Table 1
Preliminary comparison of early warning systems and datasets.
| Functions | Organization | Institution and outputs | |
|---|---|---|---|
| Armed Conflict Location & Event Data Project (ACLED) | ACLED maintains a dedicated Early Warning Research Hub allowing ‘users to track a variety of different risk factors, across a range of contexts, in a way that meets their distinct needs’. | Collects real-time data from news feeds on the locations, dates, actors, fatalities, and types of all reported political violence and protest events across Africa, the Middle East, Latin America and the Caribbean, East Asia, South Asia, Southeast Asia, Central Asia and the Caucasus, Europe, and the United States. | Registered non-profit organization with 501(c)(3) status in the United States. Financial support from the Bureau of Conflict and Stabilization Operations at the US Department of State, the Dutch Ministry of Foreign Affairs, the German Federal Foreign Office, the Tableau Foundation, the International Organization for Migration, and The University of Texas at Austin. |
| Integrated Crisis Early Warning System (ICEWS) | Comprehensive automated system to monitor, assess and forecast national and subnational crisis (e.g., conflict, ethnic/religious violence, rebellion/insurgency) | Mixed method approach using 100 data sources and 250 newsfeeds parsed using Jabari technology and BBN Serif NLP technology. Includes iData (who did what to whom and when), iTrace (news mining), iCast (forecasting) and iSENT (sentiment). Uses a CAMEO ontology. | DARPA and the Office of Naval Research (2007 start) have developed a series of component tools and focused on 250 countries/territories. Currently maintained by Lockheed Martin. |
| Continental Early Warning System (CEWS) | Intended to anticipate and prevent conflict and provide timely information according to specific metrics | Observation and monitoring unit collects data and analysis and regional units linked to ‘SitRoom’ | African Union with MoU connecting Regional Economic Communities such as SADC, ECOWAS, (daily news, reports, flash reports and updates). SitRoom includes one coordinator, two communications assistants and ten assistants. |
| Political Instability Task Force (PITF) (Formerly known as the State Failure Task Force) | Seeks to measure the factors that lead to atrocities against non-combatant populations. | The dataset covers four state failure events: revolutionary wars, ethnic wars, adverse regime changes, and genocides and politicides. Ten variables are assessed based on their magnitude and the data is manually coded. | Center for International Development and Conflict Management (CIDCM), University of Maryland. |
| EC/EU Conflict Early Warning System (EWS) and GCRI | Assesses structural underlying risks for violent conflict (civil war, subnational conflicts, interstate conflict) | EC EWS includes the Global Conflict Risk Index (developed by ECJRC) and qualitative input from EU staff and country experts. The GRCI consists of a regression model and a composite model based on 24 variables from 14 different datasets. It generates a list of intensity of risk by country. | EU – External Action Service (EEAS) with European Commission |
| INFORM Risk, INFORM Severity and INFORM Warning | Provides risk assessment for humanitarian crises and disasters, a review of severity and issues warning globally to enhance preparedness, early warning and early action. | INFORM addresses several dimensions of risk related to hazard, exposure, vulnerability, and coping capacity. | A collaboration of the Inter-Agency Standing Committee Reference Group on Risk, Early Warning and Preparedness and the European Commission. Output: dataset, dashboard, country profiles, reports |
| ViEWS | Tracks four types of political violence including state-non-state actors, between nonstate actors, violence against civilians, and forced displacement. | Applies a blended approach including Bayesian and regression methods to generate early warnings for specific actors across geographic areas, one month in advance. Geographically focused on Africa. | Uppsala Conflict Data Program (UCDP), Department of Peace and Conflict Research, Uppsala University, Sweden. Cost is approximately Euro 600,000 a year. |
| EU-LISTCO (Nygärd et al. 2019) | Identifies risks in Europe in order to assess the EU’s preparedness and resilience in responding to governance breakdowns. | Applies a blended approach to track multiple types of conflict and governance breakdown. Geographically focused on four areas (EU and selected sites such as Mali, Georgia, and Ukraine). Timeframe is limited to 1989 and 2017. | Project funded by the EU’s Horizon 2020 Research and Innovation Program. Output: reports, publications, infographics, newsletters. Consortium of 14 universities and cost of roughly EUR 5 million (2018-2021). |
| Situational Awareness Geospatial Enterprise (SAGE) (Duursma and Karlsrud 2019) | An incident and event database developed in 2018 used to identify trends and indicators for early warning. | SAGE features an incident monitoring database used by UN military, police and civilians in UN peace operations. Since structured data is stored and categorized, it can be analyzed using machine learning. | United Nations Department of Peacekeeping Operations (UN DPKO). |
| Conflict Early Warning and Response Mechanism (CEWARN) | Assesses regional situations that could potentially lead to violence, develops case scenarios, shares analyses and prepares response options. | CEWARN divides incidents into four categories: armed clashes, raids, protest demonstrations, and other crimes. The mechanism consists of 50 indicators from open sources and SitRoom reports. | IGAD (Intergovernmental Authority on Development) member countries: Djibouti, Ethiopia, Kenya, Somalia, Uganda, Sudan and Eritrea. Cost was reportedly USD1.4 million per year. |
| Early Warning Project | Applies qualitative and quantitative forecasting methods to identify countries where risks of mass atrocities are high. | An annual statistical risk assessment of 160 countries based on assessing historical episodes (1945-present) and training a model (logistic regression with elastic-net regularization) of roughly 20 variables to predict onset risks. | Joint initiative of the Simon-Skjodt Center for the Prevention of Genocide at the US Holocaust Memorial Museum (USHMM) and Dartmouth College. |
| Atrocity Forecasting Project | Deploys multiple quantitative forecasting models to improve insight on causes of political instability and conflict leading to mass atrocities and genocide. | The Atrocity Forecasting Project applies machine learning-based forecasting techniques based on over 200 incidents recorded between 1946-2017. | Based in the Australian National University, the initiative issues periodic updates on risks for a specific interval (2015-20). The project also hosts periodic events. |
| The Sentinel Project EWS | Focuses on genocide prevention, though alert functions are still in development | Draws on open sources, including social media to monitor potential genocidal events in selected sites – i.e., Myanmar, Central African Republic, Democratic Republic of Congo, Iraq, Kenya, South Sudan and Uganda. Currently developing a database that will facilitate automated data collection from open sources. | Based in Canada and outputs include reports and visualizations. No dedicated staff or budget in 2020. |