MDC Research

RESEARCH ON SECURITY ISSUES

The University of Bergen has conducted comprehensive research on the topic of security while using Mobile Data Collection, in particular for health projects. We encourage you to have a look at their work here: http://www.uib.no/en/project/smdc/56405/secure-mobile-data-collection-systems

DEFINING MOBILE DATA COLLECTION

Mobile Data Collection (MDC) is the targeted gathering of structured information using devices such as smartphones, PDAs, or tablets. In the last few years, in addition to continuous improvements of earth-observation and web mapping techniques, the increasing use of new sources of geo-information based on new mobile technologies has emerged. This has created insights and opportunities into the mechanisms of sudden onset crisis related data collection, analysis and mapping.

The humanitarian community also recently discovered that mobile phones are useful tools for collecting data in the field. The arrival of devices allowing geo-localization of data collected also raised interest in the humanitarian community for new technologies such as mapping SMS incident reports or SMS based data collection. As a result, an abundance of mobile data collection applications and initiatives appeared in the last seven years in the humanitarian and early warning field.

Mobile Data Collection Systems (MDCS) ask questions that are answered on mobile devices, therefore requiring two-way communication, either immediately or with delayed synchronization of data. It is more than simply sending bulk SMS to a targeted population, and different from subscription information services that provide alerts such as the Tsunami Early Warning System and The Australian Early Warning Network. Mobile data collection applications are often used internally in an organization, customized to fit with existing organizational processes. This may mean using
services or applications that are outside most people’s day-to-day experience with mobile use.

MDC differs from the crowd-sourced data aggregation paradigm popularized by tools such as Ushahidi. Data aggregators collect unstructured data found as posts to services such as Twitter, Facebook, email, and SMS, and they mine this data for information. By contrast, mobile data collection systems run designed surveys which collect specific information from a target audience. The audience can be either organizational staff trained to conduct surveys/assessment or the target population being studied can be surveyed directly via their personal mobile devices. In either case, the specific questions and structured responses can be important to rapidly collecting information deemed essential to an emergency response.

RESEARCH OBJECTIVES

Choosing the most appropriate technology strategy for a specific organizational context and communication environment remains a difficult task for humanitarian workers, for the following reasons:

  • The main challenge remains to identify the appropriate mobile data collection system to fit the multiplicity of operational contexts humanitarian organizations have to operate in.
  • The second challenge is to keep track of the evolution of a very dynamic sector and the constant evolution of new technologies flourishing on the data collection market.
  • Last but not least, while the rich content of information – whether available on the internet or in the data derived from mobile data collection – poses opportunities for application in crisis management, it also poses challenges derived from the analysis of the quality, accuracy, and reliability of the data.

All those challenges apply particularly in the field of early needs assessment which requires a small set of highly accurate standardized information to better inform emergency decision makers.

Since mobile data collection systems have been used for years in the humanitarian sector, there is enough experience and operational learning on the issue to allow a decent review of existing initiatives, their performance, and a mapping of potential use in different operational contexts. To this end, ACAPS and CartONG have partnered under the NOMAD banner to evaluate the current state of the MDC field. This report investigates the available options for the moment, categorizing and grouping for operational goals where relevant. It also suggests trends for the near future and a strategy for maintaining the freshness of this knowledge base.

The purpose of this research is to review existing mobile data collection software systems, projects,
and initiatives. In order to accomplish this, NOMAD undertook the following tasks:

  • Build a matrix of analysis for mobile data collection systems currently available for use in humanitarian relief interventions.
  • Review the use of MDCS and successful experiences, potential, gaps and limitations, specifically for data collection speed, analysis and reporting. Selection of most promising application and tools.
  • Model and build a decision tree to facilitate choice and use of MDCS according to different operational contexts.

BASIC COMPONENTS OF a MDCS

While system architecture approaches vary greatly, there are a few components that are common to all MDCS:

  • Many mobile devices are used for data collection. Each MDCS supports a subset of mobile device technologies. The most simple hardware requirement is plain SMS (FrontlineSMS1, RapidSMS, and Souktel AidLink specialize in SMS). More complex forms are built on Java (Nokia Data Gathering; EpiSurveyor) or a smartphone platform such as Android (ODK and its offspring; Imogene) or Windows Mobile (CSPro; DevInfo; IMSMANG). Some MDCS can support multiple mobile platforms for the same form and server (Acquee; Mobenzi Researcher; Pendragon Forms).
  • The administrator interface is used by a few survey designers and data analysts. It is used to design the form layout and create the mobile application. It sometimes allows for data entry and viewing of the collected data. For tools with integrated visualization features such as DevInfo and IMSMANG, the admin interface acts as the analysis platform and generally provides basic descriptive statistic functions as well as line graphs and bar charts.
  • The third component is one server which hosts the database. It includes some mechanism to upload data from the mobile devices. Connectivity can be via internet, SMS, or directly copying files. Once collected, the server presents the data via the administrator client interfaces, and sometimes the mobile devices in the case of bi-directional synchronization systems (Imogene;EpiCollect). Some systems integrate the administrator interface and the server software. This is usually done when the synchronization is not done via the internet and the data is directly uploaded from the devices, such as CSPro and CyberTracker.

RESEARCH METHODOLOGY

NOMAD first began collecting information on used cases of mobile data collection in October 2010, when CartONG interviewed several project teams engaged in mobile data collection in the field. These interviews informed the creation of a wider web-based survey of existing mobile data collection initiatives among humanitarian actors in November 2010. The survey asked respondents to comment on their organizational requirements and experiences. The findings from the survey, available on the NOMAD website, set the initial orientation for the NOMAD project.

High level work to plan the scope and direction of the research continued at the NOMAD workshop on 22-23 June 2011 in Geneva. During the workshop, NOMAD members refined the research objectives and compiled lists of resources, building on those identified in the web survey. More detailed research commenced at the end of July and continued through the end of 2011.
The methodologies for each of these tasks are broken down in the sections that follow.

To be continued…

The report can be found here.