ModernStats Community of Practice

Starting April 2023, the Supporting Standards Group of the UNECE HLG-MOS is launching a series of on-line events "ModernStats Community of Practice (CoP)" that aims to bring international experts in the statistical organisations together and facilitate the exchange of knowledge and experience in using ModernStats models. The event is open to everyone interested in using the models and the materials from the event will be published online.

Upcoming ModernStats Community of Practice meeting

** Let UNECE know (choii at un dot org) if you wish to propose a topic for next CoP meeting

Past ModernStats Community of Practice meetings

Linked Open Data (4th December 2023)

What are the FAIR data principles, and how they can benefit the dissemination of official statistics? How can organizations effectively assess their compliance with FAIR principles, and in what ways does Linked Open Data (LOD) notably improve the experience of users of statistical data?

FAIR principles stand as an essential set of guidelines for any organization wishing to make their data and metadata Findable, Accessible, Interoperable and Reusable. Representing statistical datasets and structural metadata in RDF (LOD) can enhance compliance with the FAIR principles:

• Statistical data and structural metadata are identified by unique identifiers and described with metadata which makes data easily Findable.
• By using standards, structural metadata can be integrated into data making them are Accessible and Interoperable.
• Data are Reusable in open and machine-readable formats, with metadata describing the provenance and usage of data.

Many statistical organizations expose their datasets as RDF within open data catalogues using DCAT or its extension, DCAT-AP. While the DCAT or DCAT-AP descriptions provide useful information to users, they often lack information about the structural metadata used within each dataset. As a result, retrieving datasets from different sources (different statistical organizations) sharing the same dimensions or resulting from the same statistical activity is not systematic.

Additionally, considerable work has been done on how structural metadata (statistical classifications) should be conceptually (Neuchatel Model, GSIM) or technically modelled (XKOS - Extended Knowledge Organization System). However, the number of statistical organizations exposing their structural metadata as Linked Open Data is still limited and, overall, there has been less work on the definition of a common API for the retrieval of metadata.

The presentations and discussion at our next event revolve around the theme of Linked Open Data and why Fair Data Principles are important for the dissemination of official statistics.

We invited four speakers to give perspectives on producing official statistics in international organizations and a national statistical organization, to talk about their experiences and practices. We also aim at facilitating the exchange of information between organizations producing official statistics and gather feedback for the further development of the Linked Open Data statistical ecosystem, and therefore we are looking forward to hearing your experience, your successes and challenges in this area.

Modernizing management systems: modeling processes using ModernStats models (28th April 2023)

What are the traits of successful organizations, what management tools and practices do they use to cope with the changes in the environment, support innovation and improve data quality and organizational efficiency? As the role of data in society evolves, what management techniques can statistical organizations use that help them stay relevant? How can ModernStats models support the modernization of management systems and in what aspects do they need to be improved to better serve the needs of the statistical community?

Modeling, breaking down processes into standard building blocks, describing tasks, inputs and outputs, assigning responsibilities, are practices that produce information on different aspects of the architecture for management purposes. The applications are manifold: organizations use these techniques to better understand their systems, to streamline everyday operations, to plan development projects, to evaluate certain activities or areas, to find inconsistencies or to standardize, automate, rationalize activities or elements they handle. ModernStats models, developed under the umbrella of UNECE HLG-MOS have been created with the intent to support the modernization endeavors of organizations producing official statistics. The Generic Statistical Business Process Model (GSBPM), the Generic Statistical Information Model (GSIM) and the Generic Statistical Activity Model (GAMSO) provide generic elements that may be used for modeling purposes.

The presentations and discussion at our next event revolve around the theme of modernizing management systems in official statistics and modeling processes using ModernStats models. We invited four speakers from national statistical organizations and an international organization producing official statistics to talk about their experiences and practices. We also aim at facilitating the exchange of information between organizations producing official statistics and gather feedback for the further development of the ModernStats models, therefore we are looking forward to hear your experience, your successes and challenges in this area.

Programme