Improving the Involvement of Digital Volunteers in Disaster Management

Abstract

Volunteered geographic information (VGI) has been seen as useful information in times of disasters. Several authors have shown that VGI is useful for coping with preparedness and response phases of disaster management. However, because it is still a young technology, the use of VGI remains uncertain, due to its lack of strong reliability and validity. It is our assumption that to improve reliability and validity the promotion of citizen engagement (CE) is needed. CE is not new topic, but in the digital humanitarian context, it involves important factors that are not yet considered by disaster managers, such as communication processes, motivation of volunteers, different media for production of information, etc. To fill this gap, we identified a set of preliminary factors which should be considered to promote the involvement of volunteers in disaster management. These factors were derived from critical review of CE literature and from an analysis of lessons learned from an experiment on interaction with citizens carried out in context of the EU-project “DRIVER – Driving Innovation in Crisis Management for European Resilience”.

Full text

Improving the Involvement of Digital
Volunteers in Disaster Management
Roberto dos Santos Rocha
1,2(&)
, Adam Widera
2
,
Roelof P. van den Berg
2
,João Porto de Albuquerque
1,3
,
and Bernd Helingrath
2
1
ICMC, University of São Paulo, São Carlos, Brazil
rsrocha@usp.br, j.porto@warwick.ac.uk
2
ERCIS, University of Münster, Münster, Germany
{adam.widera,roelof.vandenberg,
bernd.hellingrath}@ercis.uni-muenster.de
3
CIM, University of Warwick, Coventry, UK
Abstract. Volunteered geographic information (VGI) has been seen as useful
information in times of disasters. Several authors have shown that VGI is useful
for coping with preparedness and response phases of disaster management.
However, because it is still a young technology, the use of VGI remains
uncertain, due to its lack of strong reliability and validity. It is our assumption
that to improve reliability and validity the promotion of citizen engagement
(CE) is needed. CE is not new topic, but in the digital humanitarian context, it
involves important factors that are not yet considered by disaster managers, such
as communication processes, motivation of volunteers, different media for
production of information, etc. To fill this gap, we identified a set of preliminary
factors which should be considered to promote the involvement of volunteers in
disaster management. These factors were derived from critical review of CE
literature and from an analysis of lessons learned from an experiment on
interaction with citizens carried out in context of the EU-project “DRIVER –
Driving Innovation in Crisis Management for European Resilience”.
Keywords: Citizen engagement Volunteered geographic information 
Motivation Crowd sensing Disaster management
1 Introduction
Citizen Engagement (CE) refers to actions designed to identify and address issues of
public concern [1]. Community participation can augment officials’abilities to govern
in a crisis, improve application of communally held resources in a disaster or epidemic,
and mitigate community wide losses [2].
Participatory community approaches in research and governance are not new [3,4].
However, Web 2.0 platforms, mobile internet, and social networking access through
smartphones have made a significant difference by encouraging the social responsi-
bility and active engagement of citizens [3]. These technologies enable the public to
contribute and participate on an unprecedented scale and have led to many diverse
©IFIP International Federation for Information Processing 2017
Published by Springer International Publishing AG 2017. All Rights Reserved
Y. Murayama et al. (Eds.): ITDRR 2016, IFIP AICT 501, pp. 214–224, 2017.
https://doi.org/10.1007/978-3-319-68486-4_17

initiatives using information from citizens [3,4]. Examples include, among others,
participation of the public in event reporting, environmental monitoring, and providing
information on natural disasters. This phenomenon is called volunteered geographic
information (VGI).
VGI is the harnessing of tools to create, assemble, and disseminate geographic data
provided voluntarily by individuals [5]. VGI has been increasingly recognized by
researchers as an important resource to support disaster management [23–25]. The
production of geographic information is predominantly made through social media
(e.g. Twitter, https://twitter.com/), crowd sensing (e.g. citizens equipped with smart-
phones can report about local conditions using dedicated applications) and online
mapping tools (e.g. OpenStreetMap, https://www.openstreetmap.org; Wikimapia http://
wikimapia.org/; Google Map Maker, https://www.google.com.br/mapmaker)[5–7].
Whilst those platforms can be potentially used to provide useful information for
dealing with disaster management, there are still many challenges to be addressed, for
instance: (i) how can people be encouraged to provide valuable information; (ii) how
can information from volunteers be validated; and (iii) how can this information be
integrated with other sources of data [6,8].
Many governments and agencies recognize the opportunities and challenges posed
by informal volunteers, and many have developed strategies and resources for engaging
and managing them. However, organizational culture, risks and liabilities impose
significant barriers to greater involvement of informal volunteers in emergency and
disaster management [2].
Different VGI categories –social media, crowd sensing, and collaborative mapping
activities –require different strategies for promoting citizen engagement. It is our
assumption that knowledge of the VGI categories is relevant for disaster managers to
recruit and motivate users to utilize VGI-systems.
Additionally, works related to VGI in disaster management focus on production by
volunteers and the use of this information by disaster managers. They disregard the fact
that the production and consumption of VGI should be seen within a communication
process, i.e., the communication among the stakeholders should be multidirectional.
To help fill this gap, we present in this paper a preliminary set of key factors to help
promote the involvement of volunteers in the disaster management domain. These
factors were derived from review of CE literature and from an analysis of lessons
learned from a simulation exercise carried out in context of the EU-project “DRIVER –
Driving Innovation in Crisis Management for European Resilience”. The DRIVER
project was launched in May 2014. This project, gathers the expertise of 37 organi-
zations, and will jointly develop solutions for improved crisis management. Repre-
sentatives from the security and defense industry, research and academia, SMEs,
end-users and several European institutions, from 13 EU member states and 2 asso-
ciated countries participate in this innovative venture.
With this work we aim to answer the following research question:
RQ. What factors should be considered by disaster managers to improve the
involvement of digital volunteers?
The remainder of this paper is organized as follows. First, in order to set a ground
on the different VGI approaches an overview is presented in Sect. 2. In Sect. 3we
present a review on the motivation and engagement of digital volunteers. In Sect. 4we
Improving the Involvement of Digital Volunteers in Disaster Management 215

present factors to improve citizen engagement, based on lessons learned from an
experiment on interaction with citizens carried out in context of the EU-project.
Finally, in Sect. 5, we conclude with final remarks and give potential directions for
future works.
2 Volunteered Geographic Information
2.1 Volunteered Geographic Information VGI Source
In general, VGI in the context of disaster risk management can be collected through
different collaborative sources [6]: (i) social media; (ii) crowd sensing; and (iii) col-
laborative mapping activities.
The first category of geo-information (i) involves the use of existing social media
platforms to exchange information in an unstructured way. These platforms enable
citizens to share self-produced content within a network of contacts or for the general
public [6]. Common social media platforms include Twitter; Facebook, https://www.
facebook.com/; Flickr, https://www.flickr.com/; YouTube, https://www.youtube.com/.
The second category of geo-information (ii) relies on citizens on the Web or
equipped with smartphones to act as sensors and share observations [6,10]. The term
‘crowd sensing’is used to describe approaches that make use of specific software
applications to provide more precise structured data [6]. Ushahidi-based platforms and
mobile applications are the most commonly used in this category for data collection.
GDACSmobile, for instance, is a tool that facilitates the self-organization of volunteers
and improves the situational awareness of citizens by sharing an easy-to-understand
overview of the state of affairs. At the same time, GDACSmobile also provides a
feedback mechanism to the crisis manager/control center [11].
The third category of geo-information (iii) consists of a specific type of information
and collaboration platform: the collaborative editing of geographic features to fulfill
internet-based interactive maps. Well-known platforms like OpenStreetMap (OSM),
Wikimapia and Google Map-Maker fall into this category [6].
Collaborative mapping activities are essential for disaster management, because they
collect a very specific type of data –namely, georeferenced data about features like
streets and roads, buildings etc. –and structures this information in the form of a map
[23]. The OpenStreetMap (OSM) project has great potential in disaster scenarios, which
was shown when a large number of volunteers provided their support in mapping events
after the 2015 Haiti earthquake [26,27] and the 2015 Nepal earthquake [23]. Collab-
orative mapping in OSM has emerged as a key mechanism through which individuals
can provide information about affected areas, thus making a tangible difference to aid
agencies and relief work without actually being physically present on-site [23].
2.2 VGI Types
Senaratne et al. [12], categorize the main types of VGI as (i) text-based VGI, (ii) im-
age-based VGI, and (iii) map-based VGI.
216 R. dos Santos Rocha et al.

Text-based VGI is generally produced implicitly on portals, such as Twitter or
various blogs, where people contribute geographic information in the form of text by
using smartphones, tablets etc. [12]. Twitter, for example is used as an information
foraging source [12,13]
Image-based VGI is generally produced implicitly within portals such as Flickr,
Instagram, etc., where contributors take pictures of a particular geographic object or
surrounding with cameras, smart phones, or any hand held device, and attach a
geo-spatial reference to it [12].
Map-based VGI covers all sources that include geometries as points, lines, and
polygons, which are the basic elements to design a map. Among others, OSM,
Wikimapia, Google Map Maker, and Map Insight are examples of map-based VGI
projects [12].
Table 1presents the relationship between sources and the different types of VGI.
2.3 Typology of VGI
Craglia et al. [3] introduced the concept of typology in VGI. According to these
authors, there are two modes through which individuals or communities contribute
such information: first, the way the information was made available and second, the
way geographic information forms a part of it.
Each of these two dimensions can be ‘explicit’or ‘implicit’, with explicit denoting
that the dimension is of primary concern to the piece of VGI, while implicit denotes
that the dimension was not originally an integral part, and is of secondary concern [3].
Thus the topology of VGI proposed by Craglia et al. [3] is a matrix of four types of VGI
as shown in Table 2.
Table 1. A summary of the source and types of VGI
Source Type
Text Image Map
Social media X X
Crowd sensing X X
Collaborative mapping X
Table 2. Typology of VGI [14] (adapted from Craglia et al. [3])
Geographic information
Explicit Implicit
Explicitly
Volunteered
“True”VGI, e.g., OpenStreetMap Volunteered (geo)spatial.
Information, such as Wikipedia
articles about non-geographic topics
containing place names
Implicitly
Volunteered
Citizen-generated geographic
content (CGGC), e.g., Tweets
referring to the properties of an
identifiable place
User-Generated (geo)Spatial Content
(UGSC), such as Tweets only
mentioning a place in the context of
another (non-geographic) topic
Improving the Involvement of Digital Volunteers in Disaster Management 217

Geographic location is essential in disaster analysis [14]. Thus, only the explicit
geographic category –explicitly- or implicitly-volunteered information –of the VGI
typology is used in this paper.
Nevertheless, the typology of VGI proposed does not take in account the fact that
different VGI types have different translation needs, which this may imply excess noise
(e.g., many useless messages before a useful message to be found). For example, a
picture of a flooded area is more effective (i.e., it has less translation needs) for disaster
managers than a short message (tweet) describing the same flooded area.
Considering this aspect, we propose a new typology of VGI, which considers
different levels of uncertainty –noise and translation needs. As can be seen, the explicit
VGI sources –crowd sensing, and collaborative mapping activities –have fewer
translation needs than social media data (Fig. 1).
3 Motivation and Engagement of Digital Volunteers
A Digital volunteer or a digital humanitarian is an individual that applies and leverages
their technical skills in collecting, processing and managing data in support of response
efforts for disasters [30]. In most cases, he/she is not physically present at the place
where the disaster has occurred. The Digital Humanitarian Network (DHNetwork)
grew out of this ecosystem of emerging technical volunteer involvement based
throughout the globe [29]. Since the 2010 Haiti earthquake, these communities have
provided support to formal humanitarian operations [27], and more recently have
provided a crucial compliment to operational organizations and governments active in
the field [29].
Fig. 1. Typology of VGI considering different levels of uncertainty - noise and translation needs
218 R. dos Santos Rocha et al.

However, it is still a challenge to keep digital volunteers motivated and engaged for
longer periods, especially considering that they do not have strong connections to
events due to their digital presence instead of physical presence in affected areas. This
requires different ways to motivate and engage them to provide high quality contri-
butions in future crisis/disaster situations.
To deal with this critical issue, we propose in this section a first attempt to
understand how motivation of digital volunteers can be understood using, for instance,
the Valence, Instrumentality, Expectancy (VIE) approach [17].
In general, volunteers are motivated by many incentives. Examples include, ide-
ology, personal satisfaction, community, and humanitarian values. Particularly, in the
context of a digital humanitarian, there is another factor that should be considered: the
desire to apply and improve technical knowledge. Considering that many of these
volunteers come from open source communities [28], why is it so important to
understand the incentives of citizens in order for them share their observations from the
field? Considering the 90-9-1-Rule [31], there is a so called “participation inequality”.
According to this rule, in a collaborative online environment, 90% of the participants of
a community only view content, 9% of the participants edit content, and only 1% of the
participants actively create new content [31].
In addition to such factors, it is important to understand two specific questions:
(i) why does a citizen report an observation from the field, and (ii) does the information
reported supports the decision making of disaster managers.
The first question is related to behavioral aspects, i.e., what are the incentives of
citizens in order for them to want to share their observations from the field? Literature
commonly understands incentives as instruments influencing the behavior of members
of an organization or community in order to adapt to the organization wide system of
objectives [18]. By creating incentives, certain desired modes of behavior from indi-
viduals are promoted, enabling specific situational conditions which in turn result in the
activation of individual motives. In this case, a motive denotes a time-invariant psy-
chological disposition, i.e. an isolated, not yet activated incitement for the behavior.
Capelo et al. [28] highlight some important incentives:
–Encourage volunteers by giving feedback, recognition, appreciation and gratitude;
–Cultivate a sense of ownership and accountability. Team members have to know
that they matter, and that they are making a difference in the humanitarian
operation;
–Generate a feeling of inclusivity based on a system of collaboration, partnership and
sharing with multiple stakeholders;
–Provide training and capacity-building opportunities for volunteers.
The second question is related to the contribution of effort input. For instance, the
reporting of a flooded road is higher, if the reporter (or citizen) is affected or not.
According to the VIE approach [17], the effort input of an individual is high when it
expects that the contribution will yield results, which are first important to the orga-
nization or community, secondly, due to the expected instrumentality, show close
relationships to individually aspired results from extrinsic incentives, and thirdly
exhibit valences as high as possible.
Improving the Involvement of Digital Volunteers in Disaster Management 219

4 Lessons Learned to Improve the Involvement of Volunteers
In this section, we summarize the lessons learned to improve the involvement of
volunteers in the production of high-quality relevant information for disaster man-
agement. The elements presented here were derived from the VGI and citizen
engagement literature reviews, as well as the analysis of lessons learned from a field
experiment carried out in the EU-funded demonstration project DRIVER.
The selection process of the literature was based on the experience of the authors of
this paper. Regarding the VGI literature, four main works were selected as an input to
identify the main characteristics that may affect the digital volunteers’engagement:
Albuquerque et al. [6], Craglia et al. [3], Klonner et al. [14], Senaratne et al. [12].
Regarding motivation and engagement of volunteers, we selected Nielsen [31], Lawler
[17], and Capelo et al. [28] to understand the main aspects that should be considered in
the digital volunteers’engagement.
The field experiment was based on a storyline designed by practitioners. They
defined a fictitious disaster event based on past experience, which resulted in a more
realistic and relevant scenario compared to a more tool-friendly situation designed by
the tool providers. The experiments conducted in the DRIVER “Interaction with
Citizens”campaign concentrate on the following functions (a more detailed description
of this experiment can be founded in Havlik et al. [33], Middelhoff et al. [32] and van
den Berg et al. [22]):
–Provision of context-aware and timely information tailored to the specific needs of
different societal groups over various channels, in order to improve their under-
standing of the crisis situation and to minimize adverse impacts.
–Context-aware (micro-) tasking of non-affiliated volunteers to perform real and
virtual tasks.
–Efficient gathering of situational information about an incident from volunteers.
–Efficient usage of received information from volunteers to improve the situational
awareness of crisis managers and consequently their handling of the cri-sis.
In the following subsections, we will summarize the findings into two categories:
(i) characteristics of VGI, and (ii) communication processes.
4.1 Characteristics of VGI
The characteristics of VGI –origin, type and typology –shown in Sect. 2have an
impact on citizen engagement.
In regard to the origin of VGI, crowd sensing and collaborative mapping activities
have the potential to promote citizen engagement, due the ways in which the infor-
mation is created.
Thus, we propose a typology of engagement based on five levels of involvement
from volunteers in scientific work [20] and a typology of participation proposed by
Pretty and Hine [21]. At the first level, citizens provide resources, while having only a
minimal cognitive engagement. This level is called ‘basic’. In second level, ‘distributed
intelligence’relies on the cognitive ability of the participants. After some training, the
participants collect data or engage in minor interpretation activities. At this level,
220 R. dos Santos Rocha et al.

quality evaluation by the volunteers is crucial. The third level represents ‘participatory
engagement’, where users take part actively in the problem definition and data col-
lection. On the last level, ‘self-mobilization’, non-professionals collaborate with pro-
fessionals, and together, decide on a problem they want to focus on and the methods for
data collection. This allows for both the consideration of interests and motivation of the
volunteers. On this level, volunteers are not only experts, but also have the role of
facilitators [14,20].
As shown in Table 3, social media presents a ‘basic’level of engagement. This is
because of the nature of its contribution, i.e., social media is provided implicitly. All
other VGI sources, provided explicitly, require different strategies for citizen engage-
ment, since many have volunteers with different levels of knowledge and motivation.
4.2 Communication Process
The elements in the communication process determine the quality of communication.
A problem in any one of these elements can reduce communication effectiveness [15].
For instance, different perceptions of the message, language barriers, interruptions,
emotions, and attitudes can all reduce communication effectiveness. Therefore, a
feedback mechanism should be considered to promote the involvement of volunteers.
The existing literature on VGI focuses on the production of geographic informa-
tion, and the use of this information by disaster managers. It disregards the fact that the
production of VGI should be seen within a more effective communication process, i.e.,
the communication among the stakeholders should have to include a mechanism for
continuous feedback.
In the context of the DRIVER Project, tools were proposed that should address both
objectives for the benefit of the community, and for individual members of the pop-
ulation according to the VIE approach. In a recent field exercise, the software tool
GDACSmobile was used to communicate observations to crisis mangers
(community-objective). The personal objectives of members of the population were
addressed by sharing reports with the community as an information layer on a map of
the environment around the user. In this way, the users could assure themselves of their
safety in the situation and strengthen their situational awareness using map
representation.
Table 3. Typology of engagement
Typology of VGI Levels of
engagement
Source Explicitly Implicitly I II III IV
Social media X X
Crowd sensing X X X X X
Collaborative mapping X X X X X
Legend: I-Basic. II-Distributed intelligence. III-Participatory
engagement. IV-Self-mobilization
Improving the Involvement of Digital Volunteers in Disaster Management 221

Consequently, by acknowledging the perceptions of community members, a
common language visualizing interactions becomes a basic requirement for an
appropriate crisis communication environment. One way to establish a common lan-
guage is to use VGI systems in combination with commonly used information cate-
gories and according pictograms [22]. In the meantime, many different VGI tools are
available, having different pros and cons regarding particular tasks. However, as
mentioned above, the main challenge here is less a technical problem, but rather an
organizational one. According to the discussion on incentives, we identify a trustful
and open solution as most appropriate. However, it must be able to visualize benefits
for the community, i.e. an easy- and fast-to-understand situation overview including a
connection to responding authorities. In order to do so, the information should be
structured and visualized respecting the communities’attributes (like age distribution,
language, technical affinity, etc.).
5 Conclusion
Further research is still necessary for engaging volunteers in the production of
high-quality relevant information for disaster management. For instance, how can we
ensure that local communities are involved at a meaningful level in different phases of a
disaster? This could be achieved, for instance, by initiating a community group or by
providing training to volunteers to produce high-quality VGI. Moreover, how to
improve collaboration between formal humanitarian organizations and volunteer
technical communities (VTCs) should also be explored in future works.
Additionally, the different VGI categories require different strategies for promoting
citizen engagement, given that the knowledge of the VGI categories is relevant for
disaster managers to recruit and motivate users to utilize VGI-systems. Therefore, one
of the expected outcomes will be the development of a new framework for promoting
engagement of digital volunteers in the disaster management context.
Acknowledgments. The research that led to this work was funded by the European Commu-
nity’s Seventh Framework Programme: Marie Curie Actions/Initial Training Networks under
grant agreement n° 317382 and FP7/ 2007-2013 under grant agreement n° 607798. João Porto de
Albuquerque is grateful for the financial support from the CAPES Pró-Alertas (grant nº
88887.091744/2014-01 and nº88887.091743/2014-01). The authors would like to thank Robin
Mays and Lívia Degrossi for their helpful comments and suggestions, and the DRIVER
“Interaction with Citizens”experiment team that has been working together for several months in
order to prepare, conduct and finally assess the field exercise in The Hague.
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