Democratizing Mobile App Development for Disaster Management
Fuming Shih, Oshani Seneviratne, Daniela Miao, Ilaria Liccardi, and Lalana Kagal
Massachusetts Institute of Technology
Cambridge, USA
Evan Patton
Rensselaer Polytechnic InstituteTroy, New York
Abstract
Smartphones are being used for a wide range ofactivities including messaging, social networking,calendar and contact management as well as location and context-aware applications. The ubiquityof handheld computing technology has been foundto be especially useful in disaster management andrelief operations. Our focus is to enable developers
to quickly deploy applications that take advantage
of key sources that are fundamental for today’s networked citizens, including Twitter feeds, Facebook
posts, current news releases, and government data.
These applications will also have the capability of
empowering citizens involved in crisis situations tocontribute via crowdsourcing, and to communicate
up-to-date information to others. We will leverage several technologies to develop this application
framework, namely (i) Linked Data principles forstructured data, (ii) existing data sources and ontologies for disaster management, and (iii) App Inventor, which is a mobile application development
framework for non-programmers. In this paper, we
describe our motivating use cases, our architecture,and our prototype implementation.

1

Introduction

Smartphones are quickly becoming the primary computing
and communication platform for people’s daily tasks. With
the rise of social networks, “netizens” are now comfortablewith frequently updating their social profiles with their current activities and/or locations. This new source of information, social signals from microblog platforms, has been foundto be especially useful in disaster management and relief operations [Fajardo and Oppus, 2010]. For example, during
the Beijing flash floods in July 2012, people took to Twitter to provide information about the flooded areas and collaboratively developed a live crisis map of the floods impact
using Google Maps 1 . By integrating crowdsourced information with Geographic Information Systems (GIS) data orother open datasets released by the local government, some

Carlos Castillo, Patrick Meier
Qatar Computing Research InstituteDoha, Qatar
technical volunteers have developed useful mobile applications for disaster reliefs. However, each organization usually
has its own application that creates or consumes data stored
in standalone databases, or even worse, in spreadsheets. Thismeans most of these applications are built in silos without exploiting the potential of being “interlinked” with other datacollected from other organizations, or even the government.
The lack of expertise and the cost for building mobile applications cause relief workers to turn to more manual steps for
merging various reports from volunteers. Consequently, theincreasingly unorganized and scattered information become
noise in the system and can sometimes slowdown the decision making process. We envision a framework that enables
non-technical application developers to quickly build and deploy applications that easily reuse existing and crowdsourced
structured information sources.
One major challenge in the afore-mentioned example is
how to effectively integrate data generated by multiple parties, including the “crowd”, relief organizations, and government agencies. We address this challenge by using Linked
Data principles2 to enable the reuse, extension and integrationof heterogeneous structured data from distributed sources.
Linked Data is a set of design principles proposed by theWorld Wide Web Consortium (W3C) for using Web technologies in order to support the distributed development ofstructured information such that it can be easily and automatically combined. However, consuming and generating Linked
Data is difficult as pointed out in [Scharffe et al., 2012], especially on mobile devices. This implies that we need to also
focus on reducing the barrier to the adoption of Linked Datatechnologies on smartphones.
This paper describes our ongoing work of extending the
App Inventor3 platform with Linked Data technologies. App
Inventor is an open-source project that provides a blockbased interface to visually create Android apps [Wolber etal., 2011]. We are developing “Linked Data” components for
App Inventor that will allow app developers to easily build applications that explore and consume Linked Data datasets aswell as publish structured data directly to remote Linked Datarepositories. Our App Inventor components will focus on (i)embedding semantic concepts directly into the process of mo2

1

http://iRevolution.net/2012/08/01/crisis-map-beijing-floods/

3

http://www.w3.org/DesignIssues/LinkedData.html
http://appinventor.mit.edu/

9:40

QCRI APP

9:40

9:40

QCRI APP

WATER

9:40

QCRI APP

FOOD

DonateWATER
MEDICINE

RequestHOSPITAL

9:40

QCRI APPSHELTER

Recent Actions

CLOTHES

Welcome to the QCRI app.
Log in using your twitter credentials

(a)

(b)
9:40

9:40

WATER
QCRI APP

Recent Actions

username

I can donate water 3L.
9:23 AM

password

Tag

Name

WATER

Edit

RemoveEdit

RemoveEdit

Removezip code

Description

if blank we will use your GPS Location

WATER
I can donate water 5L.
10:13 AM

Description

FOOD
I can donate food.

Log in10:13 AMI am looking for water, please help.
Submit(c)

9:23 AM

(d)

reply

(e)

Submit(f)

Figure 1: Two Semantic Web enabled mobile apps for disaster response situations
9:40
bile app-building while hiding most of the operational
details
WATER
from novice developers, and (ii) the integration of structured
information from microblog platforms, crowdsourced and existing open data.

2

Microblog	
  Analysis	  Motivating scenarios

We describe two applications that can potentially be used bypeople during a crisis situation: (1) App Donate-N-Request
will be used to match requests and donations during a disaster
scenario, and (2) App WeReport will be used to report scenes
and information related to the disaster. These apps will havethe ability to be integrated
with different public datasets using
There are 8 people looking for water in your proximity
linked data.

DevelopersData	
  service	
  endpoints	
  

Data	
  
Cura7on	  Crowd with LD-Apps

Crowd
9:40

Figure 2: Architecture of LinkedWATER
Data enabled crowdsourcing
and application development platform
I am looking for water, please help
9:23 AM

2.1

Donate-N-Request App

This app is inspired by MatchApp4 , where requests for resources are met with the availability of those resources.
Consider this resource match-making scenario: Alice lives
9:40 Alice wants
in New York City. After Hurricane Sandy hits,
QCRIBob
APP has been affected by the crisis.
to help people in need.
Both Bob, the requestor, and Alice, the donator, can place thea picture or a video
donation and request for Takeitems
within our app as shown in
Figure 1(a) & (b). They can also view/edit/remove recent listof their activities as shown in Figure 1(c). Alice chooses todonate water, so she checks up all the people within a 3 miles
radius of her location who are in need of water on a map asshown in Figure 1(e). Bob had previously requested water byusing our app (Figure 1(d)). Alice selects Bob from the listof people in need. Alice and Bob can message directly witheach other to arrange the exchange.

2.2

WeReport App

On his way to the grocery store, after a severe hurricane, Joenoticed many parts around his community are in bad conditions. For example, fallen trees are blocking the road and4app/

http://iRevolution.net/2013/02/27/matchapp-disaster-response-

I am in your proximity, do you still need water?

some can be dangerous for the pedestrians. With our WeReport app, he could take either a picture or a video of the scene.
He decides to take a picture of the road, by adding a “tag” anda “description” to the image as shown in Figure 1(f).
10:23 AM

3

Prototype Implementation

In order to implement the apps described in Section 2, andgather the necessary data items, we explored the use of existing linked data vocabularies and tied them into App Inventor
as illustrated in Figure 2.

3.1

Linked Data

Disaster management activities such co-ordinating relief operations, setting up shelters, reporting structural damages, andoverseeing volunteers generate a lot of data. These need to be
integrated and be interoperable with data provided by various organizations to be useful in decision making processes
during disasters. Previous research [Babitski et al., 2011] hasdemonstrated how the use of ontologies and Semantic technologies can be advantageous in developing applications fordisaster management scenarios. We identified two vocabularies that are useful in modeling such data as Linked Data.

They have varying degrees of support for some of the disasterconcepts, and we used terms from both the vocabularies in
our implementation. We discuss some shortcomings of these
ontologies in Section 4.
Humanitarian eXchange Language Situation andResponse Standard (HXL)HXL5 was developed through an initiative by the United Nations High Commissioner for Refugees (UNHCR) after inspecting a broad range of systems in use with different humanitarian organizations. The schema is available in fivemain sections, namely: geolocation (information on the locations affected), humanitarian profile (information on the
populations affected), metadata (who is collecting the data,
date/time the data was collected, etc), response (informationon the organization responding), and situation (information
related to the emergency).
Management Of A Crisis Vocabulary (MOAC)
MOAC6 was created after the earthquake in Haiti in 2010.
Much of the focus in developing this vocabulary was to mitigate the inconsistencies between aggregated data and requirements of relief organizations. This was the first Linked Data
vocabulary that had the objective of facilitating non-experts toprovide data in Linked Data formats through crowd sourcing
mechanisms such as Google Map Maker, Open Street Map,
Twitter and Ushahidi. MOAC defines three main sections that
relate to relief agency standards.

3.2

App Inventor

App Inventor provides a Web-based development platform
for novices with no prior programming experience to create
mobile applications easily. A user can drag and drop graphical objects on the interface editor (Figure 3(a)) to design an
app or implement behaviors with blocks as shown in Figure3(b). App Inventor also provides many high-level components for using smartphone resources as well as communicating with external web resources. For example, it has components for reading the GPS location sensor, taking photos
with the camera, receiving SMS texts, and sending Twitter
messages. By hiding most of the technical details, App Inventor gives its users the benefits to focus on designing app
behaviors rather than lower-level debugging. However, App
Inventor currently has little support for integrating application
data with backend data-stores, for example, to save application data as Linked Data or integrate with other Linked Data
resources.

3.3

Linked Data Extension of App Inventor

In order to enable developers using the App Inventor platform
to interact with Linked Data sources, we provide an extended
version of App Inventor with additional components and userinterface elements powered by a modified version of the Jenaframework [Carroll et al., 2004]. In this section we outline
how we expose Linked Data concepts to application developers in the App Inventor the new components that can be usedby developers to consume and generate Linked Data.
5
6

http://hxl.humanitarianresponse.info/ns/index.html
http://observedchange.com/moac/ns/

(a)

(b)

Figure 3: Interface of the App Inventor platform

Figure 4: App Inventor autocompletion of concepts and properties powered by SPARQL queries over cached semantic
web ontologies
Exploring Linked Data
One challenge of using Linked Data is finding details of an
ontology that describes a dataset. App developers should not
be burdened with knowing all the details of an ontology. For
example, when building a crisis response app, a developer
may begin with a general concept such as Shelter and let
the system provide more relevant information. Our extension
provides an autocompletion capability in the designer interface to assist developers in selecting the appropriate ontological term (see Figure 4). We provide a service within the App
Inventor that loads ontologies, indexes labels for classes andproperties, and answers queries to support this autocompletion widget.
Consuming Linked Data with Semantic Web Component
The Semantic Web Component converts semantic forms
into RDF graphs, executes and process results of SPARQL
queries, and saves and loads the content of ontologies. For
example, the app developer can execute a SPARQL query tofetch information about nearby shelters based on the user’s
current GPS location and show the results on a map.
Publishing Linked Data with Semantic Form
The Semantic Form is a layout component that can be usedby developers to identify a collection of fields that should beapplied to a particular ontological concept. Forms can also
assign an auto-generated subject URI based on one or more
fields to create new Linked Data instances. For example, a developer can have two textfields for the name and the description of a shelter. Semantic Form will automatically generate
Linked Data triples if those fields are tagged with ontologicalterms like the properties shelterName and shelterDescription
from the MOAC ontology.

4Discussion

Existing disaster management vocabularies have support for
many disaster management scenarios. But there are someshortcomings in current vocabularies. HXL defines administrative units that may accept the donations, and the affected populations that would receive those donations. However there is no support to specify what the donation is, i.e.
whether it is money, clothes, food, etc, as well as who is donating it and other logistics related to the donation. Similarly,
MOAC has support for specifying the needs of a specific shelter and who is handling what in the WhoWhatWhere (W3)section of the vocabulary. However, there is nothing to describe data relating to donations. Another shortcoming ofthese two vocabularies is the lack of support for situationalawareness data. As an example, if someone is reporting structural damage to a bridge that might be affecting a population,
there is no way to link the bridge data to MOAC and/or HXL.
We are in the process of formulating a vocabulary that willtie in these disaster vocabularies with other related linked data
vocabularies, e.g. Geonames, Semantically Interlinked Online Communities (SIOC)7 , etc. Geonames can be used tomodel geo-location information, and the related population
information. SIOC can be used to tie in information available
in microblog posts from tweets and Facebook posts after adisaster such as zones that people need to evacuate from, newdevelopments in a disaster (e.g. the potential sighting of alooting), donation pledges along with requests for donations,etc.
With the proliferation of linked datasets, developers using App Inventor may want to use these data directly via
App Inventor components without having to write SPARQL
queries themselves. In order to facilitate this feature, we
are in the process of developing “data wrapper” components.
These components have built-in SPARQL queries to accessfrequently accessed data, with extended functionality to plugin custom SPARQL queries to get at more specific data items.
With this functionality, we hope not to clutter the App Inventor component interface with data items that a majority of app
inventor developers may not use while providing the flexibility to retrieve any kind of data the developer desires. As an
example, consider a data wrapper component for the NYC
demographics statistics datasets8 . This dataset includes all
the population statistics such as number of males and females
as well as number of people based on their ethnic categorization in a given zip code area. This ethnic categorization includes generic categories such as white, black, hispanic, asianin addition to very specific categories such as pacific islander,
asian non-hispanic, white non-hispanic, white hispanic, black
non-hispanic, black hispanic, etc. The data wrapper would
expose the gender based information and the general ethnicities in the interface with built-in SPARQL queries that could
just be dragged and dropped on to the interface, whereas very
specific queries to obtain information about a particular ethnicity (for e.g. black hispanic) could be written by the app
inventor developer and plugged into the component.
7

http://sioc-project.org
https://nycopendata.socrata.com/Statistics/DemographicStatistics-By-Zip-Code
8

Using linked data within a mobile environment has proved
useful and challenging in other research. David et al. [2010]
propose a general framework in order to introduce Linked
Data sources as device content in the Android platform;
D’Aquin et al. [2010] consume selected data sources andcreate new social link between people in the author’s university; Razzak et al. [2010] utilize government data to support tourism within the author’s city. However in all theseapproaches the application is domain specific and cannot be
extended to be used with different data sources. Extending
the App Inventor framework with Linked data will allow developers to be able to reuse available linked data sources andto tailor and extend apps to a variety of scenarios.

5

Summary

In this paper we have demonstrated the effective use of
Linked Data within mobile applications with a special focus
on disaster management. As organizations continue to expose
their data as Linked Open Data, our platform will be able
to help developers using the Linked Data App Inventor platform to come up with useful applications quickly and without
much effort to help those in need during disasters.

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