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Abstract

The immediacy of locational information requirements and importance of data currency for natural disaster events highlights the value of volunteered geographic information (VGI) in all stages of disaster management, including prevention, preparation, response, and recovery. The practice of private citizens generating online geospatial data presents new opportunities for the creation and dissemination of disaster-related geographic data from a dense network of intelligent observers. VGI technologies enable rapid sharing of diverse geographic information for disaster management at a fraction of the resource costs associated with traditional data collection and dissemination, but they also present new challenges. These include a lack of data quality assurance and issues surrounding data management, liability, security, and the digital divide. There is a growing need for researchers to explore and understand the implications of these data and data practices for disaster management. In this article, we review the current state of knowledge in this emerging field and present recommendations for future research. Significantly, we note further research is warranted in the pre-event phases of disaster management, where VGI may present an opportunity to connect and engage individuals in disaster preparation and strengthen community resilience to potential disaster events. Our investigation of VGI for disaster management provides broader insight into key challenges and impacts of VGI on geospatial data practices and the wider field of geographical science.
Article title: A review of Volunteered Geographic Information for Disaster
Management
Author(s): Billy Haworth1, 2, Eleanor Bruce1
Affiliation: 1School of Geosciences, The University of Sydney, Sydney, Australia
2 Bushfire and Natural Hazards Cooperative Research Centre, Melbourne, Australia
Correspondence address / email address:
Mr Billy Haworth
Room 419, Madsen Building, The University of Sydney
Sydney, NSW 2006, Australia
E: billy.haworth@sydney.edu.au
1
A review of Volunteered Geographic Information for Disaster Management
Abstract:
The immediacy of locational information requirements and importance of data currency for
natural disaster events highlights the value of volunteered geographic information (VGI) in
all stages of disaster management, including prevention, preparation, response, and recovery.
The practice of private citizens generating online geospatial data presents new opportunities
for the creation and dissemination of disaster-related geographic data from a dense network
of intelligent observers. VGI technologies enable rapid sharing of diverse geographic
information for disaster management at a fraction of the resource costs associated with
traditional data collection and dissemination, but they also present new challenges. These
include a lack of data quality assurance and issues surrounding data management, liability,
security, and the digital divide. There is a growing need for researchers to explore and
understand the implications of these data and data practices for disaster management. In this
article we review the current state of knowledge in this emerging field and present
recommendations for future research. Significantly, we note further research is warranted in
the pre-event phases of disaster management, where VGI may present an opportunity to
connect and engage individuals in disaster preparation and strengthen community resilience
to potential disaster events. Our investigation of VGI for disaster management provides
broader insight into key challenges and impacts of VGI on geospatial data practices and the
wider field of geographical science.
Keywords: disaster management, volunteered geographic information, VGI, emergency
management, disaster communication, geospatial data
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Introduction
Natural disaster events, such as the recent Typhoon Haiyan in the Philippines, floods and
bushfires (wildfires) in Australia, or Hurricane Sandy in the United States, remind us of the
importance of geospatial data and the need for timely and reliable communication in all
aspects of disaster management. New opportunities for the creation and dissemination of
important disaster-related geographic data from a dense network of intelligent observers are
now provided through online user-generated geospatial data termed volunteered geographic
information (VGI) (Goodchild 2007; Elwood et al. 2012). Like geographical information
systems (GIS), VGI involves the sharing and mapping of spatial data, however through
voluntary information gathered by the general public. Though, extant debates question the
appropriateness of the adjective ‘volunteered’ noting differences between crowdsourced data
that is actively contributed with the individual’s awareness and user-generated data that is
harvested otherwise (Harvey 2013; Stefanidis et al. 2013). Similarly, definitions of the
‘general public’ and who produces VGI are often blurred (Budhathoki et al 2008), with
contributions coming from disparate sources (Haklay 2013a; Coleman et al. 2009; Schlossber
& Shuford 2005). VGI represents various opportunities and threats for traditional data
production systems, as summarised by Genovese and Roche (2010), some of which are
particularly relevant to disaster management, including the opportunity for citizens to actively
contribute to public issues with personal local knowledge and the threat that VGI may reduce
the importance of authoritative mapping.
Disasters create a time-critical need for geographic information that is unlike the normal pace
with which geographic information was traditionally acquired, compiled, and disseminated,
and VGI is ideally suited to fill the need for near real-time information (Goodchild &
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Glennon 2010). Management of disasters follows the four phases of the disaster lifecycle:
prevention, preparedness, response, and recovery (PPRR) (Abrahams 2001; Zakour &
Gillespie 2013; Crondstedt 2002). Reduction of negative impacts of disasters requires
improving approaches in all four phases (Zakour & Gillespie 2013). Through rapid exchange
of geographic information between authorities and citizens for disaster response, and
promoting connectedness and community engagement in disaster preparation practices, VGI
can contribute to all phases of disaster management. Further, digital humanitarianism can
add to traditional systems with techniques such as crowdsourcing, remote volunteer
collaboration, and ‘crisis mapping’ (Burns 2014b). Authorities and individuals are already
exploiting VGI technologies, both for communicating disaster-related information (see
Taylor et al. 2012; Bird et al. 2012; St. Denis et al. 2012) and for collating and mapping
relevant geospatial data (see Meier 2012; Ziemke 2012; McDougall 2011; Liu & Palen 2010).
This has created a new landscape of geo-data production and knowledge sharing for disaster
management, generating a need for researchers to explore and detail the implications of these
data and data practices.
This article aims to review the current state of research in this field. The intent of this paper
is not to exhaustively document all related literature, but to offer a context for future thinking.
An outline of key themes in VGI and disaster research is presented here, with emphasis on
present limitations and potential areas for further geographical enquiry. We acknowledge
that this review emphasises the post-disaster application of VGI over prevention and
preparedness. This is a product of the current state of academic literature in this field and is
in itself an important finding which we discuss later in the paper.
The VGI phenomenon may be one of the most important to impact the discipline of
geography in recent years, and the associated changes in the production and sharing of
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geographic information are not just pertinent to the field of natural disasters, but also the
broader discipline of GIScience, with geographers in a unique position to examine the
impacts of VGI (Elwood et al. 2012).
A brief background to VGI and disasters
VGI is defined as the widespread engagement of large numbers of public citizens in the
creation of geographic information (Goodchild 2007). User generated content (UGC) is
exemplified by social media sites such as Twitter and Facebook, and VGI in this context is
that subset of UGC that contains a geographic reference, either explicitly or implicitly
(Craglia et al. 2012; Elwood et al. 2012). The voluntary nature of data production
distinguishes VGI from other spatial UGC (Elwood et al. 2012). Efforts to theorise why
individuals volunteer information (see Poser & Dransch 2010; Goodchild 2007; Haklay
2013a; Budhathoki & Haythornthwaite 2013; Starbird & Palen 2011) note that motivations
for volunteering or withholding will shape the dynamics of inclusion and exclusion in VGI
development and influence data content (Elwood 2008b; Leszczynski 2012; Thatcher 2013;
Stephens 2013).
Recent spatially enabling technologies including Web 2.0, georeferencing, geotags, global
positioning systems and broadband communication have enabled mass proliferation of UGC
via the internet and allowed citizens to produce maps using free or inexpensive online
resources, giving rise to VGI (Goodchild 2007). Further, smartphones equipped with
location and data recording sensors have enabled near-instant geospatial data collection and
dissemination using mobile platforms (Raento et al. 2009; Lane et al. 2010).
The ease of volunteers to create and publish geographic information combined with the need
for rapid communication during crisis events has created a new disaster management context
(Goodchild & Glennon 2010; Wald et al. 2011). Emerging social media platforms are
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changing the way people create and use information for crisis events (Ostermann & Spinsanti
2011; Liu & Palen 2010) with significant increases in the uptake of internet-based
communication technologies reported during recent disaster events (e.g., Fraustino et al.
2012).
The growth of VGI has begun to transform not only practices of technology use for disaster
communication, but also attitudes towards the value of user-generated online geospatial data
and technologies. For example, in response to flooding in Queensland in 2011, the
Australian Broadcasting Corporation utilized data volunteered online by citizens to produce
maps of crisis incidents in what was referred to as “an experiment in gathering information
from the community” (Middleton 2011). In contrast, responding to bushfires in January
2013, the New South Wales Rural Fire Service Commissioner urged “people to stay plugged
into social media” (AAP 2013). This reference from authority to social media as a source to
trust for crisis information came just two years after it was referred to as experimental,
emphasizing the recent and rapid emergence of VGI technologies in the emergency response
space. This shift reflects the growing number of citizens seeking to access online
technologies for sending and receiving disaster information, and in turn the response, and
often expectation, of many official agencies to exploit these technologies for connecting with
citizens (e.g. St. Denis et al. 2012).
The era of ‘big data’ defined by the exponentially increasing “volume, velocity and variety”
of data (McNeely and Hahm 2014) has also resulted in the emergence of new tools for data
curation, management and analysis (Fischer 2012; Kitchin, 2013) with significant potential
for disaster management. Although VGI contributes to only one of the three categories of big
data sources identified by Kitchin (2013), directed, automated and volunteered, the myriad of
challenges and vulnerabilities presented by big data have implications for the application of
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VGI in disaster management. In supporting disaster management, methods for big data
analytics need to optimize the collation of contextual information, contribute to
understanding causal mechanisms, and recognize the underlying social processes that are not
easily represented, characterised or interpreted using big data technologies.
As individuals and authorities continue to utilize VGI for disaster management, important
challenges need to be overcome. In the following sections we present discussion on key
issues for the uptake of VGI in disaster management, including questions of data collection
and dissemination, data quality and security, data management, and the notion of
empowerment.
Data collection and dissemination
The emergence of VGI has created a new platform for collection and dissemination of
information for disaster management. Authorities can now rapidly communicate important
time-critical geographic disaster-related information directly with the public at a fraction of
the logistical and resource costs of traditional communication methods. VGI also presents
unique ways for the general public to contribute and map important geospatial information
for crisis management and engage directly with authorities and each other in alternative ways,
even if they are located outside the potentially affected areas (see Meier 2012; Crowley &
Chan 2011; St. Denis et al. 2012).
The internet is well structured to facilitate collaboration among individuals, thus increasing
utilization of knowledge assets by reducing limitations such as high costs associated with
traditional geographic information production (Flanagin & Metzger 2008; Meier 2012). The
collection of large amounts of near real-time information by individuals at the disaster
location (Gao et al. 2011), and the dissemination of information from relief agencies (Abbasi
et al. 2012) have been shown to be critical for effective response efforts. VGI postings were
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demonstrated to provide an alternative to official sources during the Santa Barbara wildfires
of 2007-2009 with significant time efficiency in the collation and sharing of information
(Goodchild & Glennon 2010). A shift away from traditional cartographic practices and
protocols has important implications for information contributions during disasters and the
role of geographic information producers. The production of disaster-related information is
no longer simply an expert’s game for those organizations that can resource the acquisition of
authoritative data. The emergence of VGI has enabled anybody with access to the
technology to contribute in a new disaster management context that has seen knowledge-
users become knowledge-producers, or “produsers” (Coleman et al. 2009; Budhathoki et al.
2008).
There is value in the depth of information and immediacy gained through people from a
breadth of backgrounds contributing and disseminating disaster related information. This was
emphasized during the 2007-2009 Santa Barbara wildfires (Goodchild & Glennon 2010) and
the 2010/2011 Queensland floods (McDougall 2011). The Queensland flood events were
characterised by an unprecedented use of social media to report incidents as they happened
(McDougall 2011; Bird et al. 2012), and flood extent mapping for rudimentary post disaster
assessment was enabled by VGI through geotagged images and social media content. VGI
contributors with personal cameras and mobile phones often have the advantage of being in-
situ at the disaster location capturing near real-time data without the constraints associated
with other forms of technology, such as cloud-obscured satellite imagery (Triglav-Čekada &
Radovan 2013).
Sharing content online facilitates fast and broad information mobility. VGI collection and
dissemination through social media in particular has an inherent ability to promote or
propagate messages (e.g., Gao et al. 2011). During the 2010/11 Queensland floods a high
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level of re-sharing of social media posts was reported, particularly of those publically
expressing gratitude for emergency services, even well beyond the disaster, indicating a
significant form of emotional engagement with the acute event (Shaw et al. 2013).
Technologies and the capacity to spread individual information are allowing individuals to
engage, and remain engaged, with crisis events in unprecedented ways. For disaster
recovery, there is a need to consider how this new context of engagement may impact the
efforts of individuals to recover or ‘move on’ following a disaster.
It is important to recognise that the same mechanisms enabling messages of support and
emergency information to be shared widely and quickly can also work to propagate
misinformation, malicious and/or false content. This issue needs to be understood in the
broader context of traditional geospatial data dissemination and efforts should be made to
comprehend how these new data sharing practices are impacting the veracity of geographic
information as it proliferates through the online arena.
Data quality and security
Security and data quality are major concerns for VGI. Individual’s physical and online
security may be compromised by utilising low-quality VGI. Data from (often) untrained
individuals with varying agendas and experience often suffers from an absence of quality
assurance (Goodchild & Li 2012). Studies have highlighted the importance of data
verification by reporting on issues of quality control, misinformation, spurious or fraudulent
postings, duplicate and doctored images, and the lack of ‘right’ information for disaster relief
(see McDougall 2011; Bird et al. 2012; Fraustino et al. 2012; Ostermann & Spinsanti 2011;
Gao et al. 2011; Triglav-Čekada & Radovan 2013). Despite these concerns, it has been noted
that in some contexts, such as the 2010 Haiti earthquake which occurred with a void of
quality authoritative geospatial data, crowdsourced maps produced with volunteered data can
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be the most comprehensive and up-to-date information available (Meier 2012; Crowley &
Chan 2011). In this section issues of data quality and security are discussed with particular
reference to credibility. We then outline and critique reasons why VGI has been recognised
for its capacity to complement authoritative datasets.
The lack of adequate security features associated with VGI is a concern pertinent to natural
disaster management (Gao et al. 2011; Shanley et al. 2013). The nature of VGI is that it is
often made openly available to the general public. Data of this nature may be particularly
compromising during a disaster event, especially when those affected are at their most
vulnerable and privacy may be less of a priority than in ‘normal’ circumstances (Crawford &
Finn 2014). For example, a geotagged image of a disaster impacted property provides useful
information to emergency authorities if shared through social media, but that same locational
information about a vulnerable and potentially vacant property may also be available to those
with malicious intent. In the hostile environment of the 2011 humanitarian crisis in Libya,
two crowdsourced maps were produced to mitigate security issues; one was password
protected for humanitarian workers, and the other contained heavily edited information for
the public on a 24-hour time delay (Meier 2012). Crawford and Finn (2014) assert that while
it could be assumed people can manage their own privacy settings on public platforms, many
are not well-informed about who can access the data they contribute.
Furthermore, authorities acting on information posted by members of the public, without
credibility assurances, may potentially be exposed to risks beyond those already associated
with the hazard event (Shanley et al. 2013). Goolsby (2013) argues disaster responders, relief
workers, and digital volunteers who provide support for crisis events should be particularly
cautious in regards to social media as a source of VGI. In a study of information posted on
Twitter during various high impact events, Gupta and Kumaraguru (2012) showed just 17%
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of event-related tweets contained credible information, while 13.5% was spam (the rest was
either not credible or event-related but not useful, i.e. personal opinions). Uncertainty
surrounding credibility of online data and data sources is contiguous with uncertainty
surrounding online security. Anxiety associated with data security and privacy of
volunteered information may prevent individuals from contributing during a disaster and may
limit the uptake and capabilities of the technologies for official emergency agencies (Shanley
et al. 2013; Crowley & Chan 2011).
Credibility of data and data sources is thus a concern for VGI in disaster management.
Flanagin and Metzger (2008) highlight the difficulty in locating and authenticating digital
information sources and the lack of quality control standards as key issues for credibility. By
making it possible for more people from a diverse range of groups to produce more data in
digital form, the heterogeneity and sheer volume of information and information sources has
increased (Flanagin & Metzger 2008; Elwood 2008b; Crowley & Chan 2011), and Callister
(2000) argues standard conventions for determining credibility break down in cyberspace.
How can such vast amounts of data from non-experts, following no institutional or legal
standards, be trusted as credible, particularly in the case of emergencies? Though limited by
using Twitter data in isolation, Castillo et al. (2013) describe features that may be effective
for automatically classifying microblog posts as credible or not with emphasis on information
posted during natural disasters, showing that credible posts tend to be longer, contain a URL,
and are questioned less by other users.
Data may contain false positives and negatives (Goodchild & Glennon 2010). For example, a
hypothetical oil spill may cause a false positive with an untrue rumour of the chemical spill,
or a false negative through absence of information about the spill’s existence (Goodchild &
Glennon 2010). Information about the spill is time-critical and delay in its availability
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amounts in effect to a false negative. A false positive may result in unnecessary evacuation.
However, if the event was true and people were to wait for official information, the delay
could have life threatening consequences and constitutes high risk. This is not to argue false
positives are preferable to false negatives. There are substantial costs to false positives,
including the resource costs and danger involved in evacuation, and the weakening of
confidence in the system reducing the effectiveness of future true positives. We argue that
regardless of use, quality of VGI for disaster management applications is a serious and
potentially life-threatening issue, whether false positive or negative.
Some have argued that VGI may approach the quality standards of authoritative data, offering
various justifications (see Goodchild & Li 2012; Goodchild & Glennon 2010). First, sites
such as Wikipedia provide evidence that crowdsourcing is an effective mechanism for
eliminating propagation of erroneous information via masses of individuals submitting and
reading information (Giles 2005). But what threshold volume of contributors is required for
the source to be deemed accurate? Linus’ Law, which implies that by having more observers
fewer errors go unnoticed and data is improved, has been shown to apply to OpenStreetMap
(Haklay et al. 2010). But Haklay et al (2010) could only speculate on VGI more broadly and
focused on positional accuracy without considering other aspects of data quality, such as
attribute accuracy or the currency of VGI sources. Application of Linus’ Law to VGI is
problematic for incidents that are obscure, such as those that persist for only a short period of
time, which is the nature of many disaster-related incidents (Goodchild & Li 2012). If the
‘wisdom of the crowds’ can eventually filter out false information, this may happen too late
in a time-critical situation like a disaster event (Spinsanti & Ostermann 2013). In addition, is
there potential for mass contributions to encourage ‘group think’ and propagation of
misinformation (Murdock 2011)? By its nature UGC broadly is incomplete and despite very
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large volumes of data bias is not removed (Hollenstein & Purves 2010; Purves 2011; Graham
2010; Stephens 2013; Burns 2014a; Crawford & Finn 2014).
Second, geographic information is rich in context (Goodchild & Glennon 2010). In the
context of Tobler’s first law (Miller 2004), which states that any location is likely to be more
similar to its surrounds than distant things, geographically inconsistent information stands out
as erroneous. Tobler’s law suggests that information about a location should be consistent
with what is already known about the location’s surrounding area (Goodchild & Li 2012).
Report of a bushfire, for example, is more likely to be true if fire has recently been described
nearby.
Third, Goodchild and Glennon (2010) report currency is a feature of accuracy. Rapid
generation of VGI has potential to capture changes in landscapes as they occur, which is
unachievable with the lengthy delays associated with traditional map production. Thus data
that has currency is potentially more reliable in the sense that it is more up-to-date. But does
currency of data indicate accuracy in the form of ‘correctness’?
Fourth, advances in positional technology and increase in the ubiquity of technologies that
give the average person access to geographically-referenced data production may increase
data quality. But this does not conclusively eliminate human error. There is no guarantee
users consistently operate equipment correctly (for example, use of appropriate map datum
settings) or that they are necessarily aware when the technology is not operating properly. As
researchers continue to seek new applications for these data, innovative methods are needed
for empirical validation of the quality and credibility of VGI.
Data management
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Data from the general public presents a number of challenges for data management which are
particularly relevant to disaster management. Key issues include data filtering and
verification with increased volumes of data and data sources, the place for VGI in spatial data
infrastructures (SDIs), and issues of liability surrounding the use of UGC.
The sheer volume of information provided through VGI is a current obstacle to its efficient
use in emergency management, highlighting the need for effective methods to mine, filter,
verify and summarise these data and data sources to ensure credible and relevant content
(Bakillah et al. 2014; Spinsanti & Ostermann 2013; Crowley & Chan 2011; Graham 2010).
Verifying data accuracy and the potential value of information for a range of purposes under
the time-critical and rapidly changing circumstances of a disaster scenario presents
significant challenges. Spinsanti and Ostermann (2013) incorporate the knowledge of experts
for refining UGC. They present a prototype system to retrieve, process, analyse and evaluate
social media content on forest fire using expert input to establish key words, contextual
information and spatio-temporal clustering parameters (Spinsanti & Ostermann 2013). Gao
et al. (2011) note the ability of social media tools to allow for rudimentary analysis and
summaries to help observe trends and partition data into pre-determined most-urgent
categories during disasters, such as medical assistance requests or trapped persons. Social
media technologies have the ability to coordinate widespread communication and strengthen
information flows, but also to adapt in real time to changing needs of those affected by the
disaster (Yates & Paquette 2011).
Traditionally, SDIs are not premised around the need to handle UGC, and SDIs’ top-down
model of supporting digital data access, storage, and sharing is unlike the bottom-up
approach on which VGI is established (Craglia 2007; Gould 2007; Elwood 2008a, b; Díaz et
al. 2011; Duce & Janowicz 2010). VGI represents a departure from the assumption with
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contemporary SDIs that formal organizations are the producers of geospatial information and
users are the passive recipients (Budhathoki et al. 2008). Budhathoki et al. (2008) argue for
reconceptualization that sees production expanded from expert organizations to user
organizations and individuals, establishing two-way interaction and blurring the boundary
between producers and users. The sharing and availability of VGI within mainstream SDIs
may improve traditional geospatial analysis and decision support tasks (Díaz et al. 2011).
Genovese and Roche (2010), however, argue VGI inclusion in official SDIs may pose a
threat to data integrity. For disaster management, opportunity exists for VGI to augment
existing SDIs, providing valuable localised and contextual information for planning decisions
and encouraging information flow between communities and disaster management
authorities. De Longueville et al. (2010) illustrated how VGI sensing and SDI components
can act as complementary senses for supporting a crisis-related scenario.
Liability questions associated with the use of VGI in authoritative public and private
geographic datasets are among the most paramount (Rak et al. 2012). Due to the higher level
of inherent risk to life and property in disaster management decision making, liability
concerns may deter organizations from integrating VGI into their datasets (Shanley et al.
2013). Who is responsible if harm results from reliance on volunteered information: the
initial contributor; the host or organization responsible for the website or product relying on
VGI; the user? Scassa (2013) argues VGI site operators, users and contributors must all have
some awareness of the legal and ethical issues that may be triggered by their activities,
including issues of intellectual property, liability for faulty information, and defamation.
‘Digital volunteers’ are at risk if they disseminate false information, develop sloppy software,
or fail to use reasonable care, act in a manner comparable with similarly situated individuals,
properly supervise volunteers, or act when they have a duty to do so (Robson 2012; Shanley
et al. 2013). Furthermore, as websites have a global reach and laws vary widely between
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regions, liability risks in and across foreign jurisdictions need consideration (Scassa 2013;
Shanley et al. 2013). Robson (2012) argues that evaluating the precise contours of potential
liability for ‘digital volunteers’ can be difficult because of the novelty of issues and a lack of
court guidance, but many potential liabilities can be mitigated through planning and
organization.
Empowerment through VGI
A loss of empowerment for individuals has been described during disaster events (Bird et al.
2009), and research has suggested VGI technologies can act to empower citizens (Tulloch
2008; Goodchild & Glennon 2010). Empowerment is described as an individual’s capacity to
have control over their personal affairs and confront hazard issues while receiving the
necessary emergency management support (Bird et al. 2009). The notion of citizen
empowerment through VGI must be considered alongside marginalization.
Goodchild and Glennon (2010) argue the average citizen, already equipped with powers of
observation, is now empowered through VGI technologies with the ability to georegister
those observations, transmit them through the internet, and synthesize them into readily
understood maps and reports. But does this indicate VGI can enable individuals to achieve
connectedness, more control, and empowerment in disaster management? Numerous papers
have discussed the concept of empowerment through public participatory GIS (PPGIS)
(Sieber 2006; Harris & Weiner 1998; Elwood 2002), including in natural disaster research
(Kemp 2008; Kienberger 2007). In this context, empowerment is a complex social construct
and political process, whereby its attainment through PPGIS is contingent upon multiple
factors including community make-up, endorsement from local leaders, nature of power
relations and administrative structures within the community (Kyem 2002). The relationship
between VGI and citizen empowerment is similarly complex. Elwood (2008b) claims
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discussions about the societal significance of VGI are similar to ‘GIS and Society’ debates
during the mid-1990s, in which GIS was welcomed by some as a tool for the empowerment
of marginalized individuals and decried by others as a mechanism of exclusion and
disempowerment (Schuurman 2000). Research has similarly considered how VGI may
aggravate existing inequalities and create new forms of exclusion (see Zook & Graham
2007a, b).
While VGI may empower some citizens to contribute and engage in disaster management, it
also acts to marginalize others. If we consider the digital divide (see Van Dijk & Hacker
2003; Chinn & Fairlie 2007; Gilbert 2010; Sui et al. 2013), what is the role of citizens with
limiting socio-economic circumstances or those in parts of the world without access to these
‘empowering’ technologies? Sui, Goodchild, and Elwood (2013) report two-thirds of
humanity does not have access to the rapidly expanding digital world. What contribution
does VGI have to make to disaster management for these citizens? VGI cannot represent ‘the
everybody’ and in fact favours ‘the privileged’, or those with money, access and time to
utilize the technology (Haklay 2013b; Crawford & Finn 2014). Just 36% of the population
had internet access in the Philippines when Typhoon Yolanda struck in 2013, presenting a
partial and skewed picture of the disaster through social media data (Crawford & Finn 2014).
We must recognise that UGC will provide only selective representations of any issue, and
that there will always be people and communities that are missing from the map (Zook et al.
2010; Burns 2014b).
For those that are ‘included’ the use of geospatial data from the crowd has been shown to
enhance existing inequalities. Text messages sent to the Mission 4636 service (Crowley &
Chan 2011; Meier 2012; Ziemke 2012) during the 2010 Haiti earthquake crisis were
translated into English and subsequently mapped and reported in English, preventing the
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Kreyòl speakers who texted for help from accessing the project outputs and benefiting from
their own data, thus reproducing unequal power relations between the poor Haitians and the
rich who acted on the information (Crawford & Finn 2014). Information is often least
available where it is most needed (Sui et al. 2013), and during disasters, those in society
already marginalized are often the most vulnerable (Hewitt 1983b, 1997; Watts 1983). Thus,
a shift in focus to data sources for emergency management that are potentially excluding of
those vulnerable is not plausible. For emergency management, VGI may only be a useful
tool alongside more traditional disaster management methods, and triangulation of various
spatial data sources should remain a goal of any project leveraging UGC (Ziemke 2012;
Hassanzadeh & Nedovic-Budic 2013).
VGI also provides novel capabilities and opportunities for authorities and those undertaking
geographical research. By providing new insight into the complexities of disasters at various
spatial scales, with increased access to important local and community knowledge, VGI can
aid in strategizing and planning for all stages of the PPRR cycle. Studying a community’s
daily life activities and spatial patterns at a local level may be where VGI offers the most
interesting and lasting value to geographers (Goodchild 2007). Material conditions of daily
life prefigure disasters (Hewitt 1983a) and there is little long term value in confining attention
to hazards in isolation from local vulnerabilities and their causes (Blaike et al. 2003). Failure
to include important local data for management of diverse issues over varying spatial scales
and choosing rather to focus on data at broader scales alone can result in ineffective policies
(e.g., Haworth et al. 2013). VGI may also have implications for the perceived value of
geographers. With skills formerly relied on now enshrined in software, the production of
geographic data and knowledge is no longer exclusive to geographers (see NeoGeography, or
“geography without geographers;” Sui 2008; Turner 2006; Liu & Palen 2010; Haklay et al.
2008; Goodchild 2008).
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Future research recommendations
As citizens and authorities continue to embrace VGI for disaster management, researchers
must continue to address important questions surrounding data quality, the social and
institutional implications for adopting UGC, and the overall utility of VGI for all stages of
disaster management. Further consideration needs to be given to best practices for
emergency management agencies to support digital volunteers, and for digital volunteers to
support traditional and authoritative disaster management practices. Burns (2014b) notes that
no formal relationship exists between digital humanitarians and traditional humanitarian
institutions. In this final section we reflect on the existing literature to offer recommendations
for further academic research in the field of VGI and disaster management.
There is limited systematic research on the role of different types of VGI platforms during
disasters. Similarly, comparisons are limited between different types of disasters and whether
or not the disaster type has any influence on VGI usage patterns. Particular research
emphasis should be given to improving data validation and automatic report summation.
Several studies have emphasized the need for further research into VGI verification and
reporting systems for disaster management to assist in addressing data quality and
management issues (see Poser & Dransch 2010; Gao et al. 2011; Abbasi et al. 2012).
Research is needed on more appropriate use of VGI enabling technologies. The inclusion of
geotags in reports from some devices (such as smartphones), for example, can assist in
discriminating between reports based on location and allow for more targeted relief action
and improved spatial planning. However, it has been observed that less than 5% of users
provide location information due to privacy concerns or lack of awareness about the feature
(Abbasi et al. 2012). Murdock (2011) estimates just 1.5% of Twitter posts are geotagged,
proving a major limitation to the geographic application of tweets and an under-
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representation of information. Those posts that are geotagged also pose issues, such as
whether a geotagged image provides the location of the image-subject or of the photographer
(Hollenstein & Purves 2011). Another relevant example is the need for appropriate and
effective use of hashtags for managing large volumes of data on social media (Ziemke 2012).
New methods for encouraging the most effective use of VGI technologies may lead to
increased adoption and improved data accuracy, ultimately increasing capacity for those
seeking to engage VGI for disaster management.
Significantly, we propose research is needed on the role of VGI in the preparation and
prevention phases of disaster management. This review clearly highlights that contemporary
research on the role of VGI in disaster management predominantly focuses on the response
phase of the PPRR cycle. Disaster preparation has been considered through spatial data
technologies such as GIS (Asante et al. 2007; Chou 1992; Atkinson et al. 2010; Atkinson et
al. 2007). But the use of VGI for pre-disaster planning and preparation has not received the
same attention. Burns (2014a) also describes the need for inclusion of preparedness and risk
information in volunteered humanitarian databases. In the preparedness phase of the PPRR
cycle a range of possible events must be analysed for both hazards and vulnerabilities,
providing a useful opportunity for effective risk analysis (Asante et al. 2007). Several
researchers have argued there is potential for social media to assist in building pre-disaster
resilience (Dufty 2012, 2011; White 2012). Boon (2014) reports the most effective
emergency communication is two-way and locally derived, enabling those at risk to obtain
more personalised information and advice about their preparations. Specific local knowledge
shared via a VGI platform may assist individuals and communities better understand local
vulnerabilities and risks, and develop effective planning and response procedures for a
variety of hazards. Directing increased attention to the pre-disaster phases may present an
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opportunity for VGI to foster community engagement and empower individuals to be more
directly involved in risk reduction practices.
Conclusion
Academic commentary on VGI in disaster management is recent; however, a body of work
exists that demonstrates utility and significance. Through VGI vast amounts of diverse, local
knowledge can now be collected and shared for disaster management at a fraction of the costs
associated with traditional data collection and map-making, while at the same time
potentially fostering community engagement in disaster prevention, preparation, response,
and recovery. We have argued that alongside these opportunities there are important
challenges for VGI, chiefly issues of data quality, bias in contributions, data management,
and the security of individuals, authorities, and their information. Addressing limitations will
build confidence in VGI as a reliable resource for disaster management, ultimately adding to
its utility for citizens as well as emergency services, policy makers, and GIScientists. There
is an urgent need for further research on the technical and critical dimensions of VGI and for
human geographers to engage with GIScientists to comprehend the implications of these data
and data practices for citizens, traditional methods of disaster management, and geography as
a discipline more broadly.
Acknowledgements
The authors would like to thank Kurt Iveson, Matt Duckham, and two anonymous reviewers
for providing useful feedback on earlier versions of this paper. The support of the
Commonwealth of Australia through the Cooperative Research Centre program is
acknowledged.
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... One important benefit of VGI for disaster management is the ability to support decision making in near-real time situation analysis, referring to the properties of particular VGI applications that allow for real-time data gathering 34,36,37 . Incorporating VGI into disaster-risk reduction (DRR) has created opportunities to increase local participation and promote the integration of local knowledge in the DRR process 38 . ...
... The risks of VGI use, both the imprecise event descriptions and reporting guidelines, can be outweighed by the benefits of targeted use, especially in areas of limited data collection after disasters and/or with a lack of detailed eventattribution data 34,42 and in areas with sharp gradients in socioeconomic conditions 43 . This is especially true for VGI sources that harness actively contributed data, as opposed to data that is passively harvested as a byproduct of unrelated user actions 38 . Data quality concerns should be addressed before assuming VGI integration will improve existing flash flood reporting capacity 44,45 . ...
... While Waze shows potential as a source of flood and flash-flood data, challenges remain. A primary concern is in understanding the scope of the Waze platform and data, particularly biases in the representativeness of its user base 38,62 . Despite large sample sizes, VGI from social media is rarely representative of the population 38,63 and tends to overrepresent young and affluent citizens. ...
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Using volunteered geographic information (VGI) to supplement disaster risk management systems, including forecasting, risk assessment, and disaster recovery, is increasingly popular. This attention is driven by difficulties in detection and characterization of hazards, as well as the rise of VGI appropriate for characterizing specific forms of risk. Flash-flood historical records, especially those that are impact-based, are not comprehensive, leading to additional barriers for flash-flood research and applications. In this paper we develop a method for associating VGI flood reporting clusters against authoritative data. Using Hurricane Harvey as a case study, VGI reports are assimilated into a spatial analytic framework that derives spatial and temporal clustering parameters supported by associations between Waze’s community-driven emergency operations center and authoritative reports. These parameters are then applied to find previously unreported likely flash flood-events. This study improves the understanding of the distribution of flash flooding during Hurricane Harvey and shows potential application to events in other areas where Waze data and reporting from official sources, such as the National Weather Service, are available.
... The effectiveness of a disaster management system relies on reliable information as input to the system. The research community has discussed the importance and effectiveness of information input to a disaster management system and its responses for relief and related recommendations [16,17]. One of the practical examples is the Twitter Earthquake Detector (TED) program, funded by the American Recovery and Reinvestment Act. ...
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Emergency response systems require precise and accurate information about an incident to respond accordingly. An eyewitness report is one of the sources of such information. The research community has proposed diverse techniques to identify eyewitness messages from social media platforms. In our previous work, we created grammar rules by exploiting the language structure, linguistics, and word relations to automatically extract feature words to classify eyewitness messages for different disaster types. Our previous work adopted a manual classification technique and secured the maximum F-Score of 0.81, far less than the static dictionary-based approach with an F-Score of 0.92. In this work, we enhanced our work by adding more features and fine-tuning the Linguistic Rules to identify feature words related to Twitter Eyewitness messages for Disaster events, named as LR-TED approach. We used linguistic characteristics and labeled datasets to train several machine learning and deep learning classifiers for classifying eyewitness messages and secured a maximum F-score of 0.93. The proposed LR-TED can process millions of tweets in real-time and is scalable to diverse events and unseen content. In contrast, the static dictionary-based approaches require domain experts to create dictionaries of related words for all the identified features and disaster types. Additionally, LR-TED can be evaluated on different social media platforms to identify eyewitness reports for various disaster types in the future.
... However, the research methodology was designed to be extendible for its main components. In this regard, it is possible of course (a) to model the whole transportation         step of the methodology concerning size and capacity, traffic signals, and accidents; (b) to consider the specifications of off-theshelf geosensors and their communication protocols        deploy the technical details of data collection and dissemination, data quality and reliability, and data management and filtering of VGI [75], and the technical details of data standardization and fusion of in situ and multi-agency sensors [36,37] in the   . ...
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Evacuation, as a response of paramount importance to mitigate the impact of disasters, involves the movement of people out of affected areas into safe zones. In urban areas, the consequences of an earthquake usually include damages and collapses in both transportation and telecommunication infrastructures, which outdate the (spatial) information required for evacuation and lead to imperfect situational awareness. These circumstances challenge the effectiveness of the current centralized policies of urban evacuation planning and management. Although the alternative decentralized approach attempts to address this problem, dependency of its performance on the local sharing of information, and not communicating with the centralized systems do not make it an integrated solution. In this paper, a new approach based on Ubiquitous GIS is proposed and validated. To the authors’ best of knowledge, so far Ubiquitous GIS is not appeared to be applied for assisting in earthquake outdoor evacuation, and this research contributes an integration of the centralized and decentralized approaches. Multi-agent-based simulations are carried out to assess the current policies and the proposed approach as evacuation assistance services. The experimental evidence validates the effectiveness of the proposed approach by hypothesis testing. Applying the Ubiquitous-GIS-based approach significantly reduces the evacuation time compared to the centralized and decentralized approaches (60.8% and 49% average reductions in elapsed evacuation time of 90% of the total evacuated evacuees, respectively; and 42.8% and 41.9% average reductions in network clearance time, respectively). Availability of post-earthquake spatial information reduces the response time to avoid cascading effects of earthquakes. In this regard, Ubiquitous GIS paradigm will influence policies of urban evacuation planning and disaster management, enabling more lives to be saved.
... Disaster management consists of four phases: prevention, preparation, response, and recovery (Haworth and Bruce 2015). In disaster management, especially in the response phase, rescue and relief teams should quickly plan and take appropriate decisions and actions. ...
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Natural disasters have always threatened the lives of humans and other creatures. One of the significant challenges for quickly responding to an earthquake is the need for precise and comprehensive information. Given that part of the environmental infrastructure is destroyed, quickly acquiring the required information is a serious challenge. Due to the ubiquity of smartphones, which have sensing, processing, and communication capabilities, this paper proposes CrowdBIG, a crowdsourcing-based architecture for information acquisition from the disaster environment. CrowdBIG architecture consists of four layers: sensing, fog, cloud, and application. Given that the reliability of crowdsourcing systems is dependent on the quality of user data, detecting malicious users, as well as scoring, and selecting useful users are of great importance. The CrowdBIG system is equipped with a reputation management component, which contains two sub-components: malicious user detection and user scoring. To evaluate the CrowdBIG system, first, we validate the information acquisition and dissemination workflow of the system using a scenario-based method. We then simulate the disaster environment through several well-known scenarios. The results show that CrowdBIG can detect malicious users appropriately. The CrowdBIG system can also score non-malicious users reasonably based on their usefulness and information completeness rates. The simulation results reveal that the reliability of the CrowdBIG system is 92%. Finally, the usability evaluation survey shows that more than 80% of the participants rated the usability of the proposed information-gathering tool as good or excellent.
... Finally, the town and its residents, are the most essential stakeholders and are frequently at the receiving end of every crisis. As a result, every policy dealing with regards to disaster risk management must carefully include them (Haworth & Bruce, 2015). It is in the business's and key stakeholders' best interests to achieve resilience in case of calamity. ...
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Whether an occurrence is natural disaster and man-made calamity, one thing is sure, it is not expected and at some instances, it cannot be avoided by any means. Just like other entities, businesses are vulnerable to these risks and it would surely cost the resources and profit of these enterprises. This study aimed to unravel the enterprise continuity and resiliency factors among Micro, Small, and Medium Enterprises in Region XII in the Philippines. The survey utilized an Exploratory Factor Analysis (EFA) with 450 respondents. Results showed that there were five elements that emerged: disaster preparedness, institutional planning and control, external relations, stakeholder’s support, disaster mitigation and support investment. Although most of the enterprises surveyed have an idea how to respond to calamities and mitigate disastrous situations, this research argues that a solid policy framework might be drawn through the local government units concerned to institutionalized this effort. Findings suggest that models such as pre-disaster agreement may be initiated and policy framework can be patterned after The Sendai Framework for Disaster Risk Reduction
... While these new technologies empower the general public to contribute to and engage in disaster management, they also act to marginalize others (Haworth & Bruce, 2015). We must be aware that the digital divide makes it difficult for members of the public with limited socioeconomic circumstances to access the rapidly expanding digital world (Van Dijk & Hacker, 2003), which means that the introduction of new geoinformation technologies in disaster education cannot ignore the conventional text-and image-based means. ...
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The complexity of disasters creates a significant challenge in the knowledge acquisition of the public. With the development of geospatial technologies, maps, geographic information science, and virtual geographic environments are widely used to represent disaster information and help the public better understand disaster risk. However, the application, design, and specific challenges have not been investigated comprehensively in disaster information representation thus far. This article presents the weaknesses and strengths of the existing methods for representing disaster information in recent decades, and then gives some basic ideas for efficient disaster knowledge communication. The objective of this article is to provide a clear image that improves users’ understanding of disaster information and bridge the communication gaps in disaster management.
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Mankind has been facing constant threats and challenges from natural and civilisational disasters for centuries. The fundamental responsibility of states is to protect the lives, health, and property of their citizens. However, protection against natural and civilisational disasters is a complex task in which the population also has to take part, and the availability of geoinformation is a prerequisite for effective protection. The aim of this study is to demonstrate the combined power of both citizens and technology in the task of alerting and informing the public of the opportunities offered by virtual crowdsourcing, Web 2.0, the role of geoinformation, crisis maps, and drones through the application of a qualitative method, by analysing case studies and by searching for internal connections between different phenomena. Citizens around the world can collaborate and contribute to the sharing and collection of geoinformation to create real-time, interactive maps. These so-called crisis maps support intervention organisations in obtaining information, and they can also be used as sources of information. The use of Web 2.0, crisis maps and drones, as well as the emergence of digital humanitarian volunteering, have fundamentally changed the role of the public when it comes to responding to disasters, including alerting them using geoinformation.
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From 2010 to 2019, Argentinian medical students and faculty at the Universidad Nacional de Rosario worked with allies from grassroots movements to routinize new epidemiological data collection practices designed to call medical students’ attention to the public health consequences of industrial agriculture’s indiscriminate use of pesticides. This paper charts the rise and fall of their collective efforts to institutionalize participatory knowledge and pedagogy that directly challenged the political legitimacy of industrial agriculture. We anchor our study in a trio of concepts—sociotechnical regime, niche, and network—using these tools to describe the dynamic interplay among dominant and subordinate knowledge systems. Our analysis reveals that radical participatory projects cannot be understood without reference to the historical and institutional contexts that structure opportunities and constraints within which participatory knowledge research is developed, implemented, and sustained.
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Data-driven artificial intelligence (AI) technologies are progressively transforming the humanitarian field, but these technologies bring about significant risks for the protection of vulnerable individuals and populations in situations of conflict and crisis. This article investigates the opportunities and risks of using AI in humanitarian action. It examines whether and under what circumstances AI can be safely deployed to support the work of humanitarian actors in the field. The article argues that AI has the potential to support humanitarian actors as they implement a paradigm shift from reactive to anticipatory approaches to humanitarian action. However, it recommends that the existing risks, including those relating to algorithmic bias and data privacy concerns, must be addressed as a priority if AI is to be put at the service of humanitarian action and not to be deployed at the expense of humanitarianism. In doing so, the article contributes to the current debates on whether it is possible to harness the potential of AI for responsible use in humanitarian action.
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Assessment of drought impact on the socio-economic fabric is a critical issue worldwide. Many studies have attempted to obtain socio-economic drought information. However, not enough attention has been paid to reducing the awareness gap between the monitoring of data of drought by public institutions, and local situations. This study proposes a socio-economic drought information (SEDI) based on Internet news articles that can consider droughts in situ. Based on 20,999 processed news articles, the SEDI is classified into four categories: water deficit, water security and support, economic damage and impact, and environmental and sanitation impact. In the moderately and severely dry conditions, the relationships between SEDI and monitoring data were evident with the receiver operating characteristic and the area under the curve of above 0.7. The evaluation results showed that SEDI could realistically reflect the lack of precipitation and social impact on South Korea. SEDI can successfully detect drought situations, thereby allowing understanding of the spatial temporal patterns of drought impact. The proposed SEDI can help effectively disseminate public safety information, thereby providing helpful data on local areas.
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critical disaster studies, mainly famine
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Volunteered geographical information represents a promising field in the monitoring and mapping of natural disasters. The contributors of volunteered geographical information have the advantage that they are at the location of the natural disaster at exactly the time when the disaster happened. Therefore, they can provide the most complete account of the extent of the damage. This is not always possible when applying photogrammetric or remote-sensing methods, as prior to the data acquisition an order to carry out the measurements has to be made. On 5 and 6 November 2012 almost half of Slovenia was badly affected by floods. The gathering of volunteered geographical information in the form of images and videos of these floods will be presented. Two strategies were used: (1) a public call for volunteered contributions and (2) a web search for useful images and their authors. The authorship of these images was verified with every contributor, and with the help of the volunteered images 12% of the most severely affected river sections were mapped. Altogether, 1195.3 ha of flooded areas outside of the usual riverbeds along a total river length of 48 km were mapped. The results are compared with those from satellite mapping of the same floods.
Article
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In this paper we review data collected from an online, social media-administered survey developed to explore public use of social media during a series of natural disasters, predominantly in Australia and New Zealand, during January to March 2011. These data are then explored using examples taken from the experiences of those involved in administering the most widely-used community-driven Facebook page during these disasters, which focused on tropical cyclone Yasi ('Cyclone Yasi Update'). The survey was completed by 1146 respondents who had used social media in relation to the recent natural disasters. Data indicated that the public relied on a mix of formal and informal information sources, often using social media to re-post or re-tweet links from government websites felt to be of use to communities, thus acting as filters and amplifiers of 'official' information. This paper discusses how social media, specifically their core strengths of timely information exchange and promotion of connectedness, were able to act as sources of psychological first aid in the early stages of disaster and assist in supporting aspects of community resilience.
Book
The phenomenon of volunteered geographic information is part of a profound transformation in how geographic data, information, and knowledge are produced and circulated. By situating volunteered geographic information (VGI) in the context of big-data deluge and the data-intensive inquiry, the 20 chapters in this book explore both the theories and applications of crowdsourcing for geographic knowledge production with three sections focusing on 1). VGI, Public Participation, and Citizen Science; 2). Geographic Knowledge Production and Place Inference; and 3). Emerging Applications and New Challenges. This book argues that future progress in VGI research depends in large part on building strong linkages with diverse geographic scholarship. Contributors of this volume situate VGI research in geography’s core concerns with space and place, and offer several ways of addressing persistent challenges of quality assurance in VGI. This book positions VGI as part of a shift toward hybrid epistemologies, and potentially a fourth paradigm of data-intensive inquiry across the sciences. It also considers the implications of VGI and the exaflood for further time-space compression and new forms, degrees of digital inequality, the renewed importance of geography, and the role of crowdsourcing for geographic knowledge production.
Conference Paper
Social media is often viewed as a sensor into various societal events such as disease outbreaks, protests, and elections. We describe the use of social media as a crowdsourced sensor to gain insight into ongoing cyber-attacks. Our approach detects a broad range of cyber-attacks (e.g., distributed denial of service (DDoS) attacks, data breaches, and account hijacking) in a weakly supervised manner using just a small set of seed event triggers and requires no training or labeled samples. A new query expansion strategy based on convolution kernels and dependency parses helps model semantic structure and aids in identifying key event characteristics. Through a large-scale analysis over Twitter, we demonstrate that our approach consistently identifies and encodes events, outperforming existing methods.
Book
Disaster vulnerability is rapidly increasing on a global scale, particularly for those populations which are the historical clients of the social work profession. These populations include the very young and very old, the poor, ethnic and racial minorities, and those with physical or mental disabilities. Social workers are increasingly providing services in disasters during response and recovery periods, and are using community interventions to reduce disaster vulnerability. There is a need for a cogent theory of vulnerability and research that addresses improved community disaster practice and community resilience. Community Disaster Vulnerability and Resilience provides a unifying theoretical framework backed by research which can be translated into knowledge for effective practice in disasters. © Springer Science+Business Media New York 2013. All rights are reserved.
Article
Social media platforms and mobile phone data are commonly mined to produce accounts of how people are responding in the aftermath of crisis events. Yet social and mobile datasets have limitations that, if not sufficiently understood and accounted for, can produce specific kinds of analytical and ethical oversights. In this paper, we analyze some of the problems that emerge from the reliance on particular forms of crisis data, and we suggest ways forward through a deeper engagement with ethical frameworks and a more critical questioning of what crisis data actually represents. In particular, the use of Twitter data and crowdsourced text messages during crisis events such as Hurricane Sandy and the Haiti Earthquake raised questions about the ways in which crisis data act as a system of knowledge. We analyze these events from ontological, epistemological, and ethical perspectives and assess the challenges of data collection, analysis and deployment. While privacy concerns are often dismissed when data is scraped from public-facing platforms such as Twitter, we suggest that the kinds of personal information shared during a crisis—often as a way to find assistance and support—present ongoing risks. We argue for a deeper integration of critical data studies into crisis research, and for researchers to acknowledge their role in shaping norms of privacy and consent in data use.