Two options to overcome challenge n°1

Option 1: Limit the exercise to the level of the datasets (exclude the indicator matrix)

The exercise is still vast and the scope of the exercise can be further reduced by considering the following:
1) The range of datasets to investigate
For example, Côte d’Ivoire decided to investigate the datasets managed by key sectors involved in nutrition (health, education, gender, social affairs, agriculture, animal resources, water, economy, finance & planning) and other agencies known for managing databases (National Agency for Rural Development, National Water Offices, etc.)
“Key sectors” are those involved in the Multi-sectoral Plan of Action for Nutrition. In some countries this list can be much more vast, including more than ten ministries. For the sake of the data landscape exercise, it is recommended to reduce the list of data providers to investigate to keep the exercise feasible. Other sectors could be investigated in a second stage using the experience of the first exercise.

2) The level of detail of information to collect for each dataset
NIPN teams can decide the level of detail necessary to collect for each dataset. One option is to request a detailed description of datasets only for some prioritised sectors.

Option 2: Include datasets and indicator matrix in the data landscape exercise

The scope of the data landscape exercise can be reduced by looking at:
1) The number and range of indicators to investigate
There are several ways to decide the number and range of indicators to include in the matrix:

Select key data providers instead of selecting indicators. For example, the Côte d’Ivoire NIPN country team decided to investigate all the data available in key ministries (health, education, gender, social affairs, agriculture, animal resources, water, economy, finance & planning) and other agencies known for managing databases (National Agency for Rural Development, National Water Offices, etc.)
Refer to the M&E plan and list of multi-sectoral indicators that are attached to a national multi-sectoral plan of action for nutrition. If this list is still too long, key indicators can be identified and selected. For example, the Guatemala NIPN country team selected 70 key indicators from the M&E plan. This would mean that the indicators matrix is limited to those 70 indicators but the description of the datasets would need to have a wider scope.
Adapt the SUN MEAL system which includes a list of multisectoral indicators (about 300) and a sub-selection of key indicators (about 70) for nutrition.

2) The level of detail of information to collect for each indicator
There are several options to consider when deciding the level of detail for each indicator, which include:

Complete a full indicator matrix. The indicator matrix available here is an example of an in-depth assessment for each selected indicator.
Compile only basic information for each indicator. For example, the NIPN in Burkina Faso listed all the indicators available in the datasets and their definition only.
Complete the indicator matrix in full for key sectors only (Health, Agriculture, Education, etc.) and collate less detailed information for the sectors that are of lower priority. For example, the NIPN in Ethiopia decided to focus on nutrition & WASH in the first phase. This means that a detailed indicator matrix can be completed for these two domains with less detailed information for the other domains.