FAIR Digital Objects in Official Statistics

Introduction*1 Statistical offices on national and international scale provide statistics demography, labour, income, society, economy, environment other domains. Their collective output is usually referred to as ‘Official Statistics’. These have a long tradition of publishing data fairly open, which often part their mission statement. For decades they been providing websites with articles, press releases, graphs tables for free, research, policy-making, common understanding. However, users it not so easy find the needed, (re-)use in data-driven work or refer right (sub)set sustainable way. Therefore, this article we take closer look at Official Statistics from findable, accessibility, interoperability, reusability (FAIR) perspective. Digital Objects objects official can be identified multiple levels. The core concept statistical fact : number describing certain estimate phenomenon population over period time. example estimated elderly inhabitants Province Friesland (the Netherlands) Jan 1, 2020, inflation Belgium fruits 2021 are both facts. Each these facts uniquely defined published digital object online databases Netherlands Eurostat respectively. may production status (provisionary, final, revised) typically visualized table cell chart. Data without metadata meaning. A refers (region, time, subject, population, uncertainty, quality etc.) essential understand context fact. We make distinction here between structural conceptual , i.e. structure definitions concepts, dimensions types used, referential descriptive information dataset. utmost importance consumer data. Metadata own dynamics, e.g. classifications change They too, classification economic activities (NACE). form foundation higher level products. News releases thematic articles that explain broader examples. This content seen too main entry general public search engines enables findability accessibility. Standards FAIR has its structure, dissemination channels standards. sometimes hard statistics. differ among organizations, technically well API’s offer automated access. Main standards field eXchange (SDMX), JSON-stat, OData, simple formats such CSV. Commonly agreed organized into SDMX registries (global registry, registry), access metadata, good standard actually targeted financial hinder wider reusability. Therefore some moving semantic An an vocabularies linked open by Netherlands. Publishing way makes possible reuse link across organizations gives machine readable. Another office European Union, Eurostat, converting correspondence current system Linked Open EU Vocabularies website. representation based XKOS, ontology modelling classifications, offering machine-readable reusing facilitating linking national, level. Yet another initiative United Nations Economic Commission Europe (UNECE), where collectively develop Core Ontology (COOS) process. All all increasingly towards better align non-statistical communities. In Single Integrated Structure (SIMS) used. It offers unit measure, reference period, confidentiality, quality, accuracy etc. Some elements also covered widely used RDF-based Catalog Vocabulary (DCAT) variant (STAT-DCAT), raises question whether further integration could improve FAIR-ness metadata. With respect objects, use web ontologies schema.org Dublin annotating terms being Object Identifiers (DOIs) applicable easier output. From above see different levels creates various ways identify content, Uniform Resource Names (URNs), identifiers, Odentifiers (DOIs), (URIs) organization specific identifiers. Although probably satisfy principle A1, user perspective would minimize variety here. Wrap-up experience data, principles excellent vehicle enable work. Openness enough, facts, should ideally optimized point view. mix distributed Moving semantic-interoperability via generally accepted ongoing promise increase (meta)data. trustful more FAIR, searchable, findable interpretable necessary