Across the humanitarian sector, data play an increasingly important role in response efforts. To implement water, shelter, protection, or food assistance programmes, humanitarian actors collect information, such as the gender or age of individual recipients of assistance. As a result, humanitarians need to manage large amounts of data, and recognise the importance of ensuring responsible use and protection of these data (see here and here).
In its recent guidance, the Inter-Agency Standing Committee (IASC) defines data responsibility in humanitarian operations as ‘the safe, ethical and effective management of personal and non-personal data for operational response, in accordance with established frameworks for personal data protection’ (IASC 2021, 7). Managing data responsibly requires comprehensive consideration, encompassing data collection, processing, analysis, use, storage, sharing, retention, and destruction. In a recent report, I investigate one component of data responsibility: data sharing between humanitarian actors and donor governments. The research draws on interviews with donors and humanitarians about data sharing practices and an examination of formal documents. While the report goes into more detail, here I focus on two issues – data and definitions, and expectations and standards – and why they matter for more effective humanitarian response.
Data and definitions
My research finds that references to ‘data’ in the context of humanitarian operations are usually generic and lack a consistent definition or even a shared terminology. Thus, among other definitions, data could refer to quantitative or qualitative, numbers or narratives, personal or non-personal data as well as financial, audit or compliance data, situational reporting, and aggregated or disaggregated indicator data (see table below).
| Type of Data | Example |
| Quantitative/numbers | Numbers of beneficiaries/aid recipients |
| Qualitative/narrative | Descriptions of workshops or programme activities |
| Personal | Demographic data (names or contact information of aid recipients, group information, such as ethnicity) |
| Non-personal | Data about groups affected by the humanitarian situation, including needs or the threats they face |
| Group | Data about groups of aid recipients (women, children, disabled), such as location |
| Individual | Age, sex or gender data about individual aid recipients |
| Financial | Budget reports |
| Audit/compliance | Reporting against legal or regulatory requirements, such as for safeguarding or counter-terrorism or sanctions |
| Situational | Analysis of security situation |
| Organisational | Contact information for project officer |
| Disaggregated indicator | Location-specific data for those assisted in a project |
| Aggregated indicator | Total number of people assisted in a project |
Varying expectations and standards
My research also found that donors have varying expectations of their partners – both among and within donor governments (e.g., at the country or headquarter levels) – and humanitarian actors have differing experiences of data sharing with donors. Expectations are informed by factors such as the complex regulatory frameworks for data (eg. host or donor government law, particularly in the context of privileges and immunities), the type of agreement (eg. grants or contracts), and funding allocations (eg. project-specific vs non-earmarked funding).
Donors varied in terms of the level of detail and the type of markers or indicators they requested. For example, United Nations agencies and Red Cross movement actors often have overarching agreements with donors that cover a range of activities in a country rather than project specific funding, as is often the case for non-government organisations (NGOs). The formal reporting for these overarching agreements is less specific, often requiring less formal sharing of disaggregated programme-related data even if it does not preclude or prevent informal requests for such data.
Both donors and humanitarians agreed that informal requests also occur, more often for context-specific information or aggregated data, and in some cases, for sensitive or personal data. The most common type that interviewees named was requests for data related to monitoring programme delivery, such as disaggregated or aggregated indicators. Even so, donors and humanitarians confirmed that standards varied for partners, indicating that in general NGOs were required to provide the most detailed information. By contrast, donors more often accepted annual reporting statements for the UN and Red Cross, often because of the nature of the funding allocations or agreements.
Why does this matter for more effective humanitarian response?
First, not clearly defining what ‘data’ means makes it possible to have inconsistencies in the logic of handling data, to request data that should not be shared, and to compromise the principle of ‘do no harm.’ To mitigate against this, both donors and humanitarian actors must clearly define the type(s) of data that will be shared in the course of a partnership or contractual relationship. Without clarity on the type of data under discussion, it will be difficult to increase data literacy in the humanitarian sector, or to advance conversations and practice to more responsibly manage and protect data.
Second, an indirect yet mutually-reinforcing relationship exists between requests to share data and the need to collect data. Although my research focused on data sharing as opposed to data collection, the interviews and documentation point to an indirect relationship between the two: data are collected in part because they are meant to be shared. Meaning, humanitarians collect data partly because donors ask them to share data. Requests for data sharing, in turn, are driven by differing needs, which leads to collecting more data than strictly needed, with potentially higher risks to those whose data are collected.
Finally, while humanitarians have the ability to push back against donor requests to share data, this ability is greatly influenced by power dynamics and trust. This in itself is a further dilemma, given that this level of trust is more likely to exist between donors and established humanitarian actors, creating another, largely invisible barrier for newer, less established, usually national or local humanitarian actors – a barrier that undermines efforts to ‘localise’ humanitarian response.
Building the practice of responsible data sharing therefore requires a sector-wide effort to increase data literacy across humanitarian actors and donors, and ultimately to protect those who should be at the centre of humanitarian response – those affected by conflict, violence, or disaster.
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