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This study presents results from an on-going social map service pilot that supports a national mapping agency (NMA) in data collection. Results from the pilot show that a VGI map service benefits both citizens and the NMA; the data quality is high enough to suit the needs of an NMA; citizens obtain a means to contribute and be involved in ameliorating maps. The social map service works also as a citizen-to-citizen communication channel as all the contributions are immediately visible to all users. Based on the results of this study, VGI should be further integrated with NMA processes in the future. One way of improving the integration are via services offered to both citizens and NMA employees that borrow features from existing social network services but also from popular games. Commenting, voting and gamification elements can be integrated with the VGI services to benefit both citizens and NMAs. Due to the numerous challenges of VGI the European national mapping agencies involvement in using citizens as data collectors is low. It is, however, within the NMA’s grasp to develop the role of VGI in NMA processes further and to make VGI collection fun.
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Journal of Geographical Systems (2019) 21:43–59
1 3
Map Gretel: social map service supporting anational
mapping agency indata collection
MikkoRönneberg1 · MariLaakso1· TapaniSarjakoski1
Received: 29 September 2017 / Accepted: 6 December 2018 / Published online: 18 December 2018
© The Author(s) 2018
This study presents results from an on-going social map service pilot that supports
a national mapping agency (NMA) in data collection. Results from the pilot show
that a VGI map service benefits both citizens and the NMA; the data quality is high
enough to suit the needs of an NMA; citizens obtain a means to contribute and be
involved in ameliorating maps. The social map service works also as a citizen-to-
citizen communication channel as all the contributions are immediately visible to
all users. Based on the results of this study, VGI should be further integrated with
NMA processes in the future. One way of improving the integration are via services
offered to both citizens and NMA employees that borrow features from existing
social network services but also from popular games. Commenting, voting and gam-
ification elements can be integrated with the VGI services to benefit both citizens
and NMAs. Due to the numerous challenges of VGI the European national map-
ping agencies involvement in using citizens as data collectors is low. It is, however,
within the NMA’s grasp to develop the role of VGI in NMA processes further and to
make VGI collection fun.
Keywords Volunteered geographic information· National mapping agency· Social
map service· Crowdsourcing
JEL Classifcation C80· C88
* Mikko Rönneberg
Mari Laakso
Tapani Sarjakoski
1 Finnish Geospatial Research Institute FGI, Masala, Finland
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M.Rönneberg et al.
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1 Introduction
The rise and success of different volunteered geographic information (VGI)
activities (Goodchild 2007), together with increasing technological advances,
have prompted national mapping agencies (NMAs) to consider the possibilities of
using crowdsourced geographic information in topographic data collection. The
power of citizens is at its best when it comes to topographic data features that
are difficult to map with remote sensing techniques (such as forest paths hidden
by trees) or that require local knowledge (such as place names or any other fea-
tures of interest to people). In some cases, the use of VGI is the best option for
mapping temporal changes. However, NMAs have been reluctant to get involved
with VGI due to numerous challenges such as data quality, contributor motivation
and legal issues (Olteanu-Raimond etal. 2017a). Also more inconspicuous chal-
lenges like participation inequality (Haklay 2016) (where most of the contribu-
tions are done by a small group of volunteers) and semantic challenges (Ballatore
2016) (such as simple definition conflicts) can have far-reaching consequences.
Most likely because of these and many more issues, there have only been a few
examples of long-term VGI initiatives. In Europe, many NMAs have some kind
of feedback system to collect hints on map updates from citizens. For example,
Swisstopo in Switzerland (Federal Office of Topography swisstopo 2018) and
Kadaster in the Netherlands (Verbeter de kaart 2018) have active citizen feedback
services. In those services, citizen contributions and their status in the update
process are visible to all users. The US Geological Survey (USGS) has a long tra-
dition of crowdsourcing its data collection. It has created a dedicated engagement
programme to promote and sustain the mapping community called the National
Map Corps (McCartney etal. 2015). The collected VGI helps the USGS update
its structure points in support of the national map and US topographical maps.
However, the features that the USGS collects are limited to a few predefined
point-type data features, such as schools (Jackson etal. 2013), hospitals and other
public buildings. In all of these existing crowdsourcing services, the collected
data are mostly point-type hints about map errors, and they do not seek to offer
full map editing tools for complete feature contributions.
The most well-known VGI realisation is probably OpenStreetMap (OSM—
Arsanjani et al. 2015). In many areas, the OSM data coverage for certain data
classes even exceeds the one provided by the authoritative topographic data-
base (Haklay 2010). Even though OSM data are open and free to use, licensing
conflicts prevent merging OSM data with authoritative NMA data. OSM data
are licensed under the Open Database License ‘ODbL’ 1.0. All data merged
with OSM data are to be distributed using the same ODbL licence and there-
fore requires the attribution of OSM contributors. An NMA could, for example,
offer its topographic data as open data under the CCBY licenses, and if so, then
they could not be merged with data under the ODbL licence. For map users, the
licensing does not usually present a problem as long as the data are open, but for
an NMA, it is important to preserve the copyright of the data. Regarding the com-
pleteness of the data, NMAs collect data according to certain quality principles
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Map Gretel: social map service supporting anational mapping…
throughout the country, whereas OSM data are often less complete or even miss-
ing in certain areas, because of the geographical distribution of contributors and
because they fall into different contributor types (Steinmann etal. 2013), who
generate data of varying quality.
In light of the recent developments in the use of VGI by NMAs, the National
Land Survey of Finland (NLS) has been developing a concept for the use of VGI
in the data acquired for the national topographic database (NTDB). The aim of the
work is to study whether it is possible to raise the quality (i.e. the completeness:
missing features, and the accuracy: feature location errors) of the NTDB via crowd-
sourced information. By offering more advanced map editing tools such as import-
ing GPX tracks and by adding social features such as citizens being able to comment
on each others contributions, we wanted to have more complete, accessible and use-
ful data. We also incentivized citizens to create new map features that are currently
not in the feature catalogue to reveal the novel data needs of citizens. With this new
concept, NLS seeks more refined ways of employing VGI to achieve better-quality
map data with fewer resources while developing the relationship between the NMA
and citizens.
In this paper, we first explain the main principles behind the social map service
that we developed in Sect.2. Then we present the high-level technical and social fea-
tures of the map service. Outcomes from the pilot, including results from question-
naires and user feedback are presented in Sect.3. In Sect.4, we discuss the future
implications of VGI in NMA procedures and draw some conclusions.
2 Map Gretel—a social map service
Currently, through the existing simple form-based feedback system, the NLS
receives approximately five hundred reports annually from private citizens about
errors and changes in map data. A report consists of a point on a map, a descrip-
tion and an email address. These reports are processed by NLS employees who are
public officers (referred to hereafter as ‘operators’). Operators evaluate the reports,
and when needed, there is a dialogue between the concerned citizen and an operator
via email. Operators update the NTDB based on the processed reports and eventual
dialogue with citizens.
As the basis for conducting this study, we developed a social map service called
‘Karttakerttu’, which can be freely translated into English as ‘Map Gretel’. Map
Gretel is a web browser-based social map service for citizens that enables data
import and data edits. Map Gretel uses the topographic map of Finland created from
the NTDB, and it serves as the reference map for users. NTDB is a vector data set
depicting the terrain of all of Finland at the scale of 1:10,000 and is updated contin-
uously. The topographic map created on the basis of the NTDB uses a pixel size of
1m at a scale of 1:10,000 and has nine scale levels. This background map represents
the latest visualisation of NTDB data, which is updated weekly into Map Gretel.
The registered users of Map Gretel (referred to as ‘mappers’) have access to a layer
where they can add and edit features. This layer is referred to as the ‘citizen layer’ in
this study and holds all the contributed features. According to the Map Gretel terms
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M.Rönneberg et al.
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of service, to which all mappers have agreed to when registering, all rights of con-
tributed features are given to the NLS.
2.1 The operational workow ofMap Gretel
The operational workflow of Map Gretel consists of two phases: contributing and
processing. There are two types of actors in Map Gretel: a mapper and an operator.
A mapper contributes by either creating or editing features and the operator pro-
cesses the features (Fig.1). The feature contributed by a mapper can be edited by
other mappers. Content generated by the mappers is stored to the citizen layer and
is processed by operators. If accepted by the operator, the feature is transferred to
the NTDB, thereby completing one cycle of the mapping process. A mapper may,
for example, add a point marker to the citizen layer showing an error on the map,
create a new walking path that does not exist on the map or further edit another
mapper’s contributed feature by refining it. After a mapper has contributed a new
feature to the citizen layer, the feature is automatically tagged as ‘unprocessed’ by
the system and made visible and editable to other mappers and processable by the
operators. The creator can both edit and delete the feature while other mappers can
just edit the feature. The operators, who are assigned to work on a specific part of
the country, start evaluating the contributed features by tagging the feature ‘being
processed’. While the feature is ‘being processed’, it cannot be edited by mappers. If
the feature is rejected by the operator after it has been processed by the operator, the
feature stays on the citizen layer. If the feature is suitable, it is tagged ‘transferred’
Fig. 1 Functionality available to creators, editors and operators of a feature in Map Gretel
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Map Gretel: social map service supporting anational mapping…
when the operator transfers it to the NTDB. Once the feature is processed, it can
again be edited by mappers. In principle, a suitable feature is removed from the citi-
zen layer only if it does not offer any additional information to that already found in
the NTDB. One example of such a situation is a feature representing an error on the
map. In many cases, the features hold additional information, such as informative
descriptions, and therefore they are not removed from the citizen layer, even though
they have been transferred to the NTDB. This means that ‘unprocessed’ features and
‘processed’ features are both present in the citizen layer.
2.2 Map Gretel social map service pilot
The pilot for the social map service was developed based on a number of key ideas:
accessibility, freedom, quality and relationships. The key ideas are aimed at creat-
ing a service where users would find the system easy to use, where users are not
restricted by the system to contribute data, and where users can create relationships
with both other users and the NMA operators.
We wanted to keep the barrier to entry to the service low by allowing anyone to
view the data, similarly to the citizen layers of NMAs in Switzerland (Federal Office
of Topography swisstopo 2018) and the Netherlands (Verbeter de kaart 2018). Nei-
ther of these systems have registration and users are completely free to add features
to the citizen layer. As user freedom in some ways stands in contradiction to data
quality (Mooney and Minghini 2017), we decided to restrict feature contributing
to registered users. Registration does have many benefits as it is needed to enable
the social features such as having identifiable feature comments. The registration
requires only an email address, which is used to confirm the creation of the user
account. One other example of restrictions we chose to impose is the way in which
the type of feature being contributed is selected. We provided a list of thirty or more
feature types from which mappers could select. The list guides the mappers to con-
tribute the kind of data in which the NMA is interested.
The user interface was simplified as much as possible to allow users who are not
familiar with mapping tools to easily contribute. An anonymous feedback channel
was also added to make it as inviting as possible to hear from the users. We wanted
to give mappers the freedom to contribute instead of restricting them. We could have
restricted contributions by means of predefined menus and other tools or given map-
pers editing privileges only to features that they themselves had created. Instead,
we thought that in order to reach users who might have insights into what is really
going on in the environment, it was reasonable to keep the system open. We there-
fore chose to allow mappers to edit all the features, even those that the mappers did
not create themselves.
The implications of including aspects familiar from social media services in a
VGI map service will, in the long run, develop relationships between the mappers
and between mappers and operators. These relationships should help produce bet-
ter-quality features since feedback and training have been shown to retain interest
and increase quality in other VGI and citizen science-based projects (Minghini etal.
2017). Such relationships would also be useful if, for example, there would be some
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M.Rönneberg et al.
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specific need from the NMA side to map a certain place with the help of mappers.
Mappers with good reputations as reflected in their profiles could be asked to do
certain assignments for the NMA, with the NMA being relatively confident that it
would then receive high quality data. Mapper reputation could be based, for exam-
ple, on the quality and quantity of their contributions.
2.3 Technical aspects ofMap Gretel
The technical aspects of the social map service were driven by two criteria: func-
tionality and ease of implementation. These criteria led us to choose the open-source
project called uMap (uMap 2017) as the main development platform to use, which
makes use of OSM. We have made significant modifications to the source code of
uMap both on the client side and the server side, which proved necessary in order for
the functionality to work as intended. We had to use technical solutions that did not
favour performance and high-level scalability, and we also had to limit the designed
functionality. The Map Gretel pilot has the following high level of functionality: a
map browser, a citizen layer and a feature editor. Key functionalities are presented
in Table1 with a rationale for each one. The map browser displays the background
topographic map, which users then use to explore the current situation on the map.
On low-zoom levels, a heatmap is displayed to show where there is user-generated
content. Operators see a heatmap of features that have not yet been evaluated. The
citizen layer, which lies on top of the background map, displays the content that
mappers have created. Due to technical limitations of the pilot, the functionality to
display features on the map is limited to 20. Thus, the UI has a button to display fea-
tures; this button is always visible. By clicking the button, 20 of the nearest features
relative to the centre point of the map screen are displayed. The features are dis-
played as points or lines. The focus of the pilot was on point and line features; thus
polygon creation was disabled. The features presented on the map are also listed in a
side panel to show some of their attributes. By pressing on either the feature symbol
Table 1 Key functionalities of Map Gretel and the rationale behind them
Key functionality Description and rationale
Registration requirement
for adding and editing
Mappers can freely add and edit all features (point, line string). Limiting
the creation of features to only registered users reduces unintentional
false entries and spam while binding users to their content, which then
enables social features (see Sect.2.4)
Display all features as a
heatmap at lower zoom
Presenting the data as a heatmap gives users an impression of where the
features are being created and the density of the features. The heatmap of
unevaluated features helps the operator workflow
Uploading geometry Mappers can upload GPX files. This simplifies the process of contributing
features for mappers and can provide better positional accuracy when
compared to digitizing on the map or aerial image
Process features (operators) Operators tag features after evaluating them as “transferred” or “rejected”.
Features that have been transferred but remain in the citizen layer serve
as a reminder to mappers that their contribution still holds valuable
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Map Gretel: social map service supporting anational mapping…
on the map or an item on the list, more information on the feature will be displayed.
There is also a place name search and a measuring tool in the UI. With the feature
editor (Fig.2), mappers can add features to the citizen layer as points or line strings
by digitizing on the map or by importing data from a file, e.g. a GPX file. The fea-
ture editor allows any mapper to not only edit the title, description and type of any
feature but also to adjust the geometry of any feature in the citizen layer. Operators
can tag features as ‘transferred’ (feature has been added to the NTDB) or ‘rejected’
(feature remains on the citizen layer). For example, a walking path made by one
mapper can have its geometry adjusted and description expanded by another mapper
and finally have the path transferred by an operator.
2.4 Proposed social andgamication aspects ofMap Gretel
The social and gamification aspects of the service, which are based on a number
of social media services, were not implemented in the pilot (Fig.1). This func-
tionality is the basis for the mapper-to-mapper and mapper-to-operator interac-
tion. The key aspects are mapper profiles, mapper rankings, feature rating, feature
commenting and feature confirming. When implemented, mappers will have nick-
names that are to be displayed in both the features and the comment section, but
Fig. 2 Feature editor of Map Gretel displaying a footpath added by a user
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the nickname can be hidden from the feature if the mapper chooses to do so in
order to better protect their privacy. Feature creator and editor nicknames can be
presented in the feature with a timestamp. From the profile, a mapper can moni-
tor their mapping progression. The functionalities of the social and gamification
aspects are presented in Table2 with a description of each one.
Table 2 Key functionalities of Map Gretel that were not implemented in the pilot but which describe the
proposed social and gamification aspects of the tool
Key functionality Description
Feature comment section Mappers and operators can comment on features in the
comment section of each feature. Comments are sorted
by rating. Operator comments are distinguished from
other comments with a symbol. The number of comments
is displayed in the feature view and also on the map
Rating features via upvotes and downvotes Each mapper and operator can rate a feature by casting one
upvote or a downvote. Voting is anonymous. The rating
is calculated by subtracting downvotes from upvotes. The
rating of the feature is displayed on the map symbol and
also on the feature view. Operator upvoted features are
distinguished from other features with a symbol
Upvote and downvote comment Each mapper and operator can rate a comment by casting
one upvote or a downvote. Voting is anonymous. The rat-
ing is calculated by subtracting downvotes from upvotes.
The rating is displayed with the comment. Comments
with the highest rating appear first in the comment sec-
tion. Operator upvoted comments are distinguished with
a symbol
Confirm feature Mappers can confirm features by sending photos of the
feature, which indicates that the mapper has first-hand
experience with the feature. Confirmation photos are only
visible to operators. Confirmation is displayed with the
feature on the map symbol and in the feature view
Mapper profile The profile displays the mapper’s nickname and their
mapping progression by showing their rank and the steps
required to reach the next rank
Ranking system for mappers These include gamification aspects to further motivate
mappers to create content. The ranking is based on the
number of contributed features, the number of highly
rated comments, the sum of all contributed features,
and comment upvotes by the mapper. The ranking is
displayed next to the mapper’s nickname when they make
comments and next to the feature for operators
Ranking system for operators These include gamification aspects to further motivate
operators to promote quality interactions with map-
pers. The ranking is based on the number of comments
an operator has contributed and on the ratings of the
comments made by the operator on transferred features.
Rejected features are disregarded. The ranking is dis-
played only for the operator
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Map Gretel: social map service supporting anational mapping…
Commenting on a feature is a way of showing interest. Features that have been
considered interesting or important by mappers aid the operator in making decisions
about which features to focus on. Mappers also receive positive feedback when their
contribution is commented on by other mappers and operators. Other mappers may
have valuable information to add to the feature that is useful to both other map-
pers and operators. Operators can also improve their relationship with mappers in
the comment section, while operator comments guide mappers to contribute better
features. When an operator rejects a feature, the operator is asked to give a reason
for rejection. The reason for rejection is displayed as a comment in the feature. Simi-
lar to commenting, rating both features and feature comments allows mappers to
emphasize important contributions to the operators and other mappers. Each mapper
can cast one vote for each feature and comment. This one vote rule will keep the
voting democratic for the ranking system. The upvotes and downvotes are anony-
mous due to mapper privacy. Operator upvotes are visible since they guide map-
pers towards better contributions. Regarding confirmation, photos of the feature help
operators in processing the feature. Keeping them visible only to operators avoids
many privacy issues. The ranking system is based on the ratings and introduces a
gamification aspect to the mapping, allowing users to know how much and how
well they are performing compared to others; thus, visible ranks are needed. Visible
ranks also inform the operator of the mapper experience. One example of the rank-
ing system in Map Gretel is to count the number of upvotes a mapper has received
regarding the features they have contributed. This particular rank would emphasise
a mapper’s success in creating content thought to be interesting by the community.
Another example is to rank the number of features that have been successfully trans-
ferred by the operator. This rank would emphasise a mapper’s success in creating
content thought to be valuable by the operator. The extent to which a mapper scores
well on both rankings could also be used as a rank. Operators also have gamifica-
tion aspects included in their process of transferring features to the NTDB. Their
rank is based on how well the operator detects the needs of the mappers and how
actively the operator participates in the discussion. This can motivate operators to
get in touch with users and ask for more details more often. The ranking is intended
to help operators follow their own progress and is thus visible only to themselves.
3 Results fromtheMap Gretel pilot
The pilot for the social map service was launched on 23 March 2017 for the whole of
Finland. During the launch the pilot was promoted by NLS on their website and on
their Twitter and Facebook accounts. The pilot was also covered in a few newspapers
at the time. In the first 6months of operation, the pilot has expanded to include more
than 363 registered users, who have contributed over 950 features to the citizen layer.
A total of 146 users have created one or more features meaning that roughly 40% of
users have made a contribution. Thirty-four users have made more than five contribu-
tions, and 16 users have made 10 or more contributions. A total of 3326 actions have
been made by the users, which includes newly registered users (363), new features
added (950) and features edited (2086). A representation of all the accumulated data
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is presented as a heatmap in the service (see Fig.3). Of the features, 687 (73%) have
currently been processed and 330 of them (48% of the processed contributions) have
been transferred to the NTDB by the 15 NMA operators who participated in the pilot.
The operator’s performance at processing features was not measured and thus cannot
be compared to the previous email-based system. The operators were processing Map
Gretel contributions on top of their regular work, and we did not want to make them
feel pressured but rather have the operators play with Map Gretel. However, most of
the operators did not find the work required laborious. The most common reason for
not transferring a feature is that it does not belong in the current feature catalogue of
the NTDB (slipways for boats, for example), and thus cannot be transferred. Only
around 10% of all the features had either insufficient data or could not be validated by
the operators, for example, from an aerial image, and were rejected for lack of quality.
We encouraged mappers to contribute features that were not included in the NTDB
Fig. 3 Accumulated data from users is presented as a heatmap in the social map service
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Map Gretel: social map service supporting anational mapping…
feature catalogue knowing that we could not transfer them. The aim was to find out
what new features users would add to the citizen layer. Features that are not part of
the NTDB catalogue will remain in the citizen layer. Figure4 presents one example
of data contributed by a mapper and processed by the operators, where buildings that
no longer exist were marked as errors on the map and a new building was drawn
by the mapper. After the data were processed by the operator, old buildings were
removed and a new building was added to the NTDB.
3.1 User feedback
Users provided 31 messages via the feedback page of the map service. The feedback
varied from bug reports to suggestions for new functionality, but users also provided
detailed descriptions of features that they were unable to add to the system. Some
users reported that they were unable to remove some of the contributions they had
made by mistake. Much of the feedback had to do with the pilot nature of the map
service, meaning that it addressed bugs and incomplete features. Some feedback
was clearly from experts in the field, who were kind enough and interested enough
to detail multiple issues, while also praising the service. As the feedback was very
constructive, we responded to all feedback that gave an email address. Here is one
example of expert feedback (translated from Finnish): ‘For some reason, nobody
before has developed this sharing of geographic data from the users’ perspective
(having a low barrier to entry)’, meaning that there is not currently a service that
makes it very easy for citizens to contribute data to an NMA.
3.2 User survey
We conducted a web-based, 5-to-10-min survey with 10 questions and received
78 responses from users. We sent the survey to all registered users via email and
Fig. 4 User contributions (on the left) for buildings that no longer exist and drawing of a new building,
which the operator then processed and transferred to thenational topographic database (NTDB) (on the
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M.Rönneberg et al.
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also provided a link to the survey on the Welcome view and on the navigation
bar of the map service. The aim of the survey was to obtain an overall idea of
what the average user is like and gain an understanding of how they would like to
see the service developed further. We asked how often the user had visited Map
Gretel. 54 of the 78 respondents answered ‘a few times’, and 12 answered ‘often’
or just ‘once’. (See Fig.5.) Regarding the ‘often’ answers, it is important to note
that the service has been up and running for only 6months, but this pattern does
follow what is often found with other citizen-based projects, i.e. a small number
actually make the most contributions (Fritz etal. 2017). We asked whether the
user had added features and roughly 70% (54) of the respondents answered ‘yes’.
We asked the respondents if the features that other users had contributed had been
useful, and 25% of them answered in the affirmative. This rather high percentage
was somewhat unexpected, since the 950 features contributed were spread around
the country and not restricted to one particular area of familiarity (see Fig. 3).
Given the number of features and the extent of the area in which they are situ-
ated, a single feature has a low likelihood of being both near and useful to other
users. We also asked what new functionality users would like to see included,
and 67.6% of them chose a mobile mapping application. This is unsurprising as
many citizen science projects now use mobile apps for participation (Seibert etal.
2017). 54.4% also wanted to receive notifications of when their contribution had
been processed by the NMA operator, which makes sense since citizens want
recognition that their contributions are being used (Fritz et al. 2017). The open
feedback from the survey was much like the feedback given through the service.
Many of the comments had to do with the user–operator relationship. Below is
some translated feedback.
‘It’s great that an active mapper can add something that is not visible on the
‘I would like to know about the processing time. My contributions have still not
been processed’.
‘There’s no mobile application’.
‘There are issues with the user interface’. The respondent then listed multiple
relevant issues, such as the lack of transparent layers.
Fig. 5 78 respondents answered
the user survey on how often
they have visited the service
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Map Gretel: social map service supporting anational mapping…
3.3 NMA operator survey
Eight of the 15 NMA operators answered a survey directed at them. The operators
estimated that approximately 10% of the contributions were of low quality (mostly
tests done by users). When asked what portion of the data has been useful or usable,
the operators answered ‘more than 60%’. As to whether the processing of features
has been laborious, three out of eight operators answered yes. The operators thought
that the geometric quality of the data was mixed, as was to be expected when some
users imported GPX tracks and others drew their tracks on the map freehand. One
operator noted that a large proportion of the features are paths that actually exist in
the real world, but that are not in the NTDB. This confirms that Map Gretel also
yields other types of data than just point data, unlike the existing report system used
by NLS, which cannot handle line strings. We estimate that approximately 50% of
the features contributed by the users to Map Gretel are some type of path and there-
fore are a new type of data received from citizens. There has been both excitement
and a lack of enthusiasm among the operators regarding the whole idea of VGI.
The reason for the lack of enthusiasm of some of the operators may be the result of
operators having to process Map Gretel data on top of their normal work. The data
quality may also have had an effect on the operators’ enthusiasm. Overall, however,
the response has been positive, and operators are clearly interested in the idea of
including VGI in their processes. As one operator put it: ‘A great service for both
citizens and us operators. Thank you for the entire development team!’ The opera-
tors emphasised the importance of being able to get in touch with users as a way to
obtain more valuable information.
3.4 Overall results
Overall the social map service has been accepted very well by its users and opera-
tors alike. We were pleased with the number of people who registered for the ser-
vice and with the number of features contributed over the relatively short time span
of the service. The quality of the contributions was also at a high level. The users
were generally in favour of a mobile application as an easier way to collect data. The
desire for a mobile application was also expressed by some of the operators when we
discussed the future of the service with them. The user–operator relationship, which
unfortunately did not realise its full potential in this pilot project, was considered
important by both the users and the operators. From the user side, there is a clear
need to be recognised and to receive acknowledgement that their contribution has
been received and deemed of value. From the operator side, the ability to directly
communicate with users was seen as a way to gather even more valuable informa-
tion. The operators know the right questions to ask in a given situation, and there-
fore any means of supporting user–operator communication is a way to improve data
quality and also facilitate user retention. Due to the lack of methods to communicate
with users (e.g. the possibility to comment on a particular feature), operators fig-
ured out a way to reach users by editing the descriptions of the features as a way
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M.Rönneberg et al.
1 3
of explaining the decisions they made when, for example, choosing not to transfer
the feature to the NTDB. This speaks to both the need for better user-operator com-
munication and also the enthusiasm of operators in facilitating such dialogue. More
generally, both the users and operators need better tools for engaging in VGI work.
4 Future implications ofVGI inNMA procedures
Currently, the use of VGI in many NMAs is low; but as this study has shown, it is
not overly difficult to launch successful initiatives that aim to incorporate VGI in
NMA procedures. Our pilot service had a fair number of users, and users uploaded a
considerable number of features in a relatively short period of time, which indicates
that there are citizens interested in VGI, even though the service did not include the
planned incentives such as gamification (Olteanu-Raimond etal. 2017b) and social
aspects. Compared to the traditional way of gathering information from citizens,
which yields approximately 500 feedback reports a year, Map Gretel has already
gathered over 900 features in half a year, many of which are types of data, like paths
in a forest, that the existing feedback system cannot provide. Our service was con-
sidered to have a rather low barrier to entry: it only required the users to register
with an email to make contributions and edits. Had we released a mobile applica-
tion, which is what the majority of the users wanted, the resulting data would most
likely have been even better, both in quantity and quality. A mobile platform for
Map Gretel is the logical next step. As for other future work, we found that citi-
zens and NMA employees alike are interested in VGI and that there are many ways
to support both parties. Citizens need confirmation and acknowledgement of their
work; the emphasis on the user–operator relationship already partially meets that
need. Applying methods used in social network services such as voting and com-
menting are simple but effective ways of promoting dialogue between not only the
users themselves but also between users and operators. These methods require fur-
ther study in a VGI context. Based on our results, the operators are keen to ask users
more questions, while users are usually interested in hearing that their contributions
have been useful. Therefore, integrating this functionality into Map Gretel and other
similar projects would be beneficial.
When citizens are brought into the realm of data production, protecting their
privacy is a considerable research challenge (Mooney etal. 2016). Currently there
are initiatives to protect the privacy of citizens and give them more control over
their data (Guinness etal. 2015), but there are still many open questions and often
clear principles and rules are still lacking. Issues regarding privacy in VGI are fur-
ther emphasised in the newly implemented EU General Data Protection Regulation
(GDPR), which is ‘designed to harmonize data privacy laws across Europe, to pro-
tect and empower all EU citizens’ data privacy and to reshape the way organisations
across the region approach data privacy’ (Regulation (EU) 2016). VGI initiatives
should take into consideration the new laws, as the collected data can contain ‘per-
sonal data’, for example, location data that can be linked to a person (Regulation
(EU) 2016).
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1 3
Map Gretel: social map service supporting anational mapping…
Previous studies have suggested that VGI has great potential, but also many chal-
lenges to overcome. VGI could potentially complement and even rival traditional
mapping sources in terms of both data quality and richness (See et al. 2017), but
workflow developments and protocols for data collection processes have to be devel-
oped in order to overcome the challenges pertaining to VGI data quality (Minghini
et al. 2017). There are also issues with the metadata of VGI, as it is patchy and
extremely heterogeneous (Bastin etal. 2017). Citizens need to be supported when
contributing VGI, while also having their privacy protected. Recruitment, motiva-
tion and retention need to be addressed in the future (Fritz etal. 2017). One way
is through the use of gamification, as it shows promise as a method for increasing
motivation among citizens (Olteanu-Raimond etal. 2017a). Gamification is a new
area of expertise that NMAs can familiarise themselves with in order to better reach
and retain their users.
What kind of future implications does Map Gretel have with respect to the proce-
dures used in NLS for updating maps? At the very least, it has been recognised that
interacting with citizens, an important aspect of a successful VGI platform (Olte-
anu-Raimond etal. 2017b), can create positive publicity and aid in collecting data
that would otherwise be left unmapped. NMAs are seen as trustworthy and reliable,
and this could be leveraged when engaging citizens. One way to capitalise on this
trust is to introduce the topic of VGI in elementary schools. This would enlarge the
spatial coverage of VGI throughout the country. Embedding the topic of VGI into
the school curriculum would add continuity to the process and ease communication
with citizens, as already tested by the NMA Kadaster Netherlands (Bol etal. 2016).
Citizens will likely be more willing to share their data with an NMA rather than
with other entities, especially if they have had positive interactions with an NMA
through school cooperation. To have these positive interactions, NMA operators
need tools that will help them do their job better. Our study revealed that operators
are interested in working with citizens but they need more advanced tools that allow
for dialogue with the citizens making the contributions.
A more fundamental change regarding the advancement of automation in the
future can make certain elements of VGI redundant (de Oliveira etal. 2014), and it
might focus VGI into areas of data collection that automation cannot reach. VGI can
also only necessarily comprise a small part of the NMA’s whole data collection pro-
cess, and its role in the process might shift more to data validation rather than data
collection in the future. Citizens will more likely avoid repetitive tasks, especially
if they can be done by automation, and favour tasks that require more intelligence,
such as validating a data set that was produced via automation. The Missing Maps
project (Albuquerque etal. 2016), for example, avoided repetitive tasks by having
experienced users validate each other’s contributions. Therefore, we foresee that in
the short run, NMAs will venture further in the direction of games and gamifica-
tion that are integrated with the processes of data collection. But in the longer run,
NMAs might be more interested in the analysis that citizens can perform. As an
example, a data set that has been produced via an automation process can be ana-
lysed by a citizen in a game-like environment and the analysed result can then be
processed by an NMA operator to validate it, which will both help save resources
and give the user more incentive to continue making contributions.
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M.Rönneberg et al.
1 3
For the near future of VGI as a whole, our study has led us to envision a VGI ser-
vice influenced by social media services such as Facebook (social networking tools),
WhatsApp (privacy-respecting messaging) and Instagram (visual information tools),
and also by games such as Pokemon Go (incentives for outdoor activities). The com-
mon theme across these different services is the very low barrier to entry, simplicity,
user interactions and perhaps most importantly—fun. A simple voting or comment-
ing functionality can be seen as a gamification element when citizens compete to
become the most respected player in the VGI platform. At this point, VGI is not only
about the data collected by the user, but also a way for users to enjoy their time and
gain respect among their peers. Users will likely expect something more than just
the good feeling of helping out in the future when they participate in VGI initiatives.
They already value their time and will more likely spend it on something that is
considered an experience. We predict that whoever can develop a service that makes
the role of a ‘citizen as a sensor’ fun will raise the data collection process to the next
level both in terms of quantity and quality.
Acknowledgements This work was supported by the National Land Survey of Finland through the Pro-
ject KMTK Kansa (National Topographic Database NTDB subproject Citizen). The authors would like
to thank the anonymous reviewers for providing valuable comments and helpful suggestions to greatly
improve the quality of the paper.
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tional License (http://creat iveco mmons .org/licen ses/by/4.0/), which permits unrestricted use, distribution,
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... The United States Geological Survey (USGS) has a long history of using crowdsourcing data collection to support topographic mapping [23]. Also, national agencies develop VGI pilot projects for topographic data collection, for example, Map Gretel, developed by the National Land Survey of Finland (NLS) [24]. Indonesia's NMA, Badan Informasi Geospasial (BIG), developed PetaKita (, also available in the Google Play store) to support community involvement in participatory mapping. ...
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There has been increased collaboration between citizens and scientists to achieve common goals in scientific or geographic data collection, analysis, and reporting. Geospatial technology is leveraging the power of citizens in such efforts. Governments have been exploring participatory approaches. This situation should be balanced by sharing knowledge and collaborative learning between stakeholders involved in the participatory activity. Training and education are enhanced by providing guidelines, sharing best practices, and developing toolkits. For toponym handling, a generic framework and capacity building are needed to increase public awareness and enable citizen toponymists. This paper addresses issues around citizen involvement in increasing toponymic knowledge through citizen science and geospatial capacity building. First, we examined the current practice of toponym handling and developed a generic framework. We then used stakeholder feedback and other resources to modify the framework for Indonesian use. Second, we conducted collaborative learning to share information and bridge the knowledge gaps among multiple stakeholders. Third, we applied insights and lessons learned from these activities to develop ideas, suggestions, and action plans to implement participatory toponym handling in Indonesia.
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В статье описаны современные электронные ресурсы как инструменты для топонимических исследований. До недавних пор использование геоинформационных систем (ГИС) в исследованиях географических названий нельзя было назвать масштабным. С развитием современных информационных технологий топонимические ис- следования приобрели новый характер, отличающийся новейшими подходами к сбору и обработке геоданных. Цель статьи – выявить, проанализировать и описать современные электронные средства для сбора и изучения топонимов с целью дальнейшего использования подобных ресурсов в разного рода исследованиях. Материал и методы. Наборы топонимов стали центральным компонентом систем GPS-навигации и онлайн-карт, которые сегодня широко используются в научных исследованиях. Массовая информатизация, развитие высокоскоростного интернета, доступность приобретения и использования портативных компьютеров и мобильных устройств, повышение компьютерной грамотности населения охватывают большинство стран мира, что отражается на качественно новых подходах к изучению топонимической лексики. Революция цифрового картографирования и мобильных приложений позволяет простым гражданам вносить свой вклад в обработку топонимического материала в режиме онлайн. С появлением электронных систем Google Maps, Apple Maps, Яндекс.Карты, Bing Maps и им подобных топонимические исследования приобрели новый характер. Изыскания на уровне микротопонимии стали четче и подробнее. Наглядно показано, как можно использовать онлайн-топонимические словари, электронные карты, наукометрические базы данных, географическую базу данных GeoNames и Google-переводчик для проведения топонимических исследований. Указываются преимущества и недостатки современных сайтов и программ, ориентированных на исследования в области топонимики. Делаются выводы о целесообразности привлечения технических средств к топонимическим исследованиям в целом. Научные онлайн-дискуссии на таких площадках, как ResearchGate и Facebook, приводят к реальному взаимодействию ученых и помогают сделать научную мысль глубже, четче и ярче. Принимая во внимание всевозможные погрешности вследствие применения современных описанных технологий, считаем необходимым контроль в виде сверки данных, например по этимологии географических имен и т. п. Упомянутые инструменты позиционируются как чрезвычайно полезные для выявления, описания, изучения, комплексного анализа и систематизации топонимического материала.
New technologies have helped to improve the tourism sector and to develop strategies that resulted in the so-called smart destinations, underpinned and transformed by modern information and communication technologies (ICTs). Besides, tourism is a global market that continuously seeks mechanisms to grab tourists' and visitors' attention. In view of that, in recent decades, the gamification concept has acquired new definitions from different perspectives, but always associated with the idea of leisure. In tourism, gamification is related with experiences, which by using game elements and digital game design techniques (virtual reality or augmented reality, among others) improve the tourist experience and the user's engagement. This chapter addresses gamification and its influence on tourism experience, together with some gamification applications' examples that can be effective mechanisms to promote tourism businesses or tourism destinations, raising engagement and generating trust.
Conference Paper
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Voluntary Geographic Information (VGI) projects such as OpenStreetMap (OSM) attract more and more people. Despite the number of registered users continuously increases, it is widely unknown how these users actually contribute. The crucial question is “Who contributes what to a VGI project?” This work proposes a method for identifying contribution profiles of OSM mappers. Based on the OSM Full Planet History File, all user contributions back to the early days of the OSM project in the year 2005 have been analysed. For analysing different contribution patterns a k-means clustering of action and feature types has been applied. The clustering reveals a set of well-defined and characteristic contribution profiles like “Premium Creator”, “Highway Mapper” or “All-Rounder”.
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While there is now a considerable variety of sources of Volunteered Geographic Information (VGI) available, discussion of this domain is often exemplified by and focused around OpenStreetMap (OSM). In a little over a decade OSM has become the leading example of VGI on the Internet. OSM is not just a crowdsourced spatial database of VGI; rather, it has grown to become a vast ecosystem of data, software systems and applications, tools, and Web-based information stores such as wikis. An increasing number of developers, industry actors, researchers and other end users are making use of OSM in their applications. OSM has been shown to compare favourably with other sources of spatial data in terms of data quality. In addition to this, a very large OSM community updates data within OSM on a regular basis. This chapter provides an introduction to and review of OSM and the ecosystem which has grown to support the mission of creating a free, editable map of the whole world. The chapter is especially meant for readers who have no or little knowledge about the range, maturity and complexity of the tools, services, applications and organisations working with OSM data. We provide examples of tools and services to access, edit, visualise and make quality assessments of OSM data. We also provide a number of examples of applications, such as some of those used in navigation and routing, that use OSM data directly. The chapter finishes with an indication of where OSM will be discussed in the other chapters in this book, and we provide a brief speculative outlook on what the future holds for the OSM project.
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Despite the considerable growth in Volunteered Geographic Information (VGI) activities in citizen sensing and the evident opportunities for VGI use in map revision and updating, few European National Mapping Agencies (NMAs) or other types of government bodies have engaged significantly with VGI. Moreover , the level of engagement of NMAs with the VGI community varies greatly, and most of them have proposed their own tools for encouraging citizens and public partners to collect feedback or new data. There are numerous barriers limiting the participation of citizens and public partners in NMA data collection , including data quality issues, the motivation of the contributors and legal issues. The aim of this chapter is to give an overview of the experiences of some European NMAs in engaging with VGI. Guidelines and recommendations to support wider engagement with the VGI community are also proposed to help NMAs and interested government bodies exploit the potential of VGI for authoritative mapping.
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Volunteered Geographic Information (VGI) has become a rich and well established source of geospatial data. From the popular OpenStreetMap (OSM) to many citizen science projects and social network platforms, the amount of geographically referenced information that is constantly being generated by citizens is burgeoning. The main issue that continues to hamper the full exploitation of VGI lies in its quality, which is by its nature typically undocumented and can range from very high quality to very poor. A crucial step towards improving VGI quality, which impacts on VGI usability, is the development and adoption of protocols, guidelines and best practices to assist users when collecting VGI. This chapter proposes a generic and flexible protocol for VGI data collection , which can be applied to new as well as to existing projects regardless of the specific type of geospatial information collected. The protocol is meant to balance the contrasting needs of providing VGI contributors with precise and detailed instructions while maintaining and growing the enthusiasm and motivation of contributors. Two real-world applications of the protocol are presented , which guide the collection of VGI in respectively the generation and updating of thematic information in a topographic building database; and the uploading of geotagged photographs for the improvement of land use and land cover maps. Technology is highlighted as a key factor in determining the success of the protocol implementation.
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A protocol for the collection of vector data in Volunteered Geographic Information (VGI) projects is proposed. VGI is a source of crowdsourced geographic data and information which is comparable, and in some cases better, than equivalent data from National Mapping Agencies (NMAs) and Commercial Surveying Companies (CSC). However, there are many differences in how NMAs and CSC collect, analyse, manage and distribute geographic information to that of VGI projects. NMAs and CSC make use of robust and standardised data collection protocols whilst VGI projects often provide guidelines rather than rigorous data collection specifications. The proposed protocol addresses formalising the collection and creation of vector data in VGI projects in three principal ways: by manual vectorisation; field survey; and reuse of existing data sources. This protocol is intended to be generic rather than being linked to any specific VGI project. We believe that this is the first protocol for VGI vector data collection that has been formally described in the literature. Consequently, this paper shall serve as a starting point for ongoing development and refinement of the protocol.
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In the past few years, volunteers have produced geographic information of different kinds, using a variety of different crowdsourcing platforms, within a broad range of contexts. However, there is still a lack of clarity about the specific types of tasks that volunteers can perform for deriving geographic information from remotely sensed imagery, and how the quality of the produced information can be assessed for particular task types. To fill this gap, we analyse the existing literature and propose a typology of tasks in geographic information crowdsourcing, which distinguishes between classification, digitisation and conflation tasks. We then present a case study related to the " Missing Maps " project aimed at crowdsourced classification to support humanitarian aid. We use our typology to distinguish between the different types of crowdsourced tasks in the project and choose classification tasks related to identifying roads and settlements for an evaluation of the crowdsourced classification. This evaluation shows that the volunteers achieved a satisfactory overall performance (accuracy: 89%; sensitivity: 73%; and precision: 89%). We also analyse different factors that could influence the performance, concluding that volunteers were more likely to incorrectly classify tasks with small objects. Furthermore, agreement among volunteers was shown to be a very good predictor of the reliability of crowdsourced classification: tasks with the highest agreement level were 41 times more probable to be correctly classified by volunteers. The results thus show that the crowdsourced classification of remotely sensed imagery is able to generate geographic information about human settlements with a high level of quality. This study also makes clear the different sophistication levels of tasks that can be performed by volunteers and reveals some factors that may have an impact on their performance.
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Vast swaths of geographic information are produced by non-professional contributors using online collaborative tools. To extract value from the data, creators and consumers alike need some degree of consensus about what the entities of their domain of interest are and how they are related. Traditional information communities, such as government agencies, universities, and corporations, have devised informal and formal mechanisms to reduce the misinterpretation of the data they rely on, curating vocabularies, standards, and, more recently, formal ontologies. Because of the decentralized, fragmented nature of peer production, semantic agreements are more difficult to establish and to document in volunteered geographic information (VGI), severely limiting the re-usability and, ultimately, the value of the data. This paper provides an overview of the semantic issues experienced in VGI, and what potential solutions are emerging from research in geo-semantics and in the Semantic Web. The paradigm of Linked Data is discussed as a promising route to handle the semantic fragmentation of VGI, reducing the friction between data producers and consumers.
The rapid expansion of citizen science projects and crowdsourcing applications is yielding a huge and varied pool of Volunteered Geographic Information (VGI) on a wide variety of themes. This VGI may be of huge value for institutions, individuals and decision-makers, but only if it can be discovered, evaluated for quality and fitness-for-purpose and combined with data from other sources. If VGI data are to be discovered, used and reused to their full potential, they must be actively managed. In this chapter we assess the current state of the art regarding data management practices in VGI, identify some challenges, obstacles and best-practice examples, and review a range of developing and established open source technologies which can underpin robust and sustainable data management for VGI. We conclude that VGI is likely to remain patchy and heterogeneous and that existing standards may not be exploited to their full potential. Nevertheless, automated support for documenting the generation and use of VGI, as well as annotations following the Linked Data paradigm, can help to improve interoperability and reuse. We were able to identify good practices within different existing systems, but more research and development work is needed in order to support their joint application for the benefit of VGI. New data management methodologies can only succeed if their benefits (for example, simplifying administration or lowering the entry barrier to data publication) exceed the implementation costs.