Seminars, discussions and more from PeaceRep consortium members.



Read our key findings on PeaceTech


PeaceRep provides new and innovative ways of ‘PeaceTech’ working, focused on innovations in data, research and data collaboration, and feedback to data owners and social change agents in the field. As we have developed and used PeaceTech tools, whilst engaging with the emerging field, we have also reflected on lessons learned and important considerations for both creators and users of PeaceTech.


PeaceTech (overview)

Although there are different definitions of the term ‘PeaceTech’, it can be broadly understood as work that ‘involves the use of data, analytics, digitalization, and information technologies for peace processes’ (Bhattacharya and Badanjak et al., 2022:202).

While the tools available for collecting digital data at scale now offer the promise of high-quality datasets, they nevertheless raise new concerns around privacy and particularly the potential reidentification of personal information–not just of individuals, but of businesses and other actors in ways that previous data sources were regulated and subject to more established and conventional nondisclosure and privacy constraints (Nash, Trott, and Allen, 2022:9).

When developing PeaceTech tools, experienced ‘conflict sensitivity’ and ‘do no harm’ approaches to research have to be layered onto the normal ethical considerations of safety of those impacted by the visualizations and wider PeaceTech infrastructure, to enures that tools are safe, relevant and effective in situations of extreme and protracted violent conflict (Bell, Bach, and Kaur, 2022:163).

Participating in peacebuilding activities can put individuals, and especially women, at risk. Increased online activity and the use of digital devices may reinforce this risk if insufficient protective measures are put in place. This, in turn, creates an adverse effect on women’s inclusion. PeaceTech initiatives need to explore what digital technologies women mediators on the ground find practicable and user-friendly, and how to utilise and adapt these technologies to provide adequate peacebuilding tools that mitigate risk (Knäussel, 2020).

It is important to recognise that PeaceTech data is borrowed from the communities it is collected from, and not owned by researchers or policymakers. This acknowledges historical and political contexts in which marginalised communities are made hypervisible through over-surveillance. It also affords communities greater rights to self-determination by controlling how their data are used. The recognition of data ownership by communities also places a higher value on consent around the use of data and enables them to withdraw consent, a significant characteristic of ethical processes (Nash, Trott, and Allen, 2022:8).

When using PeaceTech tools, reliability is crucial, and new forms of data and methods raise new challenges for ensuring the quality of research. For example, questions remain regarding the quality and possible bias of the Global Database of Events, Language and Tone (GDELT), which is a machine-coded database hosted on Google’s BigQuery cloud infrastructure. Like many current machine-learning and AI systems, GDELT is a “black box”, and can only be assessed by measuring its behaviour in various benchmarking tasks (Bell and Gardner, 2022:3).

Our research suggests several ways to build confidence in GDELT. Firstly, GDELT could be benchmarked by: 1) comparing its coding of selected news stories to the coding of the same stories by human coders, 2) assessing whether trends and differences discovered in our analysis are considered credible by country and subject experts. Secondly, news sources could be assessed for quality and for type, for example, state/non-state, corporate/independent. These types would provide valuable additional comparison dimensions (Bell and Gardner, 2022:3).

As digital technologies proliferate, humanitarian and human rights organisations use them to assess food security, famine risk and starvation crimes. Monitoring food security has become increasingly quantitative in recent years, which is conducive to remote and digital assessments for hard to access conflict-affected populations (Jaspars, Majid, and Murdoch, 2022:2).

While this has some advantage for access and speed, there are limitations in terms of exclusions (where connectivity or mobile phone ownership is limited) and for understanding the complexities of famine causation. Similarly, artificial intelligence (AI) has been used for Famine Early Warning, but does not include the political choices which often cause famine and determine response (Jaspars, Majid, and Murdoch, 2022:2).

The potential risks and exclusions associated with digital assistance are likely to affect politically marginalised populations the most. As they are already the most vulnerable to famine, it can lead to increased inequality and vulnerability. In addition to exclusions due to limited connectivity, lack of national ID cards is source of exclusion, particularly for migrants and displaced populations (Jaspars, Majid, and Murdoch, 2022:2).

A key risk in digitalised assistance is politically motivated exclusions or persecution based on centralised digital beneficiary identification systems. In fact, whether civilian data are a protected object under Internayional Humanitarian Law (IHL) is a topic debated by international legal experts. This also links to the issue of cyberattacks on the computer systems of humanitarian organisations (or of data held by private data management or technology companies), and their potential to be violations of IHL. Extensive private sector involvement also raises an issue about the impartiality, neutrality and independence of humanitarian relief (a requirement under IHL) (Jaspars, Majid, and Murdoch, 2022:2).


Peace and conflict data

When it comes to data on peace processes, our PA-X Peace Agreements Database is one of the most comprehensive, comparative, consistent data resource on peace process progression or lack thereof, from 1990-2022. Nevertheless, even though PA-X comes close enough, it does not cover the full extent of information on peace processes, such as failures to reach agreements, informal deals, drafts, and other peace process components. There are conceptual and design challenges for incorporating these types of information in a peace agreement database (Badanjak, 2021:34).

The PA-X Peace Agreement Database has become a valuable resource for scholars studying peacemaking, negotiations, peace processes, and their relation to conflict dynamics. However, to be able to further contribute to these fields of study, PA-X must continue to develop, in terms of its scope, the types of data, and the level of granularity that it provides to the research community (Badanjak, 2021:37).

While the increase in local agreements listed on PA-X may be a by-product of better data collection methods and increased public relations and information activities on the part of the international third parties, the decline of pre-negotiation agreements and broader intrastate agreements is evident even as data collection methods improve. All of this suggests a change in the way that peacemaking activities take place that, in turn, requires further upgrades in data collection to be made, in order to better capture subnational and subregional agreements (Badanjak, 2021:30).

PA-X is not the only resource that provides data and information on peace agreements. It can be seen as complementing other resources, functionalities and aims of which overlap substantially across the databases and datasets. The main resources on peace agreements include the Peace Accords Matrix (PAM), Uppsala Conflict Data Programme (UCDP) Peace Agreements Dataset, “Language of Peace”, the “United Nations Peacemaker”, United States Institute for Peace (USIP) Peace Agreements collection, Political Agreements in Internal Conflict (PAIC), and ETH/UCDP/PRIO Ceasefires (Badanjak, 2021:32; Bell and Badanjak, 2019).

The growth of transitional justice (TJ) databases in research represents a significant development in the field. Our research comparing the different design aspects of TJ databases (research purposes, approaches to conceptualization, the handling of the notion of ‘transition’ and sources) finds that these differences limit the persuasiveness for scholars and practitioners of the findings produced, and restrict the ability of database researchers to draw upon pre-existing databases (Mallinder and O’Rourke, 2016:494).

Greater awareness of the diverse purposes of databases can help scholars appreciate how different forms of database can be used in an incremental and complementary manner to build knowledge that is persuasive for scholars and practitioners (Mallinder and O’Rourke, 2016:494).

Interactive digital trackers can provide information to those involved in peace negotiations and in support of peace processes, by contextualizing the data about public health and peace and conflict events (such as ceasefires), collecting and collating these data in a manner that enables learning from a multitude of verified cases. Carefully-conceptualised trackers can also highlight the complexity of conflict situations and strategic concerns of armed groups in conflict (Allison et. al, 2020; Bhattacharya and Badanjak et al., 2022; Bhattacharya and Funnemark, 2021).


Visualizing peace processes

In an era of datafication, governments and policymakers around the world have expressed great interest in the potential of big data for driving decision-making in many policy areas. This has coincided with and informed trends toward automated decision-making. Automated systems are increasingly being developed and relied upon to help inform decision-making (Nash, Trott, and Allen, 2022:8).

The role of visualisation within this datafied and technologised approach to decision-making is crucial for making sense of big data. Visualisation plays a crucial intermediary role in the collection of big data; the access, streamlining and curation of big data through digital dashboards; and the presentation of big data for both policymakers and citizen audiences in polished visualisations and infographics (Nash, Trott, and Allen, 2022:8).

The process of generating data visualisation and who produces and designs visualisations can play an important role in translating and encoding data in ways that influence the communication of particular results from the communities the data is collected from, and the policymakers who are to leverage the data in their decision-making processes (Nash, Trott, and Allen, 2022:8).

If there is clear idea of what data says, and what a key policy message might be, then it is relatively easy to commission a visualization as a communication tool. However, ‘visualizing-as-scoping’ involves letting the visualization process shape the view of the data and the sense-making process itself. Rather than using visualization as the end goal of communication (explanation) or as a form of exploratory data analysis (exploration), there is a process of thinking about an appropriate visualization for a problem/data as a tool to engage and think about the data and research. This ‘visualising-as-scoping’ can be slower and more complex, but ultimately effective (Bell, Bach, and Kauer, 2022:163).

Visualization-as-scoping requires visualizers learning what the data are, what the tasks are, what the data are not and why end-users might want to use it. It also requires social scientists to understand what is possible in design-terms. Often, what visualizers might think is interesting and challenging in visualization terms is not focused on revealing something that peace studies researchers think they and their end-users would be concerned about (Bell, Bach, and Kauer, 2022:165-166).

Visualization-as-scoping in the peacebuilding domain involves conversations about violent conflict, in contexts with strong social divisions and competing social narratives. There are logistical, ethical and risk dimensions to establishing and operationalising these relationships, from safety to the logistics of bringing people together, to the types of security that any tool needs to deploy (Bell, Bach, and Kauer, 2022:166).

Close collaborations with peacebuilders and peace researchers help in ‘seeing’ beyond the technical aspects of visualizations and to seek solutions for challenges in the field: cultural codes and cultural visual symbolism, provisions for trust, transparency and data provenance, usage scenarios, audiences and levels of visualization literacy, storytelling, and eventually means of wider participation (Bell, Bach, and Kauer, 2022:166).

Where data is to travel cultures and relates to sensitive political events there are a broad range of additional challenges that need to be thought through. These challenges include: relating to actual and conceptual translation, capacity to test visualizations in-country, dealing with issues such as reading from left to right and right to left differences; understanding culturally specific colour schemes, font-types, visual symbols, ideas of data literacy, visual literacy, general literacy, numeracy, etc. (Bell, Bach, and Kauer, 2022:166).

Visualization opens up a new way of seeing peace processes in a way that is disruptive of the type of timetables and linear processes that international actors often try to impose, but resonates strongly with experience in the field. Being honest about the data visually can enable a form of policy influence, which is about both conveying effectively and dramatically the complexity of peace processes, while giving people a way of situating their own activities in a complex unfolding process, enabling them to engage constructively with the ongoing nature of the process (Bell, Bach, and Kauer, 2022:167).