Tag Archives: PRIO

New Dataset Represents Breakthrough for Crisis Mapping Analysis

The Peace Research Institute in Oslo (PRIO) has just released the latest version of the Armed Conflict Location and Event Dataset (ACLED), which I blogged about last year here. The new peer-reviewed paper on this latest release is available here and you can watch ACLED’s presentation at the 2009 International Conference on Crisis Mapping (ICCM 2009) right here. The unit of analysis for ACLED is “an individual event that occurred at a given location.”

This new version has geo-referenced data for 50 unstable countries from 1997 through to 2010. The real breakthrough here is not just the scope of geographical coverage but more importantly how incredibly up to date the data is. I’m excited about this because it is rare that academic datasets can actually inform policy or operational response in a timely way. Academic datasets are generally outdated.

PRIO’s updated dataset codes the “actions of rebels, governments, and militias within unstable states, specifying the exact location and date of battle events, transfers of military control, headquarter establishment, civilian violence, and rioting.” As the authors note, the dataset’s “disaggregation of civil war and transnational violent events allow for research on local level factors and the dynamics of civil and communal conflict.”

Indeed, “micro-level datasets allow researchers to rigorously test sub-national hypotheses and to generate new causal arguments that cannot be studied with country-year or static conflict-zone data.” The authors identify four distinctive advantages of disaggregating local conflict event-data:

  1. Data can be aggregated to any desired level for analysis;
  2. The types of conflict events (e.g. battles or civilian violence) can be analyzed separately or in tandem;
  3. The actors within a conflict can be grouped or analyzed separately;
  4. The dynamics of national or regional war clusters can be addressed together.

The academic paper that discusses this new release of ACLED doesn’t go into much geospatial analysis but the dataset will no doubt catalyze many  analytical studies in the near future. One preliminary finding, however, shows that using country-level data can lead to biased results when studying conflict dynamics. “The average percentage of area covered by civil war from the data sample is approximately 48%, but the average amount of territory with repeated fighting is considerably smaller at 15%. Further, most conflicts initially start out as very local phenomena.”

Armed Conflict and Location Event Dataset (ACLED)

I joined the Peace Research Institute, Oslo (PRIO) as a researcher in 2006 to do some data development work on a conflict dataset and to work with Norways’ former Secretary of State on assessing the impact of armed conflict on women’s health for the Ministry of Foreign Affairs (MFA).

I quickly became interested in a related PRIO project that had recently begun called the “Armed Conflict and Location Event Dataset, or ACLED. Having worked with conflict event-datasets as part of operational conflict early warning systems in the Horn, I immediately took interest in the project.

While I have referred to ACLED in a number of previous blog posts, two of my main criticisms (until recently) were (1) the lack of data on recent conflicts; and (2) the lack of an interactive interface for geospatial analysis, or at least more compelling visualization platform.

Introducing SpatialKey

Independently, I came across UniveralMind back November of last year when Andrew Turner at GeoCommons made a reference to the group’s work in his presentation at an Ushahidi meeting. I featured one of the group’s products, SpatialKey, in my recent video primer on crisis mapping.

As it turns out, ACLED is now using SpatialKey to visualize and analyze some of it’s data. So the team has definitely come a long way from using ArcGIS and Google Earth, which is great. The screenshot below, for example, depicts the ACLED data on Kenya’s post-election violence using SpatialKey.


If the Kenya data is not drawn from the Ushahidi then this could be an exciting research opportunity to compare both datasets using visual analysis and applied geo-statistics. I write “if” because PRIO somewhat surprisingly has not made the Kenya data available. They are usually very transparent so I will follow up with them and hope to get the data. Anyone interested in co-authoring this study?

Academics Get up To Speed

It’s great to see ACLED developing conflict data for more recent conflicts. Data on Chad, Sudan and the Central African Republic (CAR) is also depicted using SpatialKey but again the underlying spreadsheet data does not appear to be available regrettably. If the data were public, then the UN’s Threat and Risk Mapping Analysis (TRMA) project may very well have much to gain from using the data operationally.


Data Hugging Disorder

I’ll close with just one—perhaps unwarranted—concern since I still haven’t heard back from ACLED about accessing their data. As academics become increasingly interested in applying geospatial analysis to recent or even current conflicts by developing their own datasets (a very positive move for sure), will these academics however keep their data to themselves until they’ve published an article in a peer-reviewed journal, which can often take up to a year or more to publish?

To this end I share the concern that my colleague Ed Jezierski from InSTEDD articulated in his excellent blog post yesterday: “Academic projects that collect data with preference towards information that will help to publish a paper rather than the information that will be the most actionable or help community health the most.” Worst still, however, would be academics collecting data very relevant to the humanitarian or human rights community and not sharing that data until their academic papers are officially published.

I don’t think there needs to be competition between scholars and like-minded practitioners. There are increasingly more scholar-practitioners who recognize that they can contributed their research and skills to the benefit of the humanitarian and human rights communities. At the same time, the currency of academia remains the number of peer-reviewed publications. But humanitarian practitioners can simply sign an agreement such that anyone using the data for humanitarian purposes cannot publish any analysis of said data in a peer-reviewed forum.


Patrick Philippe Meier

A Brief History of Crisis Mapping (Updated)


One of the donors I’m in contact with about the proposed crisis mapping conference wisely recommended I add a big-picture background to crisis mapping. This blog post is my first pass at providing a brief history of the field. In a way, this is a combined summary of several other posts I have written on this blog over the past 12 months plus my latest thoughts on crisis mapping.

Evidently, this account of history is very much influenced by my own experience so I may have unintentionally missed a few relevant crisis mapping projects. Note that by crisis  I refer specifically to armed conflict and human rights violations. As usual, I welcome any feedback and comments you may have so I can improve my blog posts.

From GIS to Neogeography: 2003-2005

The field of dynamic crisis mapping is new and rapidly changing. The three core drivers of this change are the increasingly available and accessible of (1) open-source, dynamic mapping tools; (2) mobile data collection technologies; and lastly (3) the development of new methodologies.

Some experts at the cutting-edge of this change call the results “Neogeography,” which is essentially about “people using and creating their own maps, on their own terms and by combining elements of an existing toolset.” The revolution in applications for user-generated content and mobile technology provides the basis for widely distributed information collection and crowdsourcing—a term coined by Wired less than three years ago. The unprecedented rise in citizen journalism is stark evidence of this revolution. New methodologies for conflict trends analysis increasingly take spatial and/or inter-annual dynamics into account and thereby reveal conflict patterns that otherwise remain hidden when using traditional methodologies.

Until recently, traditional mapping tools were expensive and highly technical geographic information systems (GIS), proprietary software that required extensive training to produce static maps.

In terms of information collection, trained experts traditionally collected conflict and human rights data and documented these using hard-copy survey forms, which typically became proprietary once completed. Scholars began coding conflict event-data but data sharing was the exception rather than the rule.

With respect to methodologies, the quantitative study of conflict trends was virtually devoid of techniques that took spatial dynamics into account because conflict data at the time was largely macro-level data constrained by the “country-year straightjacket.”

That is, conflict data was limited to the country-level and rarely updated more than once a year, which explains why methodologies did not seek to analyze sub-national and inter-annual variations for patterns of conflict and human rights abuses. In addition, scholars in the political sciences were more interested in identifying when conflict as likely to occur as opposed to where. For a more in-depth discussion of this issue, please see my paper from 2006  “On Scale and Complexity in Conflict Analysis” (PDF).

Neogeography is Born: 2005

The pivotal year for dynamic crisis mapping was 2005. This is the year that Google rolled out Google Earth. The application marks an important milestone in Neogeography because the free, user-friendly platform drastically reduced the cost of dynamic and interactive mapping—cost in terms of both availability and accessibility. Microsoft has since launched Virual Earth to compete with Google Earth and other  potential contenders.

Interest in dynamic crisis mapping did exist prior to the availability of Google Earth. This is evidenced by the dynamic mapping initiatives I took at Swisspeace in 2003. I proposed that the organization use GIS tools to visualize, animate and analyze the geo-referenced conflict event-data collected by local Swisspeace field monitors in conflict-ridden countries—a project called FAST. In a 2003 proposal, I defined dynamic crisis maps as follows:

FAST Maps are interactive geographic information systems that enable users of leading agencies to depict a multitude of complex interdependent indicators on a user-friendly and accessible two-dimensional map. […] Users have the option of selecting among a host of single and composite events and event types to investigate linkages [between events]. Events and event types can be superimposed and visualized through time using FAST Map’s animation feature. This enables users to go beyond studying a static picture of linkages to a more realistic dynamic visualization.

I just managed to dig up old documents from 2003 and found the interface I had designed for FAST Maps using the template at the time for Swisspeace’s website.



However, GIS software was (and still is) prohibitively expensive and highly technical. To this end, Swisspeace was not compelled to make the necessary investments in 2004 to develop the first crisis mapping platform for producing dynamic crisis maps using geo-referenced conflict data. In hindsight, this was the right decision since Google Earth was rolled out the following year.

Enter PRIO and GROW-net: 2006-2007

With the arrival of Google Earth, a variety of dynamic crisis maps quickly emerged. In fact, one if not the first application of Google Earth for crisis mapping was carried out in 2006 by Jen Ziemke and I. We independently used Google Earth and newly available data from the Peace Research Institute, Oslo (PRIO) to visualize conflict data over time and space. (Note that both Jen and I were researchers at PRIO between 2006-2007).

Jen used Google Earth to explain the dynamics and spatio-temporal variation in violence during the Angolan war. To do this, she first coded nearly 10,000 battle and massacre events as reported in the Portuguese press that took place over a 40 year period.

Meanwhile, I produced additional dynamic crisis maps of the conflict in the Democratic Republic of the Congo (DRC) for PRIO and of the Colombian civil war for the Conflict Analysis Resource Center (CARC) in Bogota. At the time, researchers in Oslo and Bogota used proprietary GIS software to produce static maps (PDF) of their newly geo-referenced conflict data. PRIO eventually used Google Earth but only to publicize the novelty of their new geo-referenced historical conflict datasets.

Since then, PRIO has continued to play an important role in analyzing the spatial dynamics of armed conflict by applying new quantitative methodologies. Together with universities in Europe, the Institute formed the Geographic Representations of War-net (GROW-net) in 2006, with the goal of “uncovering the causal mechanisms that generate civil violence within relevant historical and geographical and historical configurations.” In 2007, the Swiss Federal Institute of Technology in Zurich (ETH), a member of GROW-net, produced dynamic crisis maps using Google Earth for a project called WarViews.

Crisis Mapping Evolves: 2007-2008

More recently, Automated Crisis Mapping (ACM), real-time and automated information collection mechanisms using natural language processing (NLP) have been developed for the automated and dynamic mapping of disaster and health-related events. Examples of such platforms include the Global Disaster Alert and Crisis System (GDACS), CrisisWire, Havaria and HealthMap. Similar platforms have been developed for  automated mapping of other news events, such as Global Incident Map, BuzzTracker, Development Seed’s Managing the News, and the Joint Research Center’s European Media Monitor.

Equally recent is the development of Mobile Crisis Mapping (MCM), mobile crowdsourcing platforms designed for the dynamic mapping of conflict and human rights data as exemplified by Ushahidi (with FrontLineSMS) and the Humanitarian Sensor Web (SensorWeb).

Another important development around this time is the practice of participatory GIS preceded by the recognition that social maps and conflict maps can empower local communities and be used for conflict resolution. Like maps of natural disasters and environmental degradation, these can be developed and discussed at the community level to engage conversation and joint decision-making. This is a critical component since one of the goals of crisis mapping is to empower individuals to take better decisions.

HHI’s Crisis Mapping Project: 2007-2009

The Harvard Humanitarian Initiative (HHI) is currently playing a pivotal role in crafting the new field of dynamic crisis mapping. Coordinated by Jennifer Leaning and myself, HHI is completing a two-year applied research project on Crisis Mapping and Early Warning. This project comprised a critical and comprehensive evaluation of the field and the documentation of lessons learned, best practices as well as alternative and innovative approaches to crisis mapping and early warning.

HHI also acts as an incubator for new projects and  supported the conceptual development of new crisis mapping platforms like Ushahidi and the SensorWeb. In addition, HHI produced the first comparative and dynamic crisis map of Kenya by drawing on reports from the mainstream media, citizen journalists and Ushahidi to analyze spatial and temporal patterns of conflict events and communication flows during a crisis.

HHI’s Sets a Research Agenda: 2009

HHI has articulated an action-oriented research agenda for the future of crisis mapping based on the findings from the two-year crisis mapping project. This research agenda can be categorized into the following three areas, which were coined by HHI:

  1. Crisis Map Sourcing
  2. Mobile Crisis Mapping
  3. Crisis Mapping Analytics

1) Crisis Map Sourcing (CMS) seeks to further research on the challenge of visualizing disparate sets of data ranging from structural and dynamic data to automated and mobile crisis mapping data. The challenge of CMS is to develop appropriate methods and best practices for mashing data from Automated Crisis Mapping (ACM) tools and Mobile Crisis Mapping platforms (see below) to add value to Crisis Mapping Analytics (also below).

2) The purpose of setting an applied-research agenda for Mobile Crisis Mapping, or MCM, is to recognize that the future of distributed information collection and crowdsourcing will be increasingly driven by mobile technologies and new information ecosystems. This presents the crisis mapping community with a host of pressing challenges ranging from data validation and manipulation to data security.

These hurdles need to be addressed directly by the crisis mapping community so that new and creative solutions can be applied earlier rather than later. If the persistent problem of data quality is not adequately resolved, then policy makers may question the reliability of crisis mapping for conflict prevention, rapid response and the documentation of human rights violations. Worse still, inaccurate data may put lives at risk.

3) Crisis Mapping Analytics (CMA) is the third critical area of research set by HHI. CMA is becoming increasingly important given the unprecedented volume of geo-referenced data that is rapidly becoming available. Existing academic platforms like WarViews and operational MCM platforms like Ushahidi do not include features that allow practitioners, scholars and the public to query the data and to visually analyze and identify the underlying spatial dynamics of the conflict and human rights data. This is largely true of Automated Crisis Mapping (ACM) tools as well.

In other words, new and informative metrics are need to be developed to identify patterns in human rights abuses and violent conflict both retrospectively and in real-time. In addition, existing techniques from spatial econometrics need to be rendered more accessible to non-statisticians and built into existing dynamic crisis mapping platforms.


Jen Ziemke and I thus conclude that the most pressing need in the field of crisis mapping is to bridge the gap between scholars and practitioners who self-identify as crisis mappers. This is the most pressing issue because bridging that divide will enable the field of crisis mapping to effectively and efficiently move forward by pursuing the three research agendas set out by the Harvard Humanitarian Initiative (HHI).

We think this is key to moving the crisis-mapping field into more mainstream humanitarian and human rights work—i.e., operational response. But doing so first requires that leading crisis mapping scholars and practitioners proactively bridge the existing gap. This is the core goal of the crisis mapping conference that we propose to organize.

Patrick Philippe Meier