Information Landscape Mapping: A Technical Brief Based on JIPS’ Country Support (JIPS, Dec 2023) - JIPS - Joint IDP Profiling Service

Information Landscape Mapping: A Technical Brief Based on JIPS’ Country Support (JIPS, Dec 2023)

Related Topics: Methods, Joint analysis, Innovation

This technical brief provides practitioners with a step-by-step guide alongside practical templates needed to map and analyze the information ecosystem in internal displacement settings. It enhances their understanding of the use of such an undertaking and how to amplify its impact along the process, offering insights from JIPS’ hands-on involvement in fostering Information Landscape Mapping (ILM) within collaborative initiatives in Somalia, Burkina Faso, and Ukraine.

This brief goes beyond the basics of what ILM entails by delving into the core reasons why it holds particular significance within the context of internal displacement. JIPS’ emphasis on collaboration resonates throughout the step-by-step process we present, equipping practitioners with the knowledge and tools needed to navigate dynamic data ecosystems, build a common understanding of the information gaps and needs among different stakeholders, and promote data interoperability.

Aside from the hands-on templates, the brief also discusses the key criteria against which a data source can be assessed for suitability, completeness, comparability, and reliability. These tools can be used in conjunction with JIPS’ other tools available on the JIPS Essential Toolkit.

What is information landscape mapping?

ILM is a collaborative and data-driven process that aims to foster a comprehensive understanding of the information ecosystem surrounding a specific context. It involves identifying and analysing the various data sources and stakeholders within the context. The process facilitates the coordination and collaboration between different actors involved in data collection, management, analysis, and use.

In the context of internal displacement, the process of mapping the information landscape assumes a crucial role, given that practitioners often encounter two daunting scenarios: In a new displacement crisis they may face stark scarcity of relevant data, while in a protracted context they may find a great diversity of data sources and methodologies that are not harmonized, complete, and/or suitable. These challenges underscore the critical need for a systematic approach to navigate and make sense of the diverse data ecosystems in internal displacement situations. An ILM can assist practitioners in addressing these challenges by providing a structured framework for the comprehensive analysis of data sources from various stakeholders and their use against specific information needs. It contributes directly to building a robust, quality evidence-base that can inform sound decision-making and responses towards solutions for internally displaced persons (IDPs).

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