The preparation of a data landscape report (2/3)
3. Description of the main information systems and datasets available
This is a description of the main information systems with nutrition-relevant information. It addresses questions such as:
- How is data collection organised?
- What systematic data quality control mechanisms are applied?
- Which indicators are collected?
- What are the sampling methods, exact dates of data collection, and population groups covered by the data?
- What is the procedure to access the datasets?
- Which outputs are produced on the basis of this data? For whom and how are they used?
One data provider can manage one or more information systems (e.g. a National Statistical Office manages the Demographic and Health Survey, as well as SMART Surveys).
Typical information systems include: Education Management Information System, Health Information Routine Data (DHIS2), Water Management Information System, Household Income and Consumption Surveys, Health and Nutrition Expenditure Surveys, Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), SMART Nutrition Surveys, and Integrated Food Security Phase Classification Database (IPC)…
4. Indicator matrix
Ideally, an Excel file is populated with information for all the indicators included in the data landscape (see below for an example of an indicator matrix).
The typical information collected on each indicator includes:
- Name of the dataset(s) to which the indicator is attached
- Definition of the indicator (variables used to generate the indicator)
- Period of data collection
- Year when data was collected
- Data collection sampling method (e.g. survey, routine)
- Geographic coverage
- Organisation(s) that collect and manage the data
Note that indicators from different datasets may not be directly comparable (see Challenge n°3 on page 8 of this section).
|The indicator matrix in an Excel file (as in the example provided below based on Niger’s experience) is an ideal output of a data landscape exercise. It describes in which datasets you can find the indicator you are looking for to answer the policy-relevant question identified. However, as detailed in Challenge n°1 (see page 6 of this section), describing all the indicators available in all the datasets of interest to the NIPN can be a very vast piece of work. Ivory Coast, for example, decided to describe the information systems and the datasets of interest to the NIPN without describing precisely the indicators available in these datasets, and did not develop an indicator matrix.|