sustainability
Communication
Humanitarian Mapping as a Contribution to Achieving
Sustainable Development Goals: Research into the Motivation
of Volunteers and the Ideal Setting of Mapathons
Radim Štampach , Lukáš Herman * , Jakub Trojan , Kateˇrina Tajovská and Tomáš ˇRezník
Citation: Štampach, R.; Herman, L.;
Trojan, J.; Tajovská, K.; ˇRezník, T.
Humanitarian Mapping as a
Contribution to Achieving
Sustainable Development Goals:
Research into the Motivation of
Volunteers and the Ideal Setting of
Mapathons. Sustainability 2021, 13,
13991. https://doi.org/10.3390/
su132413991
Academic Editor: Corrado Battisti
Received: 24 October 2021
Accepted: 15 December 2021
Published: 18 December 2021
Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims in
published maps and institutional affil-
iations.
Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
Department of Geography, Faculty of Science, Masaryk University, Kotlarska 2, 61137 Brno, Czech Republic;
stampach@mail.muni.cz (R.Š.); trojan@sci.muni.cz (J.T.); 54836@mail.muni.cz (K.T.);
tomas.reznik@sci.muni.cz (T. ˇR.)
* Correspondence: herman.lu@mail.muni.cz; Tel.: +420-549-497-612
Abstract: Missing Maps is a humanitarian mapping project that maps vulnerable places in the
developing world. Its outcomes are used to target aid in affected areas and to help achieve Sustainable
Development Goals. A mapathon is an event in which a group of volunteers maps a defined location.
The presented communication answers the following questions: What is the motivation of different
contributors in the Missing Maps community in Czechia and Slovakia? How can a mapathon be set
up to attract as many participants as possible? How exactly can the contributors to humanitarian
mapping subjectively evaluate their contribution so far? A questionnaire about the motivation of
contributors and the analysis of statistics from eighteen public mapathons in Brno (Czechia) were
used as the primary research methods. The analysis of motivation found six strong motivators. Half
of them concern altruism and half of them relate to the importance of the OpenStreetMap project and
the mapping community. Analysis of the characteristics of 18 mapathons found that the month of the
mapathon had a significant influence on the number of attendants. Statistical analysis confirmed a
significant correlation between the number of edits and participants’ self-assessment. This means
that humanitarian mappers evaluate their overall contribution very realistically. Analyses with an
identical scope are planned for future years.
Keywords: Sustainable Development Goals; OpenStreetMap; volunteered geographic information;
citizen science; humanitarian mapping; mapathon; attendance; motivation; self-assessment
1. Introduction
Sustainable Development Goals (SDGs) [1] are at the heart of the 2030 Agenda for
Sustainable Development [2], which was adopted by all United Nations Member States
in 2015. The critical condition for monitoring and meeting the Sustainable Development
Goals is the availability of data, including spatial data. Crowdsourced data is helping fill
data gaps as well as provide insights into SDGs progress.
In the case of geospatial data, the OpenStreetMap (OSM) project [3] has become a
synonym for volunteer mapping, as well as an alternative to the products of national
mapping organizations (NMOs). Discussions on the quality of volunteer mapping versus
official map products from NMOs remain ubiquitous [4–8]. Volunteer crowdsourcing [9,10]
has also become a possible (yet still underutilized) source of data. Spatial data produced
by volunteers are referred to as volunteered geographic information (VGI) [11].
The Humanitarian OpenStreetMap Team (HOT) [12] is an international team dedicated
to humanitarian action and community development through open mapping. It provides
map data for disaster management that reduce risks and contribute to the achievement
of Sustainable Development Goals [13]. Beyond the context of open data, it is a broad
community partnership to collaboratively create a critical data resource for monitoring
Sustainability 2021, 13, 13991. https://doi.org/10.3390/su132413991 https://www.mdpi.com/journal/sustainability
Sustainability 2021, 13, 13991 2 of 24
and meeting SDGs by making available fundamental, detailed, and timely information on
where things are in our world [14].
There are many ways in which crowdsourced mapping using OSM can help to achieve
SDGs. For most SDGs, developing basemaps of buildings and road data and place names
(i.e., villages, towns, cities) is the starting point. Several examples of relevant demonstrations
have been presented in [15]. A brief selection is presented as follows:
• Goal 1—No Poverty—Putting villages and household footprints on a map is often the
first step in giving communities a voice in land rights. Geospatial information is critical
in helping people claim their property rights. Kenya’s Map Kibera project (begun in
2009) collects citizen-generated data and other kinds of relevant open data in one of
the region’s biggest slums-turned-informal-cities to enhance citizen accountability,
development planning, and government use.
• Goal 3—Good Health and Wellbeing—Public health data collection projects provide
local governments and organizations with information to improve their response
to health-related issues, such as malaria prevention. In 2018, the HOT supported
malaria elimination projects on the ground in Guatemala and Botswana by providing
geographical data and training. Data were used for logistics and indoor residual
spraying campaigns, for bed net distribution, and for improved monitoring and
evaluation to measure intervention impacts.
• Goal 4—Quality Education—Crowdsourced mapping provides a two-fold benefit
towards reaching the SDG for education: assisting partners, governments, and local
communities in recognizing gaps in services and the distribution of educational
facilities, as well as providing an opportunity for individuals in these groups to gain
technical and vocational skills such as GIS and surveying.
• Goal 5—Gender Equality—Since 2015, the Crowd2Map project has been mapping
rural Tanzania. These maps are used by community activists to locate and protect
girls at risk of female genital mutilation, as well as to provide local officials with data
needed to plan for the development of services.
• Goal 7—Affordable and Clean Energy—HOT completed the large-scale digitization of
rural Tanzania using mapping and household surveys, identifying millions of buildings
and more than a thousand villages. By collecting this highly detailed data on
settlements, HOT enabled the government and private electricity and renewable energy
providers to predict demand and determine where grid and off-grid connections
can be made.
• Goal 9—Industry, Innovation, and Infrastructure—With OSM, roads and buildings
can be mapped remotely while teams on the ground add important information such
as building conditions and road surface quality.
• Goal 16—Peace, Justice, and Strong Institutions—Crowdsourced mapping promotes
participatory action that increases the representation of communities. OSM is used by
humanitarian agencies in decision-making.
Solís et al. [16] describe other examples of how campaigns of volunteered geographic
information and participatory GIS driven by the YouthMappers initiative [17] relate to
various SDGs. Our focus here is on Goal 3—Good Health and Wellbeing—providing
building and road infrastructure information for an insecticide spray campaign to prevent
malaria and protect public health in Mozambique and Kenya. The author notes that
“Participatory mapping can support greater understanding of connections among places,
the people living in them, and the phenomenon arising from global change, in ways that
people ranging from scholars to youth to policymakers can quickly grasp”. The remote
cooperation between students from George Washington University and students from the
University of Kathmandu on the mapping of infrastructure in Kathmandu is an example of
cooperation between remote and local participants and the engagement of young people
from different parts of the world [16].
Another work by Solís et al. [18] provides a global survey of 205 students participating
in the YouthMappers initiative, focusing on how they understand the significance of their
Sustainability 2021, 13, 13991 3 of 24
work for SDGs. They detected differences by gender and world region. Participants from
the Global South perceive themselves to be more engaged with SDGs than those from the
Global North. This study suggests that humanitarian mapping can help motivate students
to be socially responsible. Leveraging student-led movements on connected campuses
offers one possible way of creating a sense of global citizenship, a critical component in
achieving SDGs [18].
SDGs are also strongly connected with disaster risk management (DRM). It is impossible
to build wellbeing, infrastructure, economic growth, or sustainable cities if our efforts
are regularly undermined by natural or man-made disasters. Geospatial data is a necessary
part of DRM. Crowdsourced mapping is still underestimated but is a potential source of
geospatial data for DRM.
The experience of the OSM response to the 2010 Haiti earthquake demonstrated that
volunteers who collaborated around open data could quickly create accurate information
after a disaster. Nevertheless, it is better to prepare data in advance of a disaster to allow
disaster preparedness. In [19–21] we can see other examples of how to create and use
prepared crowdsourced geospatial OSM data for DRM:
• OSM project Community Mapping for Exposure, Indonesia (2011)—the project worked
with local governments, university students, and civil society groups. The mapping
work focused primarily on critical infrastructure in the capital region of Jakarta,
including schools, hospitals, community centers, and places of worship. The resulting
data were combined with hazard information from a variety of sources to produce
realistic impact scenarios [19].
• Open Cities project Batticaloa (2012)—Batticaloa, a major city in Sri Lanka’s Eastern
Province severely affected by the 2004 Indian Ocean tsunami, is located in a hazardprone
area that has suffered near-annual droughts, floods, and cyclones. Footprints
and basic building characteristics, including the number of floors, usage, and the
construction materials used for walls and roofs were collected for all buildings in the
area [19].
• Open Cities Kathmandu (2012)—Kathmandu, the capital city of Nepal, is the most
seismically at-risk city in the world in terms of the potential for loss of human life
during a major event. Open Cities Kathmandu surveyed 2256 schools and 350 health
facilities in the Kathmandu Valley [19].
• One Map Myanmar (2018)—The American Red Cross has been working alongside the
Myanmar Red Cross to better understand the locations of critical infrastructure and
roads in order to allow decision-making during major disasters such as floods and
cyclones [20].
• Burundi anti-malaria campaign (2020)—Médecins Sans Frontières/Doctors Without
Borders (MSF) has prevented the disease from spreading in eastern Burundi with
an indoor residual spraying campaign. As large parts of the area were not mapped,
Missing Maps volunteers traced nearly 90,000 buildings in the rural region of Ruyigi
in Burundi. Over the following month, teams on the ground managed to spray 97% of
these households [21].
The latter two campaigns were part of the Missing Maps project. Missing Maps [22]
is a humanitarian mapping project that aims to map the most vulnerable places in the
developing world using OSM—in advance of an eventual disaster. International and
local non-governmental organizations, national and local governments, communities, and
individuals use the created OSM data to better respond to crises, achieve SDGs, and
monitor their progress. It is essential to have a large pool of trained volunteers ready to
assist when a disaster occurs [23]. Hence, there is a motivation to expand the community
of voluntary mappers and motivate them to contribute actively.
A mapathon (or mapping party) is an organized collaborative event in which a group
of volunteers collectively map a chosen location in places where OSM data is scarce or
non-existent [24]. The purpose of mapping parties is to map and socialize [25]. Organizers
pursue several aims focused on newcomers: to initiate them into the practice, to have
Sustainability 2021, 13, 13991 4 of 24
them produce maps throughout the event, and then to retain these new contributors for
future activities [26,27]. Classic mapathons are held at an agreed place where mappers
from a regional community group and come together in person. However, more and
more mapathons are currently organized online due to the pandemic as a substitute for
classic mapathons.
Humanitarian mappers do not have to go to mapathons; many of them work online
from home. Nevertheless, mapathons can empower users to gain new skills and experience.
Users actively producing content in OSM are mostly made up of people who attend
mapping parties [25]. One of the key goals of organizing mapathons is to attract recurring
participants. They can help to tutor beginner mappers and produce more and better-quality
data [28].
The authors of the paper are members of the Czech Missing Maps community and the
team that organizes mapathons in the city of Brno, Czechia. The motivation behind this
study was to expand the active Czech and Slovak humanitarian mapping community of the
Missing Maps project. This means attracting new mappers and ensuring greater attendance
at mapathons. To achieve this, it is necessary to discover what attracts contributors from
Czechia and Slovakia to participate in humanitarian mapping and to attend mapathons
and to discover the reasons why former contributors sometimes cease to contribute. This
should reduce the departure of experienced mappers and increase the chances of creating
more and better data. This paper communicates our preliminary results after the first round
of data collection from the questionnaire. Analyses with an identical scope are planned for
subsequent years and forthcoming mapathons.
An additional aim of our study was to examine the respective humanitarian mappers’
self-assessment of their contributions in order to learn more about the contributors’ perspective
on humanitarian mapping and mapathons and their level of satisfaction with their
mapping efforts.
We attempted to answer the following research questions:
(A) What are the motivations of different contributors in the Missing Maps community
in Czechia and Slovakia?
(B) How can a mapathon be set up to attract as many participants as possible?
(C) How do contributors to humanitarian mapping subjectively evaluate their contributions?
Do they underestimate or overestimate the importance of their results?
1.1. Citizen Science as an Umbrella for Humanitarian Mapping
The practices of volunteer-based data gathering have a theoretical framework within
the concept of citizen science [29]. Citizen science—a new term but an old practice—is
related to the opening up of science. Scenarios in which parts of research are in the general
public’s hands [30] relate to scientific approaches, tools, and data sets that were formerly
used exclusively by researchers. The term “neo-geography” (see Turner [31], who championed
the term in 2006) has also been employed [32], though the citizen science approach
can be used in any scientific field, not only in geography. For example, West et al. [33] used
volunteers to monitor air pollution, while Alender [34] wrote about volunteers monitoring
water quality. Citizen science incorporates diverse forms of interaction and cooperation
among public volunteers to benefit society and the environment [35–37]; these interactions
are significantly supported by machine learning and artificial intelligence [38].
The closely-related term citizen management is used by [39,40]. In citizen science,
properly trained citizens can participate in a widespread and fine-grained process of
knowledge acquisition. In citizen management, citizens adequately trained in problemsolving
can change the state of an environmental system with positive effects on the system
and themselves [39]. Study [40] describes this concept using the example of beach litter
clean-up campaigns. Here, it can be understood that ‘citizen science’ is used in a nature
conservation project.
The concept of humanitarian mapping is often referred to in connection with the
earthquake in Haiti in 2010, as mentioned in [41–43]. This suggests that citizen science
Sustainability 2021, 13, 13991 5 of 24
activities in humanitarian mapping came later than other citizen science activities, the
latter utilized mainly in the natural (environmental) sciences; however, the utilization of
community-based mapping in social sciences can also be found (see [44] with the example
of socio-economic variables). In the case of humanitarian mapping, where data are needed
as quickly as possible, citizen science as an umbrella term for many activities often appears
in the form of crowdsourcing [45,46].
Hackley [47] describes crowdsourcing as one of the various levels of public engagement.
Crowdsourcing is understood as “the lowest level” of activities linked to data collection.
However, the importance of crowdsourcing is enormous (as previously documented,
e.g., by Goodchild [11]). We should not see levels of participation as a hierarchically determined
sequence, with level 1 (in Haklay’s scale, equal to crowdsourcing) being “worse”
than level 4 (equivalent to extreme citizen science, according to Haklay). Indeed, deep
research conducted among Czech citizen science projects (see Duží et al. [48]) shows that
crowdsourcing is a feature of the majority of such projects. As we focus on spatial data
collection, we often use the term volunteered geographic information (VGI), defined by
Goodchild [11] and further elaborated, for example, by Sui et al. [45]. In this respect, VGI is
used as a synonym for crowdsourcing in the field of cartography and geography [32,45].
Mapathons, conducted as part of humanitarian mapping to expand geospatial knowledge
within the OSM project framework, engage the public in an organized way to obtain volunteered
geographic information to [49]. A combination of the citizen science approach and
the need to contribute to the resolution of socially pressing issues could also serve as a good
motivation for participants to be engaged long-term in such voluntary activities [50,51].
Citizen science also has a strong connection to SDGs, an idea that was discussed by
Fritz et al. [52] and supported by key policymakers, e.g., during the conference “Knowledge
for Change: A Decade of Citizen Science (2020–2030) in support of the SDGs” [53] organized
as an official event of Germany’s 2020 EU Council presidency. Fraisl et al. [54] discuss the
potential of citizen science to contribute to many more than 76 SDG indicators. The direct
connection between humanitarian mapping and SDGs is described in the Introduction.
1.2. The Humanitarian OpenStreetMap Team and the Missing Maps Project
The history of humanitarian mapping is well described [9,55–58]. The Humanitarian
OpenStreetMap Team (HOT) [12] was established in August 2010 to produce maps in OSM
for humanitarian work in areas affected by a disaster. It is an example of mapping for
disaster management after a crisis has hit.
A very active part of HOT is the YouthMappers initiative [17]. It is an academic
network of university-based, student-led, and faculty-mentored local chapters, currently
with members from many university campuses in many countries around the world [16].
It is designed to encourage students and their faculty mentors to participate in creating
open, free spatial data for humanitarian efforts [24,58]. Participating groups can apply for
grants, research fellowships, and other benefits. Studies by Solís et al. [16,18] explain how
YouthMappers contribute to various SDGs. This is described in the Introduction.
The Missing Maps project [22] was founded in 2014 as a joint venture of the British
and American Red Cross, Médecins Sans Frontières/Doctors Without Borders (MSF), and
the Humanitarian OpenStreetMap Team mentioned above [58]. Many other organizations,
universities, and entities have joined the project since that time. The goal of the Missing
Maps project is to map the most vulnerable places in the developing world where MSF or
other humanitarian organizations plan to work. It is an example of mapping as a form of
prevention [57].
The Czech and Slovak community is a viable part of the Missing Maps project. The
first mapathon in Czechia was held in Prague in June 2016. Over a period of two years
(June 2016–June 2018), 840 members of the Czech community participated and mapped
more than 400,000 buildings and 13,000 km of roads [59]. In November 2016, Brno became
the second Czech city to host a mapathon. After the event, an organizing team in Brno
was established and has since organized another 18 mapathons; the first was held in
Sustainability 2021, 13, 13991 6 of 24
December 2016. Masaryk University hosted most of these events. Others were co-organized
by private companies (Red Hat, Kiwi.com (Brno, Czech Republic), CleverMaps (Brno,
Czech Republic), and the rest of the mapathons took place as part of various events hosted
by non-profit organizations. The attendance statistics from organized mapathons are one
of the data inputs of this article.
1.3. (Dis)Connections and Engagements between Stakeholders Related to Humanitarian Mapping
We may identify several kinds of (dis)connections and relationships between various
stakeholders related to humanitarian mapping and citizen science. The following
statements are based on a review of scientific papers concerning the state-of-the-art, other
reference materials, and the experience of the authors of this paper.
Humanitarian mapping, including the use of mapathons, represents one source of
newcomers to citizen science. However, as stated for example by Béland [60], humanitarian
mapping and mapathons often bring insufficiently skilled or engaged newcomers to the
OSM project. Various authors declare that new participants in humanitarian mapping and
mapathons exhibit three major weaknesses:
• their contribution to OSM is low; we speak of ‘hit-and-run’ contributors [60],
• the average number of mistakes in mappings performed by new participants in
humanitarian mapping activities is higher than the average number produced by
other more experienced participants [56],
• most new participants do not become regular participants [61].
We can witness significant tensions between some highly experienced OSM contributors
and humanitarian mappers, as stated, for example, by [61–64]. Experienced OSM
contributors claim that the OSM project is being used for a different purpose than that
primarily envisaged for OSM, i.e., mapping based on local knowledge [64]. Sometimes,
highly experienced OSM contributors are disappointed by the strong public response that
humanitarian mapping enjoys throughout society. That is, by the general impression that
the OSM project serves a primarily humanitarian purpose [63].
Further tension arises between highly experienced OSM contributors and humanitarian
mappers/humanitarian mapping organizers due to their different points of view with
respect to initial training [62,64]. Highly experienced OSM contributors support initial
training that lasts several hours and comprises a wide variety of examples of mapped
spatial objects (in order “to map everything in relation to each other”). In contrast, initial
training in humanitarian mapping (e.g., at mapathons) typically lasts about one hour
(during a three-hour mapathon) since only three kinds of spatial objects are mapped:
buildings, residential areas, and roads. Conceptually, therefore, the demands of these two
stakeholder groups are different: highly experienced OSM contributors desire mapping in
its full complexity, while humanitarian mappers adopt a more limited, application-driven
approach. Generally speaking, however, both stakeholder groups collaborate intensively
despite these differences, driven by a shared passion and a common goal: to prepare a free
and editable map of the world.
The following conceptual steps would bring the various stakeholder groups of highly
experienced OSM contributors and humanitarian mappers closer together:
• Humanitarian mappings should be organized with as many local contributors as is
feasible. Such a step is crucial for synergy between both stakeholder groups [63]. The
participation of local contributors from the mapped countries adds value to the remote
action, as described by Solís et al. [16,18] regarding the case study of Kathmandu
Living Labs. It allows for the creation of both local and remote open data.
• The number of repeat participants should be increased. This is also one of the primary
goals of the efforts described in our paper. Increasing the number of repeat participants
would lead to an improvement in the overall quality of mapping thanks to
(1) the further training received by less-experienced mappers and (2) the greater input
received from highly experienced contributors [62].
Sustainability 2021, 13, 13991 7 of 24
• Unlike classical contributions to OSM, humanitarian mapping allows for the secondary
revision of created data by more experienced users, regarded as “validators” [16].
The shorter initial training of humanitarian mappers should be compensated by the
more complex training of validators and organizers of mapathons [64] as well as the
development of data validation tools, even during the mapping process [61]. The role
of humanitarian mapping validators is essential for maintaining the high quality of all
contributions made during humanitarian mapping—in particular, at mapathons.
1.4. Looking for the Motivations of VGI Contributors
Humanitarian projects based on OSM (HOT OSM, Missing Maps) have many volunteers.
In general, the participants’ motivations may range from enjoying helping vulnerable
people to spending free time doing “good things”. Motivations can also be influenced
by many other aspects, as recently described in [65]. Furthermore, using gamification
approaches to mapping (e.g., getting ‘points’ for every changeset in the map) can help
maintain participation by, for example, creating a sense of competitiveness amongst the
players and making them feel they are part of a community when playing as a team [61].
Detailed analysis of the motivations of mapathon participants is described, for example,
by Dittus, Quattrone, and Capra [26]. They investigated whether first-time participants
(beginners) with little experience continue mapping at home in the week after the mapathon.
On average, 50% of monthly mapathon attendees were recurring visitors. Around
10% of first-time attendees subsequently mapped at home in the first week, and a similar
proportion returned to a future mapping party event. The number was significantly lower
in irregular mapathons organized mainly by private companies. It seems that the regularity
of mapathons is essential to maintain motivation among newcomers. Online participants
of mapathons were approximately three times less likely to be retained for future work.
Dittus, Quattrone, and Capra [26] also looked at what influenced the retention of
beginner participants. Technical problems during the mapathon could negatively affect
the work of newcomers. However, they did not influence the number of newcomers that
continued mapping after the mapathon. Having a mix of attendees in terms of prior
experience, from newcomers to highly experienced mappers, also had a positive effect. The
enthusiasm of others can inspire newcomers.
Loftian et al. [66] and Hristova et al. [25] note that mapathons result in a significant
increase in OSM contributions, though, in contrast to experienced users, newcomers
typically stop participating after the event is over. Hristova et al. [25] measured user
participation in mapping parties organized regularly in the Greater London area. Most
mappers (69%) participated in one event only, while the remaining 31% took part repeatedly.
Mapping party attendance appears to be seasonal, with decreased attendance in the first
and last quarters of each year.
Green et al. [28] organized four mapathons in which only students of geoinformatics
participated. A total of 60% of mappers participated in more than one mapathon. However,
extra credit was offered to the students as an incentive. They also measured productivity
and found that more experienced participants were generally more productive.
Questionnaires to determine the motivations of OSM contributors were used by
Schmidt and Klettner [67], Budhathoki and Haythornthwaite [68], and Alender [34].
Schmidt and Klettner [67] asked inactive OSM participants what could motivate them
to become active again. The answers differed according to the participants’ previous
experience. Less experienced contributors specified tutorials for beginners, while more
experienced contributors identified mapping for a specific purpose, e.g., disaster mapping,
as a potential motivation. Many inactive participants mentioned “lack of time” as the
reason for their inactivity.
Budhathoki and Haythornthwaite [68] explored differences in motivation between
serious and casual OSM contributors. Both groups emphasized the importance of the
community, the goals of the project (a free detailed map of the world), and the importance
of helping others. Differences between groups were also described. Serious mappers were
Sustainability 2021, 13, 13991 8 of 24
more oriented towards the community (the goal of OSM cannot be achieved without a
community) than casual mappers. Casual mappers were more oriented towards the overall
goals of free and open-source projects (maps should be available for free).
Alender [34] describes similar results. The strongest motivators for participants
are helping enhance the environment, helping the community, connecting with nature,
and contributing to scientific knowledge. The weakest motivators are enhancing reputation
in the community and advancing one’s career. No variation by gender was found,
but younger volunteers rated “career” motivation much more highly than the other age
groups. The study also recommends grouping more experienced volunteers with less
experienced volunteers.
The aforementioned papers seem to indicate that motivation depends on the experience
of the contributors and that the desire to help others is a strong motivator not only
for humanitarian mappers. An interest in geography and a love of maps are, of course,
communitywide motivators. Both casual and serious mappers are well motivated by
orientation and interest in mapping and geography and particularly by the possibility of
contributing to local geography [68].
The creation and use of maps are topics also researched by means of psychological
methods. Gómez-Barrón, Manso-Callejo, and Alcarria [69] offer a psychological view of
the motivation of VGI producers. Another type of interdisciplinary research in psychology,
geography, and cartography using psychological methods is presented by [70]. Volunteerism,
however, is probably as old as humankind and is not related specifically to VGI or
OSM. An example of a study about the motivation of volunteers not focused only on VGI
is that by Clary and Snyder [71].
1.5. Experiences with Mapathons—How to Make Them Successful
The abovementioned work [26] looked at how some aspects of the organization of
mapathons influence their success. They discussed, among others, the following measures:
• Mapathons should include a mix of less and more experienced participants so that
attendees who are experienced in mapping can provide necessary peer support.
• Refreshments should be served in a separate area—food served in a separate room
may disrupt work, but it also encourages communication between participants.
• Technical issues at mapathons (especially a weak internet connection or too few
electrical outlets) should be kept to a minimum, as they diminish the participants’
overall experience.
A comparison of mapathon organization experiences from three different universities
in three different countries (Italy, USA, South Africa) is offered in [24]. Various strategies
are discernible. The following is a list of examples that could serve as inspiration:
• Some universities accept mapathons as part of the curriculum [24]. Another possibility
is to incorporate the teaching of open imagery and open mapping tools in other
programs and courses [16].
• Some universities give additional credit to students who participate in mapathons [24,28].
Students use it to improve their grades, so this gesture boosts attendance. On the other
hand, some studies cast doubt on this approach. Clary and Snyder found that there
was a slightly negative relationship between prior experience and future intentions to
volunteer for students who felt under external pressure to volunteer [71].
• Students participating in Youth Mappers are involved voluntarily and regularly organize
mapathons for their members [24].
• Sometimes, finding a date for a mapathon suitable for most students is challenging
(e.g., during exam periods). A humanitarian mapping project could be selected on
the HOT Tasking Manager, which would allow contributors to contribute for a whole
week [24].
• A mapathon could include a Skype call with a practitioner from the agency requesting
the data in order to provide context [24].
Sustainability 2021, 13, 13991 9 of 24
• The website “Show Me The Way” [72], which displays the real-time mapping of OSM
users, is visible on a large screen during the mapathon [24].
The most comprehensive recommendations for organizers of mapathons can be found
on the official website of Missing Maps [23,27]. Here is a summary:
• Find a space that fits your group—a library, community center, university, private
company, etc.
• Publicize your event on social media, on websites, in the local OSM community, etc.
• A strong Internet connection (typically wifi) is necessary. Slow wifi is the worst threat
to the success of a mapathon.
• Recruit organizers/helpers. One helper is recommended for every 10 mappers at
in-person events and for every 2 or 3 mappers online, depending on the group size.
• There must be a sufficient number of extension cords for everyone to power a laptop.
• Extra laptops/computers for people that may not bring their own are a good idea.
• Print training and publicity materials—available on MissingMaps.org.
• Arrange refreshments for the mappers. They will stay longer, and they will map
longer. “Pizza fills the Map!”
• Invite a special guest who can present his experience from the field (e.g., MSF, HOT,
OSM, etc.).
• Inform people about the mapping task and the locality; speak with them about what
they see on the map.
• Use a group hashtag during mapping. It allows the results of your group to be
summarized after more mapathons or at the end of the year.
• Show the mapathon results—the number of mapped buildings and paths; use a
leaderboard to show the best mapper of the mapathon.
• At the end of the mapathon, go to the pub with the mappers. It is a way of recruiting
new organizers to your team.
Organizers of mapathons from the Czech and Slovak Missing Maps community added
some further tips based on their experiences (shared on the Trello platform of the Czech
and Slovak community [73]):
• Search for and try new locations for mapathons. Try to reach companies.
• Allow participants to choose from more groups with different levels of experience—e.g.,
beginners, advanced mappers, experts/validators. Each group can have its own experienced
trainer who explains tips appropriate to the level of his group.
• Some experienced mappers should be with a group of beginners to be available to
help or to answer questions [28,73].
• There should also be a group for participants who want to map without training and
without being disturbed. Usually, this is the case with experienced mappers.
Most of the above-mentioned recommendations for setting up mapathons are employed
for mapathons organized in Brno. In the literature and manuals, however, there
is a lack of statistical evidence about the influence of these recommendations—e.g., the
possibility of using a borrowed computer. Mapathons held at the Department of Geography
offer computers to participants who do not have their own laptops.
In addition, some aspects are not covered in manuals for organizers—e.g., the choice
of a weekday for a mapathon. We tried to explore the influence of selected characteristics
of mapathons on attendance.
2. Materials and Methods
Two types of data were collected:
• Questionnaire answers about the motivations of contributors from the Czech and
Slovak Missing Maps community for humanitarian mapping.
• Attendance statistics concerning the previous 18 mapathons organized in Brno city.
Questionnaire data were collected from February 2020 to April 2020. The questionnaire
was prepared in web form. It was focused on anyone interested in the Missing Maps project
Sustainability 2021, 13, 13991 10 of 24
in Czechia and Slovakia. The questionnaire was disseminated through many electronic
communication channels, either by e-mail to former participants of mapathons or through
sharing in the official Facebook group of the project “Missing Maps Czechia & Slovakia.” We
also planned to offer questionnaires to participants during various mapathons in Czechia;
however, in-person mapathons were canceled because of the COVID-19 pandemic and
switched to online events. Despite all the dissemination methods used, only 44 completed
questionnaires were obtained—see Table 1. We see this paper as a communication of
our preliminary but significant results. Analyses with an identical scope are planned for
upcoming years and upcoming mapathons.
Table 1. Characteristics of respondents.
Number of Participants 44
Experience (more experienced = more than 1000 edits) (%)
less experienced 38.6
more experienced 61.4
Gender (%)
Male 68.2
Female 31.8
Education (%)
elementary school 2.3
high school 25.0
university—BSc. 18.2
university—MSc. and higher 54.5
Age (%)
25 and under 29.6
26–35 50.0
36–45 13.6
46 and over 6.8
The questionnaire consisted of several sections. The first section collected the anonymous
personal details of the participants—age, gender, education, the field of employment
or study, and status of employment. These are presented in Table 1. The main section of the
questionnaire concerned the evaluation of motivation. Motivation, in this case, was defined
on the basis of 21 statements that represent possible motivators (Table 2). The motivators
and statements offered in the questionnaire were based on the studies by Budhathoki and
Haythornthwaite [68] and by Clary and Snyder [71]. All statements were measured using
a five-point Likert-type scale with 1 as strongly disagree and 5 as strongly agree.
In the last section, participants were asked to fill in the number of his/her total edits
from their profile on the Missing Maps page [74]. They were also asked to evaluate their
overall contribution to the OSM project, this time on a scale from 1 (minimal contribution)
to 10 (maximal contribution). This section of the questionnaire also asked “When was the
last time you contributed to humanitarian mapping?” If a participant selected the answer
“more than one year ago”, additional questions appeared, such as “Why did you stop
contributing?” and “Do you plan to continue?”
The responses from the questionnaires were analyzed using methods of descriptive
statistics. Simple statistical measures were used, including means, medians, and standard
deviations. The assumption of normal distribution was tested by the Shapiro–Wilk
test. Because the distribution did not assume a normal distribution, we conducted the
Mann–Whitney U test to identify differences in motivation between identified groups of
humanitarian mapping contributors (based on age, gender, education, mapping experience,
field of employment or study, and status of employment). For the same reason, Spearman’s
coefficient was used to calculate the correlation between the number of edits made by a
participant and the participant’s evaluation of his/her contribution to OSM. Results are
displayed using a boxplot graph.
Sustainability 2021, 13, 13991 11 of 24
Table 2. Motivation from the questionnaire. Values are from a Likert-type scale: 1—strongly disagree,
2—disagree, 3—neutral, 4—agree, 5—strongly agree.
I Contribute Because . . . Mean Median
. . . I believe that my work yields significant results. 4.5 5.0
. . . helping other people is important to me. 4.4 5.0
. . . I like making maps. 4.3 5.0
. . . the community of volunteers around humanitarian
mapping is important to me.
4.2 4.0
. . . I believe that digital maps should be accessible to
everyone for free.
4.1 4.0
. . . I feel better and more satisfied with myself. 4.1 4.0
. . . it is a good means of self-realization. 3.8 4.0
. . . I like seeing immediate results. 3.8 4.0
. . . I want maps not to be created only for
commercial purposes.
3.6 4.0
. . . I am a better human because of it. 3.4 4.0
. . . I feel that I am part of a bigger group because of it. 3.2 3.0
. . . it helps me to better understand
geographical relationships.
3.1 3.0
. . . it helps me to better understand how the world works. 3.1 3.0
. . . it is a fine method of procrastination. 3.0 3.0
. . . it helps my professional development. 2.8 3.0
. . . it helps me to forget about personal problems. 2.6 2.5
. . . it is a good activity to include in my CV. 2.3 2.0
. . . people in my surroundings also contribute. 2.1 2.0
. . . I need OSM data for my work. 2.1 2.0
. . . it helps me to get the job I want. 1.8 1.0
. . . I get money for it. 1.2 1.0
We also analyzed attendance statistics relating to public mapathons in Brno that were
organized by our group. These comprised 18 public mapathons held between December
2016 and February 2020 with 183 individual participants. We correlated the characteristics
of mapathons in Brno with their attendance and tried to find positive and negative factors
influencing the attendance rate. We analyzed the impact of:
• location,
• day of the week,
• month of the year,
• the possibility to come without a laptop and use a borrowed computer.
The number of participants was also analyzed using methods of descriptive statistics
(mean, median) and common types of graphs (line graph, bar chart). Because the
distribution did not assume a normal distribution (verified by the Shapiro–Wilk test), we
conducted the Mann–Whitney U test and Kruskal–Wallis H test to identify differences
in attendance. Results were displayed using common types of boxplot graphs, stacked
column graphs, bar graphs, and line graphs.
We were also interested in the portion of recurring participants in mapathons. One of the
key goals of organizing mapathons is to motivate contributors to attend mapathons repeatedly.
3. Results
The results are presented in line with the three research questions defined in this study.
Answers to each research question are then presented in sub-sections dealing with specific
aspects in detail.
3.1. The Motivation for Contributing to Humanitarian Mapping
Identifying the motivations of different humanitarian mappers was the primary goal
of the questionnaires. Respondents evaluated 21 statements that represented possible
Sustainability 2021, 13, 13991 12 of 24
motivators. We analyzed both the general motivations of all participants and differences in
motivation between various groups of participants.
3.1.1. The General Motivation for Contributing without Division into Groups
The mean and median values for each statement are presented in Table 2. A high score
(a value between 4 and 5) indicates that individuals considered the item to be a highly
significant motivator behind their contribution to humanitarian mapping projects.
The results in Table 2 and Figure 1 can be partially summarized as follows. The three
most important motivations are:
• to produce beneficial results (“I believe that my work yields significant results”),
• to feel a sense of solidarity with other people (“helping other people is important for me”),
• to achieve personal satisfaction (“I like making maps”).
In general, most of the primary motivations are those related to creating a greater
good. In contrast, self-rewarding aspects were considered the least important (“it helps me
to get the job I want,” or “I get money for it”).
3.1.2. Differences in Motivation between Various Groups of Participants
Participants were divided into groups according to their characteristics—age, gender,
education, mapping experience, field of employment or study, and status of employment.
Differences in the responses to the 21 given statements between these groups were statistically
analyzed. The differences in responses between groups based on age, gender,
education, and mapping experience were not statistically significant, as shown by the
conducted Mann–Whitney U tests. In contrast, statistically significant differences were
found in the case of groups based on the status and field of employment or study.
For status of employment, participants were divided into two groups: students and
non-students (employed, retired, children, and others). A difference between these groups
was found for the motivator “I like making maps” (Table 3, Figure 2). It was more important
for non-students (a median value of 5) than for students (a median value of 4).
For the field of employment or study, participants were divided into two groups:
geosciences (cartography, geoinformatics, geodesy, physical geography, human geography,
geology) and other fields. Significant differences were found for the motivators: “people
in my surroundings also contribute”, “it helps my professional development”, and “I need OSM
data for my work” (Table 4, Figure 3). All of these motivators were stronger for participants
connected to geosciences.
3.1.3. Reasons for Former Contributors to Have Ceased Participation
Our study aimed to identify the motivations of humanitarian mappers from the Czech
and Slovak Missing Maps community to participate in mapathons. On the other hand, we
also tried to discover the reasons why former contributors ceased their participation. In
the questionnaire, 5 of the 44 participants answered that their previous contribution had
been more than one year ago. They mentioned two reasons for this—a lack of time (3) and
the relatively large distance to the city where mapathons are held (2)—as indicated in their
answers below:
• “I have a small child (already the third). I have not contributed since its birth. When I
have time, I want to continue.”
• “Lack of time, but I would like to continue again.”
• “I rapidly reduced my mapping activities due to a higher workload.”
• “I moved outside Prague. I cannot go to mapathons.”
• “I live outside Prague. Maybe I will continue.”
Sustainability 2021, 13, 13991 13 of 24
Sustainability 2021, 13, 13991 13 of 25
Figure 1. Motivations for contributing—answers of all participants to the questionnaire.Figure 1. Motivations for contributing—answers of all participants to the questionnaire.
Sustainability 2021, 13, 13991 14 of 24
Table 3. Results of statistical analysis for groups based on the status of employment.
Motivator
Status of
Employment
Number of
Participants Median Mean Std Dev
Shapiro–Wilk
Test
Mann–Whitney U Test
p-Value U p-Value
I like
making maps
student 19 4.0 3.9 1.2 0.000
68.0 0.016
non-student 25 5.0 4.6 0.7 0.000
ducted Mann–Whitney U tests. In contrast, statistically significant differences were found
in the case of groups based on the status and field of employment or study.
For status of employment, participants were divided into two groups: students and
non-students (employed, retired, children, and others). A difference between these groups
was found for the motivator “I like making maps” (Table 3, Figure 2). It was more important
for non-students (a median value of 5) than for students (a median value of 4).
Table 3. Results of statistical analysis for groups based on the status of employment.
Motivator
Status of
Employment
Number of
Participants
Median Mean Std Dev
Shapiro–Wilk
Test
Mann–Whitney U
Test
p-Value U p-Value
I like making maps
student 19 4.0 3.9 1.2 0.000
68.0 0.016
non-student 25 5.0 4.6 0.7 0.000
Figure 2. Differences for the motivator “I like making maps” for groups of students and non-students.
For the field of employment or study, participants were divided into two groups:
geosciences (cartography, geoinformatics, geodesy, physical geography, human geography,
geology) and other fields. Significant differences were found for the motivators: “people
in my surroundings also contribute”, “it helps my professional development”, and “I need
OSM data for my work” (Table 4, Figure 3). All of these motivators were stronger for participants
connected to geosciences.
Figure 2. Differences for the motivator “I like making maps” for groups of students and non-students.
Table 4. Result of statistical analysis for groups based on field of employment or study.
Motivator
Status of
Employment
Number of
Participants Median Mean
Std
Dev
Shapiro–Wilk
Test
Mann–Whitney U Test
p-Value U p-Value
people in my
surroundings
also contribute
geosciences 19 2.0 2.5 1.1 0.022
144.5 0.028
other 25 1.0 1.8 1.2 0.000
it helps my
professional
development
geosciences 19 3.0 3.3 0.9 0.018
145.0 0.029
other 25 2.0 2.4 1.3 0.000
I need OSM data
for my work
geosciences 19 3.0 2.8 1.5 0.031
113.0 0.003
other 25 1.0 1.5 0.8 0.000
Sustainability 2021, 13, 13991 15 of 24
people in my surroundings
also con-
tribute
geosciences 19 2.0 2.5 1.1 0.022
144.5 0.028
other 25 1.0 1.8 1.2 0.000
it helps my professional
development
geosciences 19 3.0 3.3 0.9 0.018
145.0 0.029
other 25 2.0 2.4 1.3 0.000
I need OSM data for
my work
geosciences 19 3.0 2.8 1.5 0.031
113.0 0.003
other 25 1.0 1.5 0.8 0.000
Figure 3. Differences between groups of geosciences and other fields.
3.1.3. Reasons for Former Contributors to Have Ceased Participation
Our study aimed to identify the motivations of humanitarian mappers from the
Czech and Slovak Missing Maps community to participate in mapathons. On the other
hand, we also tried to discover the reasons why former contributors ceased their participation.
In the questionnaire, 5 of the 44 participants answered that their previous contribution
had been more than one year ago. They mentioned two reasons for this—a lack of
time (3) and the relatively large distance to the city where mapathons are held (2)—as
indicated in their answers below:
• “I have a small child (already the third). I have not contributed since its birth. When
I have time, I want to continue.”
• “Lack of time, but I would like to continue again.”
• “I rapidly reduced my mapping activities due to a higher workload.”
• “I moved outside Prague. I cannot go to mapathons.”
• “I live outside Prague. Maybe I will continue.”
Figure 3. Differences between groups of geosciences and other fields.
3.2. Characteristics of Mapathons and Recurring Participants
The second research question concerned the issue of how to attract as many participants
as possible. The attendance statistics of contributors to 18 mapathons organized in
Brno were used for this purpose.
The characteristics of the mapathons (month, day of the week, location, possibility
to come without a laptop and use a borrowed computer) and their respective attendance
statistics are presented in Table 5. Figure 4 shows changes in attendance as a line chart. The
influence of the mentioned characteristics was tested statistically.
Table 5. Attendance statistics of mapathons organized in Brno. The possibility to use a borrowed computer (i.e., to come
without a laptop) was only at mapathons held at Masaryk University.
Month and Year Weekday Location Attendees Attendees that Used Borrowed Computer
December 2016 Friday Masaryk University 21 3
March 2017 Tuesday Masaryk University 30 3
June 2017 Wednesday Masaryk University 7 1
October 2017 Wednesday Masaryk University 16 2
November 2017 Tuesday Masaryk University 8 1
February 2018 Wednesday Masaryk University 21 1
April 2018 Wednesday Masaryk University 17 0
June 2018 Tuesday Masaryk University 13 1
November 2018 Sunday OpenAlt conference 11 not available
December 2018 Wednesday Masaryk University 18 2
February 2019 Thursday Masaryk University 19 2
March 2019 Thursday CleverMaps company 47 not available
April 2019 Monday Kiwi.com company 20 not available
June 2019 Wednesday Kafara community center 11 not available
October 2019 Monday Red Hat company 15 not available
November 2019 Saturday OpenAlt conference 9 not available
December 2019 Wednesday Kiwi.com company 29 not available
February 2020 Thursday Masaryk University 23 5
Mean 18.6 1.9
Median 17.5 2.0
Sustainability 2021, 13, 13991 16 of 24
Sustainability 2021, 13, 13991 17 of 25
Figure 4. The number of attendees at mapathons organized in Brno according to month, year, location, and day of the
week.
The numbers of participants were highest at two mapathons organized by private
companies (e.g., Kiwi.com (Brno, Czech Republic), CleverMaps (Brno, Czech Republic)).
The third-highest number was for participants who attended one of the mapathons held
at the Masaryk University. However, it was only the second mapathon in Brno, so it was
a new experience for most participants. Our hypothesis was that new or non-traditional
locations of mapathons are the best attractors.
However, no significant statistical difference was found between individual types of
locations according to the results of the Kruskal–Wallis H test (H(2)) = 5.176, p-value =
0.075). Similarly, the influence of day of the week was found to be non-significant (H(4) =
3.720, p-value = 0.445).
On the other hand, we found statistically significant differences between the months
of the year (H(6) = 15.307; p-value = 0.018). A comparison of the average numbers of participants
in mapathons in individual months is shown in Table 6 and Figure 5. The lowest
numbers are clearly in June and November.
Table 6. Mean and median of the numbers of attendees in mapathons held in particular months.
Month Number of Mapathons Number of Participants Mean Median
February 3 63 21.0 21.0
March 2 77 38.5 38.5
April 2 37 18.5 18.5
June 3 31 10.3 11.0
October 2 31 15.5 15.5
November 3 28 9.3 9.0
December 3 68 22.7 21.0
Total 18 335 18.6 17.5
0
5
10
15
20
25
30
35
40
45
50 Dec2016MUFr
Mar2017MUTu
Jun2017MUWe
Oct2017MUWe
Nov2017MUTu
Feb2018MUWe
Apr2018MUWe
Jun2018MUTu
Nov2018OpenAltSu
Dec2018MUWe
Feb2019MUTh
Mar2019CleverMapsTh
Apr2019Kiwi.comMo
Jun2019KafaraWe
Oct2019RedHatMo
Nov2019OpenAltSa
Dec2019Kiwi.comWe
Feb2020MUTh
Numberofparticipants
Figure 4. The number of attendees at mapathons organized in Brno according to month, year, location, and day of the week.
The numbers of participants were highest at two mapathons organized by private
companies (e.g., Kiwi.com (Brno, Czech Republic), CleverMaps (Brno, Czech Republic)).
The third-highest number was for participants who attended one of the mapathons held
at the Masaryk University. However, it was only the second mapathon in Brno, so it was
a new experience for most participants. Our hypothesis was that new or non-traditional
locations of mapathons are the best attractors.
However, no significant statistical difference was found between individual types of locations
according to the results of the Kruskal–Wallis H test (H(2)) = 5.176, p-value = 0.075).
Similarly, the influence of day of the week was found to be non-significant (H(4) = 3.720,
p-value = 0.445).
On the other hand, we found statistically significant differences between the months
of the year (H(6) = 15.307; p-value = 0.018). A comparison of the average numbers of
participants in mapathons in individual months is shown in Table 6 and Figure 5. The
lowest numbers are clearly in June and November.
The effect of the possibility of participants to come without their own laptop was
analyzed using the Mann–Whitney U test, but a statistically significant difference was not
found (computer borrow: U = 37.0, p-value = 0.928).
The number of recurring participants was another focus of this particular research subquestion.
The total number of registered participants that attended at least one mapathon
in Brno was 181. Figure 6 shows the breakdown of how many mapathons the 181 registered
participants visited in Brno. A total of 121 contributors came to only one mapathon, while
60 participants (32.8%) attended at least two. Only five mappers came to more than
five mapathons.
Sustainability 2021, 13, 13991 17 of 24
Table 6. Mean and median of the numbers of attendees in mapathons held in particular months.
Month Number of Mapathons Number of Participants Mean Median
February 3 63 21.0 21.0
March 2 77 38.5 38.5
April 2 37 18.5 18.5
June 3 31 10.3 11.0
October 2 31 15.5 15.5
November 3 28 9.3 9.0
December 3 68 22.7 21.0
Total 18 335 18.6 17.5
Sustainability 2021, 13, 13991 18 of 25
Figure 5. Differences in numbers of attendees at mapathons held in particular months.
The effect of the possibility of participants to come without their own laptop was
analyzed using the Mann–Whitney U test, but a statistically significant difference was not
found (computer borrow: U = 37.0, p-value = 0.928).
The number of recurring participants was another focus of this particular research
sub-question. The total number of registered participants that attended at least one mapathon
in Brno was 181. Figure 6 shows the breakdown of how many mapathons the 181
registered participants visited in Brno. A total of 121 contributors came to only one mapathon,
while 60 participants (32.8%) attended at least two. Only five mappers came to more
than five mapathons.
Figure 5. Differences in numbers of attendees at mapathons held in particular months.
3.3. Self-Assessment of Humanitarian Mappers
The last research question of the conducted study elicited the self-assessment of
contributors to humanitarian mapping. A particular sub-question concerned the subjective
evaluation of their contributions (underestimations or overestimations).
Data were obtained from the conducted questionnaire. The total number of each
respondent’s edits from their profile on the Missing Maps page and their evaluation of
their overall contribution to the OSM project were relativized on a scale from 1 (minimal
contribution) to 10 (maximal contribution). Spearman’s coefficient was used to calculate the
correlation between the number of a participant’s edits and the participant’s evaluation of
his/her contribution to OSM. Statistical analysis showed a significant correlation (r = 0.754,
p = 0.000) between the number of edits and self-assessment. That is, the self-assessment of
participants was generally very accurate.
Sustainability 2021, 13, 13991 18 of 24
found (computer borrow: U = 37.0, p-value = 0.928).
The number of recurring participants was another focus of this particular research
sub-question. The total number of registered participants that attended at least one mapathon
in Brno was 181. Figure 6 shows the breakdown of how many mapathons the 181
registered participants visited in Brno. A total of 121 contributors came to only one mapathon,
while 60 participants (32.8%) attended at least two. Only five mappers came to more
than five mapathons.
Figure 6. Participants of mapathons in Brno by the number of mapathons they attended.Figure 6. Participants of mapathons in Brno by the number of mapathons they attended.
4. Discussion
Similarly to the Results section, this section is also structured in line with the three
research questions identified at the beginning of this study.
4.1. The Motivation for Contributing to Humanitarian Mapping
The analysis of the overall motivation of contributors without division into groups
showed six strong motivators with a mean value on the motivation scale higher than
4. Three of them—”I believe that my work yields significant results”, “helping other people
is important to me”, and “I feel better and more satisfied with myself”—are connected with
altruism. Two of the other strong motivators—”I like making maps” and “I believe that
digital maps should be accessible to everyone for free”—are directly connected with the OSM
project. The remaining strong motivator—”the community of volunteers around humanitarian
mapping is important to me”—demonstrates the strength of networking within the OSM and
humanitarian mapping communities.
Such a statement corresponds with the study by Budhathoki and Haythornthwaite [68],
which found that the importance of community, the goals of the OSM project, and general
altruism were the strongest motivators. Budhathoki and Haythornthwaite [68] also note
that an important aspect of feedback highlighted in the OSM VGI case is the visual appeal
of maps and visualizations. The analysis of questionnaire results indicated that the overall
motivation is a mixture of various reasons. The same findings are also reported in [71].
The analysis of differences in motivation between various groups of participants
found only a few statistically significant differences. Only employment status influenced
one of the strong motivators mentioned above. Non-students assessed the motivator “I like
making maps” as more important than students. We have no exact hypothesis about this
result. Interest in maps is described as a communitywide motivator for various groups of
mappers [68]. It is possible that students are also interested in maps, but they also prefer
other motivators, so “I like making maps” is not so important for their group.
An interest in geography and a love of maps are, of course, communitywide motivators,
and both casual and serious mappers are well motivated by an overall interest
in mapping and geography and particularly by the possibility of contributing to local
geography [68].
Sustainability 2021, 13, 13991 19 of 24
Differences in three motivators were found after dividing participants according
to fields of study or employment. Participants connected to geosciences assessed the
motivators “people in my surroundings also contribute”, “it helps my professional development”,
and “I need OSM data for my work” as stronger than participants connected to other fields.
However, none of these motivators was generally strong. This agrees with [68], where
more differences were found for items on the lower end of the motivation scale.
No significant differences were found between groups based on gender, age, mapping
experience, or level of education. Our results are in line with [34,67], which found that
there was only a small difference in motivation between males and females. However,
there are differences between our results and [68] when speaking about the motivation of
more and less experienced contributors. Budhathoki and Haythornthwaite [68] noted that
serious mappers are more oriented towards the community while casual mappers are more
oriented towards the overall goals of open-source projects.
We asked former humanitarian mappers why they ended their participation. They
mentioned two types of reasons—lack of time and long distances to the cities with mapathons.
A proportion of them expressed the hope that their humanitarian mapping would
begin again.
Lack of time was also the main reason for the ceasing of contributions in [67]. In
contrast to our study, none of the related studies found that a large distance to the cities
where mapathons are held was mentioned as a reason for the ending of contributions.
Humanitarian mapping is not limited to mapathons. In fact, mappers are also encouraged
to map alone, independently of other mappers—e.g., from home. This indicates that for
many humanitarian mappers, the specific atmosphere of a mapathon is important, where
a number of volunteers work together on the same task. This can be connected with
the abovementioned strong position of the motivator “the community of volunteers around
humanitarian mapping is important to me”. This indicates that expanding the group of cities
where mapathons take place could help to retain experienced contributors and expand
the community.
4.2. Characteristics of Mapathons and Recurring Participants
The analysis of attendance statistics from Brno mapathons found only one characteristic
of a mapathon with a statistically significant influence on attendance—the month of the
year. Mapathons in Brno are usually held from October to December and from February to
June—during the months of teaching at the university. It is clear that mapathons organized
in June (when semester exams and state exams are held) suffer from lower attendance
because students either have a higher workload or have already left for the holidays. An
anomaly is the weaker mapathon attendance in November. November mapathons are
organized during the teaching season at the university; however, they are organized at the
annual IT conference OpenAlt [75] attended by IT professionals, not by the general public
or the usual participants of Brno mapathons.
No other characteristics of a mapathon—location, day of the week, or the possibility to
come without a laptop—proved to be significant attractors. This could be due to the small
number of data collected for analysis. It is also possible that in the case of some mapathons,
different influences had opposite effects—e.g., an attractive location was negated by an
unattractive day of the week. This analysis needs to be repeated when attendance statistics
for more mapathons from Czechia and Slovakia are available.
Although it is recommended in the mapathon organization manual [23,27] to provide
some extra laptops or computers for participants, most of the mapathons in Czechia
and worldwide require participants to bring their own laptops. Mapathons held at the
Department of Geography at Masaryk University offer computers to participants who do
not have their own laptop (or whose laptop does not work properly). The effect of such
an offer has not been analyzed before. Therefore, within this study, we tried to determine
whether it had some positive effect on attendance. It was found, however, that there was
no significant advantage to mapathons offering this possibility. Nevertheless, when this
Sustainability 2021, 13, 13991 20 of 24
possibility existed, it was used by 1–3 participants. Therefore, though the offer to borrow
computers did not influence the number of participants, it appeared to be a welcome
service for some. We will therefore continue to offer this option at mapathons held at the
Department of Geography.
All the organizers of mapathons try to attract recurring participants. One third of
the mappers (60 out of 181) that attended at least one Brno mapathon also visited at least
one other mapathon. This is in line with findings in [25], where 31% of participants were
recurring. However, in [26], 50% of monthly mapathon attendees were recurrent visitors.
In [28], it is even reported that 60% of attendees were reattending visitors, though this figure
was probably influenced by the fact that participants were students credited for attendance.
The authors of this study are also the organizers of mapathons in Brno. Their longterm
goal is to attract a proportion of repeat participants that is significantly greater than
the current figure of around 30%. A possible partial explanation for this relatively low
fraction is the location of some Brno mapathons in private companies. Dittus et al. [26]
emphasized that “Corporate mapathons had the lowest newcomer retention, although
their event format was comparable to other mapathons.” However, this problem must be
examined in a broader context—e.g., using attendance statistics of mapathons in other
cities in Czechia and Slovakia.
4.3. Self-Assessment of Humanitarian Mappers
One of the most common free-text comments received in questionnaires emphasized
that self-assessment is difficult for participants. Such a statement contrasts with the
statistical evaluation of participants’ self-assessment. According to the results of this study,
statistical analysis confirmed a significant correlation between the number of edits and
participants’ self-assessment. As far as the authors are aware, no similar study has so far
been published about the overconfidence or underconfidence of mapathon participants.
5. Conclusions and Future Plans
Missing Maps is a humanitarian mapping project that aims to map the most vulnerable
places in the developing world using OSM. Created data are used to better respond to
crises, achieve SDGs, and monitor their progress.
The main motivation behind the presented research is to expand the active Czech
and Slovak community of the humanitarian mapping Missing Map project, to attract new
mappers, and to ensure greater attendance at mapathons. We want to discover what
attracts contributors from Czechia and Slovakia to participate in humanitarian mapping
and to attend mapathons and to discover the reasons why former contributors sometimes
cease to contribute. Subsumed in this is the additional goal of reducing the departure of
experienced mappers. Overall, these motivations and goals should increase the chances of
creating more and better data. Data from a questionnaire and attendance statistics were
analyzed to answer the three defined research questions. The following statements can
be made:
(A) What are the motivations of different contributors in the Missing Maps community
in Czechia and Slovakia?
The importance of community and general altruism are the strongest motivators
for all mappers. They are the keys to the success of the (mapping) project, irrespective
of differences in gender, age, level of education, or mapping experience. Students are
the only exception in that they mention the strong motivator “I like making maps” less
often in comparison to other groups. The only other significant differences in motivation
were found for contributors connected to the geosciences, but they were related to less
important motivators.
Lack of time and long distances to the cities with mapathons were two mentioned
reasons why some contributors ended their participation. Expanding the group of cities
where mapathons take place could significantly retain experienced contributors and expand
the community.
Sustainability 2021, 13, 13991 21 of 24
(B) How can a mapathon be set up to attract as many participants as possible?
Statistical analysis found no significant influence of location, day of the week, or
possibility to come without a laptop. Only the month of the mapathon had a significant
influence, with the weakest attendance in June (due to the end of the university year) and
November (due to the organization of a mapathon within the IT conference).
(C) How do contributors to humanitarian mapping subjectively evaluate their contributions?
Do they underestimate or overestimate the importance of their results?
Humanitarian mappers evaluate their overall contribution to OSM very realistically.
In general, self-assessments were neither over-optimistic nor over-pessimistic.
This paper communicates our preliminary results after the first attempt at data collection
from a questionnaire. The number of collected questionnaires was too low for
representative results; however, analyses with an identical scope are planned for the upcoming
years. We would like to collect new data using the same questionnaire every year
to observe changes over time. Searching for the characteristics of the “ideal” mapathon
will be repeated after collecting data from a larger number of mapathons from Czechia
and Slovakia.
Like most human activity, humanitarian mapping and the organization of mapathons
were severely hit by the COVID-19 pandemic in 2020 and 2021. Most of the collective events,
including mapathons, moved to online environments. Accordingly, the organization and
specificities of online mapathons have become a new object of research in the humanitarian
mapping community. We plan to follow this direction and compare the characteristics,
attendance, and results of classic and online mapathons organized by Czech and Slovak
humanitarian mapping communities in the future.
Author Contributions: Conceptualization, R.Š., J.T. and T. ˇR.; methodology, R.Š. and L.H.; validation:
R.Š.; formal analysis, R.Š., L.H. and J.T.; investigation, J.T. and K.T.; resources, K.T. and L.H.; data
curation, L.H. and K.T.; writing—original draft, R.Š., J.T. and K.T.; writing—review and editing, L.H.
and T. ˇR.; supervision, T. ˇR.; project administration, T. ˇR.; funding acquisition, J.T., L.H. and T. ˇR. All
authors have read and agreed to the published version of the manuscript.
Funding: This paper is part of a project that has received funding from the European Union’s Horizon
2020 research and innovation programme under grant agreement No. 818346 titled “Sino–EU Soil
Observatory for intelligent Land Use Management” (SIEUSOIL).
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.
Data Availability Statement: Data are not publicly available, though the data may be made available
on request from the corresponding author.
Acknowledgments: Our team thanks all participants and organizers of Brno mapathons, the
Missing Maps project community in Czechia and Slovakia, and all contributors to humanitarian
mapping worldwide.
Conflicts of Interest: The authors declare no conflict of interest.
References
1. The 17 Goals. Available online: https://sdgs.un.org/goals (accessed on 2 August 2021).
2. Transforming Our World: The 2030 Agenda for Sustainable Development. Available online: https://sdgs.un.org/2030agenda
(accessed on 2 August 2021).
3. OpenStreetMap. Available online: https://www.openstreetmap.org/ (accessed on 1 May 2021).
4. Viana, C.M.; Encalada, L.; Rocha, J. The Value of OpenStreetMap Historical Contributions as a Source of Sampling Data for
Multi-Temporal Land Use/Cover Maps. ISPRS Int. J. Geo-Inf. 2019, 8, 116. [CrossRef]
5. Jonietz, D.; Zipf, A. Defining Fitness-for-Use for Crowdsourced Points of Interest (POI). ISPRS Int. J. Geo-Inf. 2016, 5, 149.
[CrossRef]
6. Muttaqien, B.I.; Ostermann, F.O.; Lemmens, R.L.G. Modeling aggregated expertise of user contributions to assess the credibility
of OpenStreetMap features. Trans. GIS 2018, 22, 823–841. [CrossRef]
Sustainability 2021, 13, 13991 22 of 24
7. Yang, S.; Shen, J.; Koneˇcný, M.; Wang, Y.; Štampach, R. Study on the Spatial Heterogeneity of the POI Quality in OpenStreetMap.
In Proceedings of the 7th International Conference on Cartography and GIS, Sozopol, Bulgaria, 18–23 June 2018; Bandrova, T., Koneˇcný,
M., Eds.; Bulgarian Cartographic Association: Sofia, Bulgaria, 2018.
8. Touya, G.; Antoniou, V.; Olteanu-Raimond, A.-M.; Van Damme, M.-D. Assessing Crowdsourced POI Quality: Combining
Methods Based on Reference Data, History, and Spatial Relations. ISPRS Int. J. Geo-Inf. 2017, 6, 80. [CrossRef]
9. Kankanamge, N.; Yigitcanlar, R.; Goonetilleke, A.; Kamruzzaman, M. Can volunteer crowdsourcing reduce disaster risk? A
systematic review of the literature. Int. J. Disaster Risk Reduct. 2019, 35, 101097. [CrossRef]
10. Koneˇcný, M.; Reinhardt, W. Early warning and disaster management: The importance of geographic information (Part B). Int. J.
Digit. Earth 2010, 3, 313–315. [CrossRef]
11. Goodchild, M. Citizens as sensors: The world of volunteered geography. GeoJournal 2007, 69, 211–221. [CrossRef]
12. Humanitarian OpenStreetMap Team. Available online: https://www.hotosm.org/ (accessed on 10 January 2021).
13. What We Do. Available online: https://www.hotosm.org/what-we-do (accessed on 2 August 2021).
14. A Practical Guide to Launching and Growing Open Mapping Initiatives at the National and Local Levels. Available online:
https://documents1.worldbank.org/curated/en/967511563521548873/pdf/Open-Mapping-for-the-SDGs-A-Practical-Guide-toLaunching-and-Growing-Open-Mapping-Initiatives-at-the-National-and-Local-Levels.pdf
(accessed on 2 August 2021).
15. Open Mapping for the SDGs. Available online: https://sdgs.hotosm.org/ (accessed on 30 October 2021).
16. Solís, P.; McCusker, B.; Menkiti, N.; Cowan, N.; Blevins, C. Engaging global youth in participatory spatial data creation for the
UN sustainable development goals: The case of open mapping for malaria prevention. Appl. Geogr. 2018, 98, 143–155. [CrossRef]
17. YouthMappers. Available online: https://www.youthmappers.org/ (accessed on 10 January 2021).
18. Solís, P.; Rajagopalan, S.; Villa, L.; Mohiuddin, M.B.; Boateng, E.; Wavamunno, N.S.; Valencia, M.F.P. Digital humanitarians for the
Sustainable Development Goals: YouthMappers as a hybrid movement. J. Geogr. High. Educ. 2020. [CrossRef]
19. Forni, M.; Haack, J.; Soden, R.; York, D.; Sommerville, R.; Deparday, V. Open Data for Resilience Initiative: Planning and Open Cities
Mapping Project, World Bank, Global Facility for Disaster Reduction and Recovery; World Bank: Washington, DC, USA, 2014; 96p.
20. One Map Myanmar and Phandeeyar. Available online: https://www.missingmaps.org/blog/2018/09/24/mapping-inmyanmar/
(accessed on 15 November 2021).
21. Burundi Anti-Malaria Campaign: Covering the Gap—A Year of Blogs—January 2020. Available online: https://www.
missingmaps.org/blog/2020/01/29/a-year-of-blogs/ (accessed on 15 November 2021).
22. Missing Maps—Putting the World’s Vulnerable People on the Map. Available online: https://www.missingmaps.org/ (accessed
on 10 January 2021).
23. Hosting a Mapathon. Available online: https://www.missingmaps.org/host/#Materials (accessed on 5 April 2021).
24. Coetzee, S.; Minghini, M.; Solis, P.; Rautenbach, V.; Green, C. Towards understanding the impact of mapathons—Reflecting on
YouthMappers experiences. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. 2018, XLII-4/W8, 35–42. [CrossRef]
25. Hristova, D.; Quattrone, G.; Mashhadi, A.; Capra, L. The Life of the Party: Impact of Social Mapping in OpenStreetMap; ICWSM:
Atlanta, GA, USA, 2013; pp. 234–243.
26. Dittus, M.; Quattrone, G.; Capra, L. Social Contribution Settings and Newcomer Retention in Humanitarian Crowd Mapping. In
Proceedings of the 8th International Conference, SocInfo 2016, Bellevue, WA, USA, 11–14 November 2016; Spiro, E., Ahn, Y.-Y., Eds.;
Springer: Cham, Switzerland, 2016; Part II; pp. 179–193. [CrossRef]
27. How to Host a Mapathon. Available online: https://www.missingmaps.org/assets/downloads/mapathon-materials/english/
How_to_Host_a_Mapathon_EN.pdf (accessed on 6 April 2021).
28. Green, C.; Rautenbach, V.; Coetzee, S. Evaluating student motivation and productivity during mapathons. Int. Arch. Photogramm.
Remote. Sens. Spat. Inf. Sci. 2019, XLII-4/W14, 85–91. [CrossRef]
29. Trojan, J.; Schade, S.; Lemmens, R.; Frantál, B. Citizen science as a new approach in Geography and beyond: Review and
reflections. Morav. Geogr. Rep. 2019, 27, 254–264. [CrossRef]
30. Kerski, J.J. Geo-awareness, geo-enablement, geotechnologies, citizen science, and storytelling: Geography on the world stage.
Geogr. Compass 2015, 9, 14–26. [CrossRef]
31. Turner, A. Introduction to Neo-Geography; O’Reilly Media, Inc.: Sebastopol, CA, USA, 2006.
32. Wilson, M.W.; Graham, M. Situating Neogeography. Environ. Plan. A Econ. Space 2013, 45, 3–9. [CrossRef]
33. West, S.E.; Büker, P.; Ashmore, M.; Njoroge, G.; Welden, N.; Muhoza, C.; Osano, P.; Makau, J.; Njoroge, P.; Apondo, W.
Particulate matter pollution in an informal settlement in Nairobi: Using citizen science to make the invisible visible. Appl. Geogr.
2020, 114, 102133. [CrossRef]
34. Alender, B. Understanding volunteer motivations to participate in citizen science projects: A deeper look at water quality
monitoring. J. Sci. Commun. 2016, 15, A04. [CrossRef]
35. Bonney, R.; Cooper, C.B.; Dickinson, J.; Kelling, S.; Phillips, T.; Rosenberg, K.V.; Shirk, J. Citizen science: A developing tool for
expanding science knowledge and scientific literacy. BioScience 2009, 59, 977–984. [CrossRef]
36. Dickinson, J.L.; Shirk, J.; Bonter, D.; Bonney, R.; Crain, R.L.; Martin, J.; Phillips, T.; Purcell, K. The current state of citizen science as
a tool for ecological research and public engagement. Front. Ecol. Environ. 2012, 10, 291–297. [CrossRef]
37. Zhang, G. Spatial and Temporal Patterns in Volunteer Data Contribution Activities: A Case Study of eBird. ISPRS Int. J. Geo-Inf.
2020, 9, 597. [CrossRef]
Sustainability 2021, 13, 13991 23 of 24
38. Franzen, M.; Kloetzer, L.; Ponti, M.; Trojan, J.; Vicens, J. Machine Learning in Citizen Science: Promises and Implications. In The
Science of Citizen Science, 1st ed.; Vohland, K., Land-Zandstra, A., Ceccaroni, L., Lemmens, R., Perelló, J., Ponti, M., Samson, R.,
Wagenknecht, K., Eds.; Springer: Cham, Switzerland, 2021. [CrossRef]
39. Battisti, C.; Cerfolli, F. From Citizen Science to Citizen Management: Suggestions for a pervasive fine-grained and operational
approach to biodiversity conservation. Isr. J. Ecol. Evol. 2021. in press. [CrossRef]
40. Battisti, C.; Poeta, G.; Romiti, F.; Picciolo, L. Small Environmental Actions Need of Problem-Solving Approach: Applying Project
Management Tools to Beach Litter Clean-Ups. Environments 2020, 7, 87. [CrossRef]
41. Taft-Morales, M.; Margesson, R. Haiti earthquake: Crisis and response. Curr. Politics Econ. South Cent. Am. 2011, 4, 1–67.
42. Reznik, T.; Horakova, B.; Szturc, R. Geographic Information for Command and Control Systems Demonstration of Emergency
Support System. In Intelligent Systems for Crisis Management: Geo-Information for Disaster Management (GI4DM) 2012, 1st ed.;
Zlatanova, S., Peters, R., Dilo, A., Scholten, H., Eds.; Springer: Berlin, Germany, 2013; pp. 263–275.
43. Reznik, T.; Horakova, B.; Szturc, R. Advanced methods of cell phone localization for crisis and emergency management
applications. Int. J. Digit. Earth 2015, 8, 259–272. [CrossRef]
44. Arsanjani, J.; Bakillah, M. Understanding the potential relationship between the socio-economic variables and contributions to
OpenStreetMap. Int. J. Digit. Earth 2015, 8, 861–876. [CrossRef]
45. Sui, D.Z.; Goodchild, M.F.; Elwood, S. Volunteered Geographic Information, the Exaflood, and the Growing Digital Divide.
In Crowdsourcing Geographic Knowledge: Volunteered Geographic Information (VGI) in Theory and Practice; Sui, D.Z., Elwood, S.,
Goodchild, M.F., Eds.; Springer: Dordrecht, The Netherlands, 2013; pp. 1–12. [CrossRef]
46. Bandrova, T.L.; Koneˇcný, M.; Yotova, A. Cartography development and challenges on the basis of Big Data. In Proceedings of the
5th International Conference on Cartography and GIS, Riviera, Bulgaria, 15–20 June 2014; Bandrova, T., Koneˇcný, M., Eds.; Bulgarian
Cartographic Association: Sofia, Bulgaria, 2014; pp. 164–173.
47. Haklay, M. Citizen Science and Volunteered Geographic Information: Overview and Typology of Participation. In Crowdsourcing
Geographic Knowledge: Volunteered Geographic Information (VGI) in Theory and Practice; Sui, D.Z., Elwood, S., Goodchild, M.F., Eds.;
Springer: Dordrecht, The Netherlands, 2013; pp. 105–122. [CrossRef]
48. Duží, B.; Osman, R.; Lehejˇcek, J.; Nováková, E.; Taraba, P.; Trojan, J. Exploring citizen science in post-socialist space: Uncovering
its hidden character in the Czech Republic. Morav. Geogr. Rep. 2019, 27, 241–253. [CrossRef]
49. Herfort, B.; Li, H.; Fendrich, S.; Lautenbach, S.; Zipf, A. Mapping human settlements with higher accuracy and less volunteer
efforts by combining crowdsourcing and deep learning. Remote Sens. 2019, 11, 1799. [CrossRef]
50. Costa Fonte, C.; Fritz, S.; Olteanu-Raimond, A.M.; Antoniou, V.; Foody, G.; Mooney, P.; See, L. Mapping and the Citizen Sensor;
Ubiquity Press: London, UK, 2017; 398p.
51. Vohland, K.; Land-Zandstra, A.; Ceccaroni, L.; Lemmens, R.; Perelló, J.; Ponti, M.; Wagenknecht, K. The Science of Citizen Science;
Springer: Cham, Switzerland, 2021; 529p.
52. Fritz, S.; See, L.; Carlson, T.; Haklay, M.; Oliver, J.L.; Fraisl, D.; Mondardini, R.; Brocklehurst, M.; Shanley, L.A.; Schade, S.; et al.
Citizen science and the United Nations Sustainable Development Goals. Nat. Sustain. 2019, 2, 922–930. [CrossRef]
53. Knowledge for Change: A Decade of Citizen Science (2020–2030) in Support of the SDGs. Available online: https://www.cs-sdgconference.berlin/en/
(accessed on 16 November 2021).
54. Fraisl, D.; Campbell, J.; See, L.; Wehn, U.; Wardlaw, J.; Gold, M.; Moorthy, I.; Arias, R.; Piera, J.; Oliver, J.L.; et al. Mapping citizen
science contributions to the UN Sustainable Development Goals. Sustain. Sci. 2020, 15, 1735–1751. [CrossRef]
55. Meier, P. Digital Humanitarians: How Big Data Is Changing the Face of Humanitarian Response, 1st ed.; CRC Press: Boca Raton, FL,
USA, 2015; 259p.
56. Clark, N.; Guiffault, F. Seeing through the clouds: Processes and challenges for sharing geospatial data for disaster management
in Haiti. Int. J. Disaster Risk Reduct. 2018, 28, 258–270. [CrossRef]
57. Koneˇcný, M.; Bandrova, T.; Kubíˇcek, P.; Stachoˇn, Z.; Štampach, R.; Shen, J.; Rotanova, I.; Brodský, J.; Špulák, P. Strategies of
Disaster Risk Reduction on the Background on U.N. GGIM and Digital Belt and Road Efforts. In Proceedings of the 8th International
Conference on Cartography and GIS, Nessebar, Bulgaria, 15–20 June 2020; Bandrova, T., Koneˇcný, M., Marinova, S., Eds.; Bulgarian
Cartographic Association: Sofia, Bulgaria, 2020; Volume 1, 17p, Available online: https://iccgis2020.cartography-gis.com/
(accessed on 16 November 2021).
58. Ebrahim, M.; Minghini, M.; Molinari, M.E.; Torrebruno, A. MiniMapathon—Mapping the world at 10 years old. In Proceedings
of the EDULEARN16 Conference, Barcelona, Spain, 4–6 July 2016; pp. 4200–4208.
59. Wirnitzer, J. Czech Volunteers Map Slums around the World ( ˇCeští Dobrovolníci Mapují Chudinské ˇCtvrti ve Svˇetˇe). Hospodáˇrské
Noviny, 2 July 2018. (In Czech)
60. Béland, P. OSM Quality Mapping: Metrics to Monitor Buildings Outbounds. In State of the Map 2019. Available online:
https://2019.stateofthemap.org/sessions/3BZCXA/ (accessed on 23 November 2021).
61. Reinmuth, M.; Herfort, B.; Stier, J.; Klerings, A. Evolution of Humanitarian Mapping within the OpenStreetMap Community. In
State of the Map 2020. Available online: https://2020.stateofthemap.org/sessions/SNEDXL/ (accessed on 23 November 2021).
62. Nile, E.; Maron, M.; Vyncke, J.; Firth, R.; Nassozi, S.; Gibb, M. Mapathons, Validation & Mapping Quality—A Debate. In HOT
Summit 2019. Available online: https://www.youtube.com/watch?v=zWW0i-V4lgw&list=PLb9506_-6FMFeUJr8cbOZ3aE7
Npw3-Ifu&index=15&t=0s (accessed on 23 November 2021).
Sustainability 2021, 13, 13991 24 of 24
63. Ramm, F. There Might Have been a Misunderstanding . . . In State of the Map 2020. Available online: https://2020.stateofthemap.
org/sessions/DYXWDC/ (accessed on 23 November 2021).
64. Menard, S.; Chavent, N. Mapathon, Mapathon, Mapathon! In State of the Map 2019. Available online: https://2019.stateofthemap.
org/sessions/GQ3AAF/ (accessed on 23 November 2021).
65. Schott, M.; Grinberger, A.Y.; Lautenbach, S.; Zipf, A. The Impact of Community Happenings in OpenStreetMap—Establishing a
Framework for Online Community Member Activity Analyses. ISPRS Int. J. Geo-Inf. 2021, 10, 164. [CrossRef]
66. Loftian, M.; Ingensand, J.; Brovelli, M.A. A Framework for Classifying Participant Motivation that Considers the Typology of
Citizen Science Projects. ISPRS Int. J. Geo-Inf. 2020, 9, 704. [CrossRef]
67. Schmidt, M.; Klettner, S. Gender and Experience-Related Motivators for Contributing to OpenStreetMap. In Proceedings of the
16th AGILE International Conference on GIS, Leuven, Belgium, 14–17 May 2013.
68. Budhathoki, N.M.; Haythornthwaite, C. Motivation for Open Collaboration: Crowd and Community Models and the Case of
OpenStreetMap. Am. Behav. Sci. 2012, 57, 548–575. [CrossRef]
69. Gómez-Barrón, J.-P.; Manso-Callejo, M.-A.; Alcarria, R. Needs, drivers, participants, and engagement actions: A framework for
motivating contributions to volunteered geographic information systems. J. Geogr. Syst. 2019, 21, 5–41. [CrossRef]
70. Stachoˇn, Z.; Šašinka, ˇC.; ˇCenˇek, J.; Štˇerba, Z.; Angsuesser, S.; Fabrikant, S.I.; Štampach, R.; Morong, K. Cross-cultural differences
in figure-ground perception of cartographic stimuli. Cartogr. Geogr. Inf. Sci. 2018, 46, 82–94. [CrossRef]
71. Clary, E.G.; Snyder, M. The Motivations to Volunteer: Theoretical and Practical Considerations. Curr. Dir. Psychol. Sci.
1999, 8, 156–159. [CrossRef]
72. Show Me the Way. Available online: http://osmlab.github.io/show-me-the-way/ (accessed on 11 January 2021).
73. Trello—Missing Maps CZ & SK. Available online: https://trello.com/b/8Vo5QWU6/missing-maps-cz-sk (accessed on 3 May
2021). (In Czech)
74. User Profile on the Missing Maps. Available online: https://www.missingmaps.org/users/#/ (accessed on 2 August 2021).
75. OpenAlt Conference. Available online: https://www.openalt.cz/ (accessed on 11 January 2021). (In Czech)