An Integrated Information System of Climate-Water-Migrations-Conflicts Nexus in the Congo Basin
Abstract
:1. Introduction
2. Study Region
3. Methodological Approach
3.1. Conceptual Framework
3.2. Desing of Data Collection Tools
- Investigator’s guide;
- Household count sheet;
- Model sheet for sample selection;
- Sample draw sheet;
- Migrant routes sheet;
- A guide to focus-groups and group discussions;
- A guide to semi-direct interviews;
- A survey guide for management of protected areas;
- Household survey questionnaire.
3.3. Field Survey and Sampling
- The first level of comparison relates to the three different provinces in the northeastern part of the DRC;
- The second level of comparison involves urban, peri-urban and rural (cluster) environments in each of three provinces;
- The third level of comparison concerns migration status;
- The fourth level of comparison is gender-related.
- Visiting the cluster and numbering all households counted, using a count sheet, 1 to N (number of households);
- Computing “R” for random sample, R = N/30 and we rounded to double digits after the comma;
- Selecting a random number. To do this, a random number table at n digits (n being the number of values that constitute the entire part of R) is considered. The random number (T1 drawn indicates the ID number, sample number) in the survey base is the first sample unit (first household);
- Selecting the other sample units on the basis of the “R” draw step by creating an arithmetic progression based on T1 and for R = N/30;
- Setting survey numbers. This involves assigning a sequential number of 1 to n to all units held in the household;
- Identifying units of the sample: for each unit we searched for the identifiers of the actors.
3.4. Data Screening and Processing
3.4.1. Data Coding
3.4.2. Data Entry
- Limiting the input of numbers to a given range or to a number of predefined values;
- Make the entry of a variable mandatory;
- Copy the contents of a variable from the previous record into the new record to be entered;
- Create transition to other variables based on the content of the data entered;
- Facilitate computation of variables based on the value of other variables;
- Facilitate computation of complexes operations.
3.4.3. Building the Database
3.4.4. Transformation of the Database from SPSS into an Interactive Data Visualisation Interface
4. Database Architecture and Information System on Climate-Water-Migrations-Conflicts (CEMiC)
4.1. Data Types, Variables and Thematic Areas
- Migration statistics;
- Vital statistics in relation to the different segments of the populations constituting each “local community”;
- The actors, stakes and capacities of influence (powers: formal, informal and spiritual) upon each other;
- Strategies (mobilized social intelligence);
- The norms involved (cultural factors, customs and traditions, state laws, social practices put in place by actors, etc.);
- Statistics of human groups, livestock and land tenure;
- Local evidence of climate variability (images, units of measurements, local concepts, actors, durations of climatic seasons, flood levels, and regularity or irregularity of precipitation) and the links between climatic factors-migratory pressures-the availability or unavailability of water resources, the nature and types of violence and conflicts associated with them, and the mechanisms of resilience of communities;
- The perception of population, involving men, women and children on migrants and climate change;
- The experience of migrants themselves in transhumance, migration routes, cultural and natural realities encountered in transit and reception places;
- Differences constructed in the socio-cultural context of the Congolese, particularly in the provinces under study, including how conceptions and forms of masculinity/femininity facilitate or hinder gender equity in various areas of the country’s development;
- Shared views, different points of view.
- Two criteria are used for the classification of the data types, including aggregation and the scale of measurement. Aggregation of variables consisted of compiling information contained in the database with the aim to constitute ensembles of data for data analysis [23]. The individual variables, also called disaggregated variables, contain the statistical characteristics of these ensembles. From a scale of measurement point of view, the variables are either qualitative or quantitative. Therefore, the disaggregated variables refer to the statistical nature of the variables which are quantitative or qualitative; nominal, ordinal, discrete or continuous.
4.2. Open Access Integrated Information System and Functionalities
- An online spreadsheet (Google Sheet) that allows data storage and correction of possible encoding during processing.
- An online tool for converting data into customizable informative reports and tables (Data Studio), which is used to produce the tables, graphs and filtering tools.
- A content Management System (Wordpress), known as one of the most effective tools for search engine optimization. It is used for the design and dynamic updating of websites or multimedia applications. A website dedicated to the presentation of data has been set up with the Wordpress tool connected to Data Studio.
- Home page: The home page is the link between the information system and visitors or users. Its purpose is to provide visitors or users with intuitive navigation of the platform’s data. It therefore has two essential functions, namely to clearly present and enhance the platform through various data updates and to direct the flow of visitors. It displays the list of themes in a structured way.
- Display of themes: The themes are organized in the second place, and each contains a list of variables. Each theme is described in a summarised way to allow visitors or users to get a feel for the content. Fifteen themes have been structured in this platform, each containing variables.
- Display of variables: The variable is the last unit of presentation in the information system and is presented in two ways, namely tabular and graphical. In the presentation of the variable, two navigation possibilities are made available to the user, namely navigation by province and navigation by locality. Two key pieces of information are also highlighted for each variable, namely the response modalities and the numbers (for the table) or percentages (for the graph). For every variable, a table and a graphic can be displayed, and the filter tools are used to facilitate navigation based on the three administrative boundaries, the territories or localities (Figure 12). The user will also find two filters next to the variable for downloading data in CSV format and for redirecting to appendix data (focus group and semi-structured interview transcript sheets) to the variable in word or pdf format.
5. Conclusions and Way Forwards
- Provide practical knowledge for decision makers and other stakeholders, along with enhanced understanding of the vulnerabilities, exposures and risks as well as participatory design of long-term investment and development strategies;
- Strengthen collaboration and experience sharing in the Congo Basin through interactions between researchers, policy makers, communities and other stakeholders;
- Contribute to the capacity building of stakeholders on emerging issues addressed by climate-water-migration-conflict nexus in the Congo Basin;
- Support policy and decision makers in the formulation and implementation of smart solutions to the impacts of climate change and the water crisis in the Congo Basin, with particular attention to the impacts of migration and conflict;
- Support key policy areas and strategies to foster effective stakeholder participation to ensure the management and governance of climate and natural resources, and gender consideration in all aspects, both at national, basin and regional levels;
- Strengthen political commitment to support climate resilient development in the Congo Basin;
- Support of the implementation of Sustainable Development Goals (SGDs), and help strengthen the capacity of local communities, empower women and benefit youth through insights for income and livelihood diversification activities.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Province | Cluster | Cluster Name | Number Household | Sample Size | No Poll | Focus Group | Discussion Group | Individual Interview | Route Sheet |
---|---|---|---|---|---|---|---|---|---|
Bas Uélé | Urban (City of Buta) | Ruby | 320 | 30 | 10 | 2 | 1 | 5 | 3 |
Bagbe | 320 | 30 | 10 | 2 | 1 | 5 | 3 | ||
Alongo | 320 | 30 | 10 | 2 | 1 | 9 | 6 | ||
Peri-urban (City of Bondo) | Makambuwa | 320 | 30 | 10 | 2 | 1 | 6 | 4 | |
Rural (Gaya Chefferie) | Localité Baye | 320 | 30 | 10 | 3 | 2 | 7 | 3 | |
Top Uélé | Urban (City Isiro) | Tely | 328 | 30 | 10 | 3 | 2 | 3 | 2 |
Kongoli | 324 | 30 | 10 | 3 | 1 | 3 | 2 | ||
Edindale | 322 | 30 | 10 | 3 | 1 | 6 | 1 | ||
Peri-urban (City of Niangara) | Ligunza | 300 | 30 | 10 | 3 | 1 | 4 | 3 | |
Rural (Chefferie Manziga) | Nambia | 300 | 30 | 10 | 3 | 1 | 2 | 12 | |
Ituri | Urban (City of Bunia) | Simbilyabo | 360 | 30 | 12 | 2 | 1 | 5 | 5 |
Muzipela | 360 | 30 | 12 | 1 | 1 | 5 | 5 | ||
Lumumba | 360 | 30 | 12 | 1 | 1 | 5 | 5 | ||
Peri-urban (City ofAru) | City ofAru | 300 | 30 | 10 | 2 | 1 | 3 | 4 | |
Rural (NdoSector) | Epulu location | 300 | 30 | 10 | 2 | 1 | 6 | 4 |
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Share and Cite
Tshimanga, R.M.; Lutonadio, G.-S.K.; Kabujenda, N.K.; Sondi, C.M.; Mihaha, E.-T.N.; Ngandu, J.-F.K.; Nkaba, L.N.; Sankiana, G.M.; Beya, J.T.; Kombayi, A.M.; et al. An Integrated Information System of Climate-Water-Migrations-Conflicts Nexus in the Congo Basin. Sustainability 2021, 13, 9323. https://doi.org/10.3390/su13169323
Tshimanga RM, Lutonadio G-SK, Kabujenda NK, Sondi CM, Mihaha E-TN, Ngandu J-FK, Nkaba LN, Sankiana GM, Beya JT, Kombayi AM, et al. An Integrated Information System of Climate-Water-Migrations-Conflicts Nexus in the Congo Basin. Sustainability. 2021; 13(16):9323. https://doi.org/10.3390/su13169323
Chicago/Turabian StyleTshimanga, Raphael M., Génie-Spirou K. Lutonadio, Nana K. Kabujenda, Christian M. Sondi, Emmanuel-Tsadok N. Mihaha, Jean-Felly K. Ngandu, Landry N. Nkaba, Gerard M. Sankiana, Jules T. Beya, Anaclet M. Kombayi, and et al. 2021. "An Integrated Information System of Climate-Water-Migrations-Conflicts Nexus in the Congo Basin" Sustainability 13, no. 16: 9323. https://doi.org/10.3390/su13169323
APA StyleTshimanga, R. M., Lutonadio, G. -S. K., Kabujenda, N. K., Sondi, C. M., Mihaha, E. -T. N., Ngandu, J. -F. K., Nkaba, L. N., Sankiana, G. M., Beya, J. T., Kombayi, A. M., Bonso, L. M., Likenge, A. L., Nsambi, N. M., Sumbu, P. Z., Yuma, Y. B., Bisa, M. K., & Lututala, B. M. (2021). An Integrated Information System of Climate-Water-Migrations-Conflicts Nexus in the Congo Basin. Sustainability, 13(16), 9323. https://doi.org/10.3390/su13169323