We're standing at the onset of a “data tsunami.” Though the use of big data in humanitarian response is rapidly rising in popularity, it is not very clear how field managers should actually incorporate such critical information into their operations. In actuality, many humanitarian organizations have found it difficult to effectively utilize big data in humanitarian service delivery.
Seeing the promise of big data and, at the same time, hearing disparaging comments from humanitarians unsure what big data is or how to integrate it, the Digital Humanitarian Network’s community of interest on Decision Makers Needs has created a guidebook to help humanitarians unlock the potential.
Produced with the support of UN-OCHA, “Guidance for Incorporating Big Data into Humanitarian Organizations” is intended to assist information or data focal points in humanitarian organizations to understand the variety of, the categories of, and possible approaches to integrating big data into their organizations. The document describes big data and its role within the humanitarian sector, offers a categorization of the large variety of big data types, highlights the benefits and risks of incorporating big data into response, identifies policy and ethical considerations for organizations, and provides example materials that organizations can use when starting the process of incorporating big data.
Authors Katie Whipkey, MSPPM ’16 Carnegie Mellon University Heinz College, and Andrej Verity, UNOCHA, state the goal is to “create dialogue and generate structure in the conversation among decision makers, data scientists, and volunteers and technical communities.”
This report is intended for humanitarian response organizations looking for new and innovative ways to combat difficulties crises – these organizations may not necessarily know how to use big data or at all, or might be looking to use it more strategically and effectively. The document can also be of use to development agencies, policy makers, or other international organizations interested in implementing big data analysis into their business model.