Data Inventory

Are you a public sector body and do you hold public sector data? If so, you will find information here on how to list your data in the Public Sector Data Catalogue (CDSP).

Data inventory follows a clear, structured procedure involving several steps. It all starts with a preparatory phase where you define your inventory project and its scope, and assign key roles within your organisation (inventory coordinator(s), metadata creator(s), proofreader(s) and approver(s)).

Next up is the actual inventory creation stage, which consists of:

• auditing existing data: draw up an initial list of all your structured data sources;
• prioritisation: evaluate your data according to its internal and external value, stability and quality;
• in-depth analysis: if necessary, organise workshops with your business experts to understand each data source in detail;
• metadata creation: describe your datasets in the CDSP's Metadata Capture Tool. Choose one of the two available instances:
  • CTIE instance, if your organisation is part of the CTIE network (access via IAM roles);
  • LNDS instance, otherwise. 

Once your metadata has been created and approved internally, submit it to the Ministry for Digitalisation for publication in the CDSP.

For further information, download the inventory guide.

Luxembourg has adopted DCAT-AP-LU, a Luxembourgish extension of the European DCAT-AP standard. This standard ensures that your metadata is interoperable with national and European catalogues so that your data speaks the same language as that of other countries! 

DCAT-AP-LU defines how to describe your catalogues, datasets and distributions in a structured and harmonised manner. Each dataset must contain at least a title and a clear and understandable description. The standard also covers aspects specific to the Luxembourg context, such as the types of protection applied to data, restrictions on use and a list of public sector bodies. The complete documentation for the standard is available here.

For structured data, it is strongly recommended that you also provide a data dictionary that describes each variable (field) individually – an essential tool for data access requests and reuse.