Data quality rating & Primary data share according to Catena-X

To increase the significance and transparency of your product footprint, you can assess the data quality of your emission factors and activity data in Climate Hub. Based on these assessments, the system calculates two key indicators:

Data Quality Rating (DQR):
Describes how well the emission factors used represent the actual situation in terms of time, geography and technology.

Primary Data Share (PDS):
Describes what proportion of your activity data and emission factors is based on primary data.

You will find both indicators in the "Analysis" → "Data Quality" tab. Use the two checkboxes to switch between data quality rating and primary data share.

The feature helps you systematically document the quality of your data, make uncertainties in the CO2 footprint transparent, make the use of primary data visible, identify potential for improvement in your data collection, and meet the requirements of Catena-X.

1. Recording the Assessment

You enter the assessments in two places:

You record the type of emission factor and its temporal, geographical and technological representativeness when creating or editing an activity.
You assess the data type of the activity directly in the data table via the "Data category" column.

Both indicators are then calculated from these inputs: the type of emission factor and the data type of the activity determine the primary data share; the representativeness of the emission factor determines the data quality rating.

2. Data Quality Rating (DQR)

The data quality rating describes how well the emission factors used represent the actual situation. It is based exclusively on the assessment of the emission factors – the assessment of the activity data is not included.

2.1 Input: Representativeness of the Emission Factor

For each emission factor, you can assess three dimensions – temporal, geographical and technological representativeness – each on a scale from 1 (very good) to 5 (very poor).

Note: If no assessment is made, "Very poor" is assumed automatically.

Temporal representativeness - How good is the emission factor compared to the reporting year?

Bewertungsstufe	Definition
Very good	≤ 1 year
Good	> 1 year und ≤ 2 years
Fair	> 2 years und ≤ 3 years
Poor	> 3 years und ≤ 4 years
Very poor	> 4 years

Geographical representativeness - How well does the region of the emission factor match the region under consideration?

Bewertungsstufe	Definition
Very good	The emission factor comes from the same region as the process under consideration (e.g. site-specific data).
Good	The emission factor matches the same country, but not exactly the same region (e.g. country-specific average data).
Sufficient	The emission factor refers to a larger region, not a specific country (e.g. European average data).
Poor	The emission factor is based on global average values without regional differentiation (e.g. global database values).
Very poor	The origin of the emission factor does not match the region under consideration or is unknown.

Technological representativeness - How well does the underlying technology of the emission factor used match the actual process?

Bewertungsstufe	Definition
Very good	The emission factor is based on the same technology as the process under consideration, directly at the same site (e.g. when measured data from your own facility is used).
Good	The emission factor is based on the same technology, but not exactly at site level (e.g. data from another plant of the same company).
Sufficient	The emission factor is based on general industry average data, e.g. a database value.
Poor	The emission factor is based on a comparable technology, e.g. using a similar material or process.
Very poor	The technology underlying the emission factor does not match the real process or is unknown.

2.2 Calculation

For each structural element, a DQR is calculated for each of the three dimensions as a weighted average across all activities; the absolute CO2e values incl. biogenic CO2 uptake serve as the weight. The aggregated DQR is derived as the mean of the three dimensions:

Aggregated DQR = 1/3 (DQR temporal + DQR geographical + DQR technological)

Important: Since the data quality rating is based on the CO2e values incl. biogenic CO2 uptake, activities without this value are not taken into account.

2.3 Results

[Screenshot Analyse - Datenqualität]

The results of the data quality rating are displayed as a table per structural element. The three dimensions (temporal, geographical, technological) and the aggregated DQR are shown. Each value is on a scale from 1 (very good) to 5 (very poor); the color of the circles reflects the classification on this scale. A low value (close to 1) shows that your data represents the actual situation well. A high value (close to 5) indicates insufficient representation or missing information – here there is potential for improvement, e.g. through the use of more up-to-date or more site-specific data.

3. Primary Data Share (PDS)

The primary data share describes what proportion of your data is based on primary data. It is calculated from the type of emission factor and the data type of the activity.

3.1 Input: Type of Emission Factor

The type of emission factor determines whether the emission factor is considered primary. Only a supplier-specific emission factor is considered primary and is therefore included in the calculation of the primary data share.

[Screenshot Dateneingabe - Primärdatenanteil]

Type	Description
Supplier-specific EF	Emission factor comes directly from the supplier
Activity-based EF (database)	Emission factor comes from a database and is based on physical quantities
Spend-based EF (database)	Emission factor comes from a database and is based on spend
Unknown / Other	Origin or methodology of the emission factor unclear

For a supplier-specific emission factor, you can enter the exact primary data share manually in the "Primary data share" field.

Note: If no type is specified, "Unknown / Other" is assumed automatically, which results in a primary data share of 0%.

3.2 Input: Data Type of the Activity

You assess the data type of the activity in the data table via the "Data type" column. It indicates whether the data is primary or secondary. Only activity data classified as primary is included in the primary data share.

[Screenshot Datentabelle]

Data type	Description
Primary	Activity data is based on primary data
Secondary	Activity data is based on secondary data

For existing reports, the previous rating levels are migrated automatically:

Old	New
Very good	Primary
Good	Secondary
Sufficient	Secondary
Poor	Secondary
Very poor	Secondary

After the migration, please check whether the transferred values correctly reflect your data and adjust them manually if necessary.

3.3 Calculation

To obtain a primary data share ≠ 0, the following three conditions must be met:

The activity is classified as primary.
The emission factor is a supplier-specific EF.
The supplier's primary data share is specified in the corresponding field.

If one of these conditions is not met – for example because no supplier-specific value has been entered – a primary data share of 0 % is assumed.

The primary data share across all activities is calculated as an emission-weighted average – activities with higher emissions have a greater influence on the result. Negative emissions are included with their absolute contribution in the calculation, so that both positive and negative emissions are weighted correctly. Otherwise, in extreme cases, the primary data share could fall below 0 % or exceed 100 %.

Important: Since the primary data share is based on the CO2e values incl. biogenic CO2 uptake, activities without this value are not taken into account.

3.4 Results

[Screenshot Analyse - Primärdatenanteil]

The primary data share is displayed per structural element as a horizontal bar chart. The colors show at a glance which range the primary data share is in:

Colour	Range
Red	< 25 %
Yellow	< 50 %
Turquoise	< 80 %
Green	> 80%

A high primary data share shows that your footprint is based on a large proportion of real, reliable data and therefore has a high level of transparency. A low primary data share, on the other hand, indicates that databases or estimates were predominantly used, or that no information on the primary data share was provided – here there is potential for improvement in data collection.