scales. Moreover, there has been an increasing awareness of the importance of Web 2.0 techniques for geospatial data capture and presentation - a means of indexing and accessing information over the Internet (Murugesan, 2007).

This prompted Goodchild (2007) to observe that whereas the early web was primarily one-directional (Web 1.0), allowing a large number of users to view the contents of a comparatively small number of sites, Web 2.0 capacity is bi-directional and interactive. Moreover, cartography and GIS have continually changed from static output (hard copy) to mobile real time usage as a result of the proliferations of devices such as iPhones, HTC, iPads, BlackBerries and Androids. State-of-the-art phones in particular, facilitate geo-tagging (mashups such as tagged photos with GPS location details) and rapid Volunteered Geographic Information (VGI) (Haklay, 2010; Goodchild, 2009; Haklay et al., 2008).

Note that the introduction of on-screen maps and their corresponding databases resulted in a split between the functional use of maps as a medium for both storage and presentation of geoinformation (Kraak & Ormeling, 2010). Moreover, on-screen mapping technologies brought the availability of database technology and computer graphics techniques that resulted in new and alternative presentation options such as 3D and animated and multi-media maps that can even be web-based.

In short, there has been a huge shift in geospatial mapping possibilities due to advances in data-acquisition equipment, availability of aerial photographs and satellite images, advancement in Information and Communication Technology (ICT), electronic surveying and digital mapping practices.

1.1 The concept of Community or Collaborative Web Mapping (CWM)

Due to an increasing demand for up-to-date geospatial data, there have been a growing number of efforts to outsource some tasks in order to ensure quality when meeting the requests of users. Indeed, Cho et al., (2012) say that

…crowd sourcing is a process that involves outsourcing tasks to a distributed group of people and this process can occur both online and offline.

Volunteered Geographic Information (VGI) is an example of the online approach, and we have explained the concept of collaborative or community web mapping (crowd sourcing VGI, or online mapping by volunteers) in Figure 1 (Chuang & Huang, 2005).


3

Figure 1 - Conceptualization of online community mapping (source: Chuang & Huang, 2005)

Today, the application of this concept is relatively unproblematic within developed countries because of developments in geoinformation (GI) science and systems occasioned by technology, unprecedented daily itineraries, and improvements in navigation systems (such as in-car), constant electric power supply and high-speed internet services. But the reverse seems to be the case within most developing countries of Africa, Nigeria in particular.

Haklay et al., (2008) observed that since 1993 the use of the Internet to deliver geoinformation and maps has steadily grown, and the number of visitors to public Web mapping sites provides an indication of this change. The Wall Street Journal (2007) reported that, in mid-2005, the market leader in the UK (MultiMap) attracted 7.3 million visitors and, in the USA, MapQuest was used by 47 million visitors. By the end of 2007, Google Maps was used by 71.5 million and Google Earth by 22.7 million (Wall street Journal, 2007). Moreover, by mid-2007 there were over 50,000 new websites based on Google Maps (Tran, 2007; Haklay, et al., 2008).

Whereas in the previous era of internet mapping the number of mapping websites was significantly smaller due to technical and financial barriers - as currently experienced in developing countries like Nigeria where no globally-accessed, Web mapping sites have been developed or effectively utilized. Ways of duplicating this in Nigeria have yet to be examined.

These changes in geodata management, as well as developments in desktop cartography and web GIS/CWM, can be described as diffusion of an innovation among a people at different time period, and the degree to which people adopt such innovation can be explained with reference to this concept. According to Rogers (1995), diffusion is described as

… an idea, practice, or object that is perceived to be new by an individual or other unit of adoption, while innovation communication is a process in which participants create and share information with one another to reach a mutual understanding.

In other words, the diffusion of innovations is a theory that seeks to explain how, why, and at what rate new ideas and technology, such as crowd sourcing of VGI, spread through

http://en.wikipedia.org/wiki/Idea

http://en.wikipedia.org/wiki/Technology


4

cultures. The theory predicts that media, as well as interpersonal contacts, will increasingly provide information and so influence people’s opinions and judgments.

Rogers (1995) further argued that diffusion has four aspects:

1. invention,

2. diffusion (or communication) through the social system,

3. time, and

4. consequences.

Based on this, five adopter categories have been identified, and they follow a standard deviation curve (Figure 2):

1. few innovators adopt the innovation in the beginning (2.5%),

2. early adopters make up 13.5% a short time later,

3. the early majority 34%,

4. the late majority 34% and, after some time,

5. the laggards 16%.

Figure 2 - Innovation adoption phases (source: Rogers, 1995)

Consequently, innovation diffusion research has attempted to explain the variables that influence how and why users adopt a new information medium such as the Internet for CWM and crowd source mapping (VGI). This theory shows that not many people will adopt the new CWM or VGI idea, especially in Nigeria, and given more time and space as enjoyed in developed countries, there is a possibility of eventually having a critical mass of adopters.

1.2 Overview of CWM, VGI and Web 2.0 applications

Volunteered Geographic Information (VGI) refers to geospatial data that are voluntarily created by citizens who are untrained in the discipline of geography, cartography, or related fields (Goodchild, 2007). Other terms used interchangeably for VGI, among others, are Citizen Sensor or Crowd Sourcing (Goodchild, 2007), Collaborative (Web) Mapping (Lemmens, 2012), Online Community Mapping (Chuang & Huang, 2005), Neogeography (Turner, 2006 & Goodchild, 2009) and Web 2.0 (Turner, 2006; Craglia et al., 2008; Graham, 2010; Haklay, 2010).

In VGI, therefore, the factor of self-will and volunteerism is the driving force behind the crowd-sourced information as there is no compulsion but self-motivation. VGI content (Mashups) is, therefore, the combination of pre-existing materials or concepts to create synthesized content or ideas by using the web/internet platform. In terms of applications, advancement in internet technologies over the past decade, along with increased access to broadband Internet have also altered the practices of environmental planning and design,

http://en.wikipedia.org/wiki/Culture


5

creating opportunities for incorporating online participation tools and techniques into the design process (Sipes, 2002; Seeger, 2008).

While Web 1.0 refers to sites that are used to simply display information or for commercial purposes, Web 2.0 refers to applications or websites that facilitate interactive information sharing and user-generated content (Wigand et al., 2008). In other words, the new Web 2.0 is a bi-directional collaboration in which users are able to interact with, and provide information to central sites and to see the information collated.

Within the framework of Web 2.0 collaborative mapping, the most striking examples of a geographical applications are OpenStreetMap project (Haklay, 2010), Wikimapia, Google Map and Bing Maps (Goodchild, 2009). In all of these, the enabling mapping technology is orchestrated by internet or Web Map Services (WMS) and the ability to create, display and share information globally is made possible. As remarked by Haklay et al., (2008), the technologies of cooperation and WMS, increases in bandwidth and the growth of connectivity options have increased the number of people with access to the internet and ushered in a new era of digital collaboration.

Technologies for collaboration can be assigned to several categories (Haklay et al., 2008) such as:

1. self-organising mesh networks - such as peer-to-peer file or multi-media sharing

2. community computing grids - which involve breaking up computing tasks among several voluntary producers and spreading them over many computers, thereby making it possible to rapidly complete computational tasks

3. peer product networks - which involve volunteers working together without any monetary reward

4. social mobile computing - which involves the call to gather using short message services (SMS) in order to solve a particular task that, most often, requires urgent attention such as the hurricane Katrina, the 2012 River Niger flood in Lokoja, Nigeria and the Haiti earthquake saga

5. group forming networks - which supports social interests, as it allows sub-groups of collectors such as eBay to interact

6. social software - also referred to as Web 2.0 social websites like Facebook, Skype, Flickr and Twitter, which facilitate the sharing of social data and information depending upon the interests of group members. Although these sites have been seen as security risks, its positive applications have far outweighed the negative, yet usage should still take place with the utmost care

7. social accounting tools – offering methods of establishing trust between users and,

8. knowledge collective - which allows users or contributors to set the rules, and structure of shared, common resources and opinions, such as the Wikipedia web blog.

1.3 The need for CWM and crowd sourcing VGI in Nigeria and Africa

Estes and Mooneyham (1994) argued that:

… it is easy to believe that the world is well mapped. Most of the countries having national mapping agencies that produce an up-to-date cartographic representation of their surface, and remote sensing satellites provide regularly updated images. But in reality world mapping or cartography has been in decline for several decades. The U.S Geological Survey no longer attempts to update its map on a regular basis, and many developing countries no longer sustain national mapping enterprise,


6

and the decline of mapping has many consequences (Goodchild et al., 2007). For example, governments are no longer willing to pay the increasing costs of mapping, and they even look to maps as sources of income. For instance, Nigeria, with a population of 162,470,737 inhabitants (World Bank, 2011) occupying a total area of about 923,864km2, has only its major cities and state capitals fairly mapped and served with internet connectivity, social infrastructure and basic amenities.

Moreover, where these facilities are available, only limited literates can actually operate and utilize the available communication gadgets, such as smart phones and computers, and e-mail and social network sites like Facebook, Twitter and Skype seem to take the lead. Only a few geoinformation savvy individuals have the potential to actually use crowd-sourced VGI and Web 2.0 Web Map projects, such as Google Map / Google Earth (Figure 3), and the reasons for this need to be examined.

Figure 3 - Google Earth image showing some VGI mashups in Nigeria and part of Cameroon

On a more specific note, there is an acute problem with geoinformation in Nigeria because most maps available today were produced in the 1960s and 1970s. These are still largely in analogue (hard copy, paper map) format; which gives room for duplication of efforts and waste of time and resources when reproducing already created datasets instead of producing once and for many uses.

This has led to a clamour for National Geospatial Data Infrastructure (NGDI) within most government circles (NASRDA, 2003; Man, 2007; GSDI, 2009; ITC, 2010) and it is now obvious that unless we have the key fundamental map layers that show the locations of existing natural and man-made features there may not be a virile foundation for the country’s development. Therefore, CWM is the most viable and cost-effective approach towards generating geospatial data and information for indexing and accessing relevant map products. Moreover, to effectively create representative, geospatial data and map contents across the continent, other African countries require this approach also.


7

1.3 Objectives

The objectives of this study were to:

1. carry out an overview of CWM and Web 2.0 and its benefits 2. make use of GI experts and non-experts for primary, map data-sourcing evaluation 3. conduct Focus Group Discussions (FGDs) and a hands-on practical on VGI

generation using the Google Map Maker platform 4. implement a VGI pilot programme for Nigeria, using Google Map Maker Web 2.0

Application Mapping Interface.

2. Materials and methods

2.1 Primary and secondary data sourcing

Collaborative mapping (Figure 4) and crowd sourcing methodologies were both adopted and they both rely upon contributions from a large and disparate group of individuals. They need web applications that allow people to upload geoinformation easily and which allow many others to view and react to such information - they are often considered to be part of Web 2.0 (Lemmens, 2012). In this study, both primary and secondary information on CWM were utilized.

Our primary source of data was mainly Focus Group Discussions (FGDs) plus hands-on, practical VGI generation using the Google Map Maker platform. The FGDs and their rapid assessment were conducted under the following hypothetical assumptions

1. anybody with an interest can make a map, regardless of whether or not training has been received in the field of surveying, geography, cartography or computer science

2. contributed information can be shared and utilized in order to meet basic and immediate needs for map and other ancillary information.

Secondary sources of information included Internet pages, books, journals, lecture notes and suggestions received while carrying out the pilot programme.

Figure 4 - CWM participants at the Advanced Communication Laboratory (source: authors’ fieldwork)


8

2.2 Implementation of the CWM/VGI pilot programme

The Google Map Maker Web 2.0 Application Mapping Interface (AMI) was utilized. It is an example of spatially-enabled web technology that allows for a low cost and fast dissemination of specific GI onto base maps, to a smaller dedicated audience, or to the public at large (Lemmens, 2012).

To examine the status, benefits and limitations of generating VGI in a developing economy, a case study evaluation was carried out using volunteers who were randomly selected from staff of NASRDA and CSTD centre. NASRDA is a government geoinformation, satellite imagery and Internet bandwidth provider with the mandate of implementing the National Space Policy (NSP) for Nigeria (NASRDA, 2003, www.nasrda.gov.ng).

The integration of the CSTD in the pilot programme was aimed at balancing the disparity in mapping skills required for crowd sourcing VGI. A total of fifty (50) personnel were gathered to crowd-source VGI under the conviction that local people know, and can map, their environment better. Table 1 shows the distribution of participants and their respective GI capabilities.

S/N Departments/ Unit/Centres

Number of Volunteers

Specialization/ Core Competence

Remarks

1 Administration & Finance (A&F)

6 Office and finance administration

Non GI Experts

2 Mission Planning, Information Technology and Data Management (MP,IT&DM)

5 Satellite telemetry, data acquisition, ingestion and archiving planning, Information technology and geospatial data management

GI Experts

3 Strategic Space Applications (SSA)

6 Satellite data thematic applications and Mapping

GI Experts

4 Engineering and Space Systems (ESS)

7 Satellite and space engineering

non GI Experts

5 GeoApps Plus Ltd. 9 Satellite data marketing, training sourcing and general consultancy

non GI Experts

6 CSTD 6 Satellite technology development, fabrication and testing.

non GI Experts

7 PPR 5 Planning and execution of agency’s internal and external events and activities

non GI Experts

8 Procurement 3 Bid preparation, material procurement, due process handling and project supervisions

non GI Experts

9 International Cooperation (IC)

1 International cooperation and legal matters

non GI Experts

10 Media 2 Management of corporate image and Publicity of NASRDA

non GI Experts

Total → 50 22% (GIE) : 78% (non GIE) 11 : 39

Table 1 - VGI pilot programme participants – “GIE” = GI experts (source: authors’ NASRDA CWM Pilot Programme, 2012)

http://www.nasrda.gov.ng/


9

From those shown in Table 1, ten (10) groups, each made up of five (5) members, were formed for the FGDs and VGI evaluation. To eliminate bias towards GI experts, no department was represented more than once in each group, and groups came together to make a general observation for each of the relevant sub-sections below.

2.3 Mapping instructions and specifications for data collection and analysis

Before the exercise, each participant was asked to get Google e-mail identification (Gmail ID) for those who had none. The web mapping interface for Google Map Maker (Figure 5), OpenStreetMap (Figure 7 below) and Bing Maps (Figure 8 below) were displayed and examined for data content comparison. Participants were then briefly introduced to the functionalities and possible layers available using places of interest known to them, like markets and schools. Using the Google Map Maker web mapping site (Figure 5), and displaying the background satellite images, participants zoomed into and mapped (digitized) an area/feature of interest. Such mapping was completed using the point, line and polygon mapping tools.

Figure 5 - The Google Map Maker Web Mapping (tools) platform showing some mapped areas within and near Ekiosa Market (point, line and polygon features) in Benin City, Nigeria

After mapping, participants came together in small groups of 5 members each to discuss the rational, ease and limitations of contributing VGI. Findings from the CWM exercise and from the FGDs were centred around the three questions:

1. Why are you interested in CWM?

2. Problems encountered or limitations during mapping?

3. Recommendations?


10

3. Results

In this study, 11 (22%) of the participants were GI experts while the remaining 39 (78%) were non-GI experts (Table 1). Out of all 50 participants, only 31 (62%) completed the exercise (i.e., 22 GI and 9 non-GI experts respectively). The implication of this is that the GI experts found it easier to identify features on the satellite image and, consequently, attempted to map them accordingly as point, line or polygon features using the predefined mapping tools in the web portal. Some results, showing identified and mapped areas, are shown in Figure 6.

Figure 6 - Sample maps showing VGI contributed by participants. Published maps are above and image maps are below. The bottom right map has locations awaiting moderator approval

Figure 7 shows some identified locations in the Abuja Central Area of Nigeria (in red and green), from the OpenStreetMap GUI, by a GI expert. Figure 8 shows a general extent of Nigeria and some neighbouring countries which the non-GI experts could have possibly identified. But when they zoomed in they could not interpret the various data layers like their GI expert counterparts could.


11

Figure 7 – The OpenStreetMap GUI showing some identified part of Abuja CBD, Nigeria

Figure 8 – The Bing Maps GUI showing Nigeria and neighbouring countries

3.2 Functional status of VGI generation based on selected web mapping platforms

Examination of the selected web map platforms by the participants reveals, for example, that using Google Map Maker, about 188 countries of the world were mapped, though in different levels of completion. Also, visual exploration of the web contents in the different web map platforms (Figures 5, 7 and 8) reveals that, although the Google Map Maker enables CWM contributors to voluntarily add and share places of interest such as government offices, schools, markets and shopping malls, most African countries have lesser details due to limited entries from volunteers. This platform also provides an enabling environment for mass editing (quality checking) and updating details of previously mapped phenomena.


12

From the Yahoo! Maps CWM interface, Figure 9 shows a sample result of a network analysis, carried out during the experimental project, of an area in Abuja. From location A to B, participants concluded that the contributed VGI could be beneficial in many ways, especially in transportation planning and route analysis. However, as observed during the FGDs, most government GI or mapping organizations in Nigeria fear irrelevance and job loses occasioned by increasing the number of crowd-sourced VGI (mashups). Synergy among these organizations is a possible solution to this problem.

Figure 9 - Web 2.0 interface of Yahoo! Maps showing some streets and a network analysis of two locations, plus driving directions in the central area of Abuja, Nigeria. Notice that only major roads are currently mapped

A comparative evaluation of the street-level data layers of some locations in Nigeria, such as Abuja (Figure 9), and those from developed countries like Hengelo in the Netherlands (Figure 10) respectively, revealed that almost all nooks and crannies of the developed countries have been mapped - even up to 3D levels in some, whereas those of the developing countries, like Nigeria, show only a generalized overview of roads and a few isolated towns and place-names. Moreover, some of the contributed vector data are inaccurate in data capture while some have attribute error, such as misspelt or misarranged place names as noticed during the CWM/VGI pilot programme.


13

Figure 10 – Mozartlaan Street, Hengelo, the Netherlands in Google Maps

For example, in the Wikimapia coverage of the National Space Research and Development Agency premises in Abuja, Nigeria undershoot error was observed in the road network data – there were no place-name attributes. Similarly, in Google Maps the place is wrongly named as the National Space Development and Research Agency (Figure 11). Hence continuous editing of contributed mashups and place names is required in order to ensure data integrity of contributed VGI to the examined crowd-sourced mapping platforms.

Figure 11 – Undershoot errors in Wikimapia (left), and attribute error in Google Maps (right)


14

In terms of reasons for volunteers’ participation in the CWM/VGI pilot project, Table 2 shows the collated, average responses from 1st (highest) to 4th (lowest). Insufficient data content in most parts of Nigeria (ranked 1st) was the major reason for participating, followed by free access to the web 2.0 mapping platforms (2nd), an opportunity to familiarize oneself with web maps/GIS (3rd) and carrying out location-based analysis such as finding directions and places (4th).

Factors aiding participation in CWM/VGI Ranking (percentage)

insufficient data content in most parts of Nigeria 1st (40%)

free access to the web 2.0 mapping platforms 2nd

(32%)

opportunity to familiarize with web maps/GIS 3rd

(20%)

carrying out location-based analysis such as finding directions and places

4th (8%)

Table 2 - Identified reasons for participating in the CWM/VGI pilot project

3.3 Identified limitations of CWM and crowd sourcing VGI

In the enabling Web 2.0 platforms (Yang et al., 2010), one major attribute of CWM is ‘data’. Hence:

… an emerging role for the traditional information (VGI) provider is to perform a data verification function, to facilitate ease of use and access to the required information, and to ensure a good user experience which might become the central role and activities of VGI data providers (Parker, 2007).

Yet one of the problems encountered by the participants was providing useful identification for mapping. This was because contributing volunteered GI requires one to register by providing ID information, such as a valid e-mail address and a brief background about the area been mapped. The ID allows users to contribute and the contributed VGI content (or mashups) are further submitted for moderation by a mass of on-line contributors coordinated by Google team moderator. Only those approved to have met cartographic quality based on the web map template are then published against the contributors ID or user name.

Other limitations that were identified by the participants, especially the non-GI experts, included an inability to identify and classify features as observed from the background satellite images owing to differences in their spatial resolutions. Also, some participants were unable to effectively digitize features as points, lines or polygons, due to lack of high resolution images covering most parts of Nigeria.

In addition, many participants found it difficult to provide acceptable information to enable them to continue mapping, or to get their contributed VGI uploaded, owing to a lack of data integrity and the requirement to provide some metadata.

Other limitations were the unstable, electric power supply. During the CWM hands-on exercise session, the power supply was erratically going On and Off and participants had to shut down their systems intermittently. Indeed, about 19, 28% opted out and so could not complete the exercise.

Finally, the slow but high cost of Internet services, lack of knowledge about satellite or aerial photo interpretation and lack of volunteered time were other inhibitors that were mentioned.

Since various countries share almost similar economic and political characteristics, these limitations affect CWM in crowd sourcing VGI not only within Nigeria but also within sub-Saharan Africa in general.


15

4. Conclusion and recommendations

As government authorities shift from traditional desktop cartography to collaborative web mapping for crowd sourced VGI, and as the context within which GI are used alters substantially due to the availability of free, web map platforms like Google Maps, OpenStreetMap, Bing Maps, Yahoo! Maps and Wikimapia, users will have easier access to geospatial data. But they will typically have less knowledge of GIS and related technologies, along with a limited knowledge of the risks related to the use of geospatial data. This will sometimes lead to faulty decision making that may have significant consequences (Devillers et al, 2002).

This study examined the status and limitations of CWM as a viable tool for freely contributing to and using globally assessed, free Web Mapping Platforms (WMPs) such as Google Maps, Google Earth, OpenStreetMap, Bing Maps, Wikimapia and Yahoo! Maps. Google Map Maker Web 2.0 was adopted to conduct an experimental mapping analysis using 50 volunteers drawn from the staff of different departments of the National Space Research and Development Agency (NASRDA) and the Centre for Satellite Technology Development (CSTD) in Abuja, Nigeria, with 22% being GI experts and 78% not, and only 62% fully participating.

The FGDs emphasized how most government GI or mapping organizations in Nigeria fear irrelevance and job loses occasioned by an increasing use of VGI mashups. However, this fear should be allayed because:

… the new CWM and Web 2.0 techniques do not negate the importance of spatial analysis or cartography or surveying used in traditional geography and GI science: it is either one or the other, and there is clearly a space for both, so a synergy approach is required (Haklay et al., 2008).

The current wave of technologies, including smart phones and high speed Internet services, provides a rich source of empirical evidence at a scale that has not been available before, and these are relevant for all level of applications and use depending on the need of the users and the required quality.

Our study revealed that although it is difficult to contribute VGI, especially for non-GI experts, propagated errors by volunteers can be verified. Indeed, quality check requirements during ID sign-in registration for mapping, customised feature extraction, and compulsory web publication moderations can help reduce mapping errors to a bare minimum.

Nevertheless, it is our main conclusion that although most local people would like to map their area, the basic requirements for effective and efficient CWM include:

1. a reliable Internet facility,

2. basic knowledge of computer usage,

3. interest in geography and maps, and

4. time.

Hence the following recommendations seem sensible if we are to achieve a rapid increase in local, collaborative, community-based, online web mapping:

1. GI organizations should champion CWM by propagating knowledge of VGI while integrating experts and GI volunteers so that in the near future, Nigeria and African countries can be mapped in as much detail as most developed countries

2. governments of developing countries like Nigeria should ensures steady electric power supply and adequate project funding for the pragmatic implementation of the National Space Policy and the National Geospatial Data Infrastructure (NGDI) initiative


16

3. geography should be made a compulsory subject in primary, secondary and tertiary institutions

4. further study of effective VGI data downloading, and friendliness of the Web 2.0 mapping platform, should be conducted, and

5. synergy and collaborations between GI organizations in the area of spatial data quality and standards is imperative for seamless, geospatial data generation and its utilization in Nigeria, Africa and the world at large.

Acknowledgements

We are specifically grateful to the anonymous reviewers of this article. We also humbly express our profound gratitude to the editor(s) of this journal for their effort in getting this paper published. Many thanks to the NASRDA and CSTD CWM programme participants.

References

Bertin, J. (1983) - Semiology of graphics, Madison, University of Winscosin Press

Cho, W., Lee, K.J. & Kim, J. (2012) - Data Quality Control: Crowd Sourcing Geospatial Information, PowerPoint presentation to the Hangzhou Forum on United Nations’ Global Geospatial Information Management, 24 – 26 May, National Geographic Institute, Republic of Korea

Craglia, M., Goodchild, M.F., Annoni, A., Camara, G., Gould, M., Kuhn, W., Mark, D., Masser, I., Maguire, D., Liang, S. & Parsons, E. (2008) - Next-Generation Digital Earth. A position paper from the Vespucci Initiative for the Advancement of Geographic Information Science, International Journal of Spatial Data Infrastructures Research, Vol. 3, 146-167

Chuang, T. & Huang, A.W. (2005) - Online Community Mapping, presented to the PNC 2005 Annual Conference and Joint Meetings, October 31 – November 3, University of Hawaii at Manoa, Honolulu, retrieved Oct. 11, 2013 from http://pnclink.org/pnc2005/02_GIS.htm

Devillers, R., Gervais, M., Bédard, Y., & Jeansoulin, R. (2002) - Spatial Data Quality: From Metadata to Quality Indicators and Contextual End-User Manual, presented at the OEEPE/ISPRS Joint Workshop on Spatial Data Quality Management, Istanbul

Goodchild, M. F. (2007) - Citizens as Sensors: The World of Volunteered Geography. GeoJournal, 69, 211-221

Goodchild, M. F. (2009) - NeoGeography and the nature of geographic expertise, Journal of Location Based Services, 3(2), 82-96

Goodchild, M.F., Fu, P. & Rich, P. (2007) - Sharing geographic information: an assessment of the Geospatial One-Stop, Annals of the Association of American Geographers. 97(2), 249-265

Graham, M. (2010) - Neogeography and the palimpsets of place: Web 2.0 and the construction of a virtual earth, Tijdschrift voor economische en sociale geografie, 101, 422–436, doi: 10.1111/j.1467-9663.3009.00563.x

GSDI (2009) - SDI Cook Book

Estes, J.E. & Mooneyhan, D.W. (1994) - Of Maps and Myths, Photogrammetric Engineering and Remote Sensing, 60, 517-524

http://pnclink.org/pnc2005/02_GIS.htm


17

Haklay, M. (2010) - How good is volunteered geographical information? A comparative study of OpenStreetMap and Ordnance Survey datasets, Environment and Planning B, 37(4), 682-703

Haklay, M., Singleton, A. & Parker, C. (2008) - Web Mapping 2.0: The Neogeography of the GeoWeb, Geography Compass 2/6, 2011–2039, 10.1111/j.1749-8198.2008.00167.x Journal Compilation, Blackwell Publishing

ITC, (2010) - GI Science and Earth Observation: A processed-based approach, ITC Educational Textbook Series, Faculty of Geoinformation Science and Earth Observation, University of Twente, Enschede, The Netherlands

Kraak, M. J., & Ormeling, F. J. (2010) - Cartography: visualization of spatial data (third edition) New York, London, Guilford Press

Lemmens, R. (2012) - Collaborative Mapping & Crowdsourcing, Google Map Makerpedia. (Web article), https://sites.google.com/site/mapmakerpedia/home, accessed 09/10/2012

Man, E. de (2007) - Beyond Spatial Data Infrastructures there are no SDIs – so what, International Journal of Spatial Data Infrastructures Research, 2, 1-23

Murugesan, S. (2007) - Understanding Web 2.0, IT Professional, 9(4), 34-41

Olomo, R.O. (1997) - Modern Comprehensive Practical Geography, Pon Publishers, Agbor, Delta State

Onokerhoraye, A.G. (1994) - Geographic Thought, Philosophy and Methodology, Benin Social Science Series for Africa, University of Benin, Nigeria, Intec Printers, Ibadan

Openshaw, S. (1989) - Learning to live with Errors in spatial Databases, in Goodchild, M. & S. Gopal (eds.): Accuracy of Spatial Databases, London, Taylor & Francis, 263-276

Parker, C.J. (2007) - Addressing grand challenges and global problems, using location information in formal and informal web-based communities, presented to Association of Geographical Information Annual Conference, Strafford-Upon-Avon, UK, September 20

Rogers, E.M. (1995) - Diffusion of innovations (4th edition), The Free Press, New York

Seeger, C.J. (2008) - The Role of VGI in the landscape planning and site design process, Geojournal, 2, 199-213

Sipes, J.L. (2002) - Digital Town Hall: Public participation in cyberspace, Landscape Architecture Magazine, 92(8), 52-56

Trans, T. (2007) - Google Maps Mashups 2.0, Google Lat-Long Blog, posted 11/7/2007, retrieved 2/11/2007 from http://google-latlong.blogspot.com/

Turner, A. (2006) - Introduction to Neogeography, O'Reilly Media

Wall Street Journal (2007) - Acquisition to Expand Microsoft’s Map Services, 13 December

Wigand, R. T., Benjamin, R. I., & Birkland, J. L. (2008) - Web 2.0. And Beyond: Implications for electronic commerce, Proceedings of the 10th international Conference on Electronic Commerce, Innsbruck, Austria, August 19 – 22, vol. 342. ACM, NY, 1-5

World Bank (2011) - Population Data, accessed 10/10/2012 and retrieved from http://data.worldbank.org/indicator/SP.POP.TOTL?cid=GPD_1

Yang, C., Raskin, R., Goodchild, M. & Gahegan, M. (2010) - Geospatial Cyber infrastructure: Past, present and future, Computers, Environment and Urban Systems, 34, 264–277

-----------------------------------------------------------------------------------------------------------------------

https://sites.google.com/site/mapmakerpedia/home,%20accessed%2009/10/2012

https://sites.google.com/site/mapmakerpedia/home,%20accessed%2009/10/2012

http://google-latlong.blogspot.com/

http://data.worldbank.org/indicator/SP.POP.TOTL?cid=GPD_1

applied gis - monash university...bello, i.e. & ojigi, l.m. (2013) – collaborative web mapping...

Documents