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UID:pretalx-foss4g-europe-2025-8GJRDX@talks.staging.osgeo.org
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DESCRIPTION:Over the last decade\, the global landscape of data sharing has
  gone through profound changes that also applied to the geospatial domain\
 , where traditional Spatial Data Infrastructures (SDIs) have progressively
  evolved into multifaceted data sharing ecosystems [1]. These ecosystems e
 mbraced fundamentally new elements in terms of: (big) data sources (e.g. f
 rom research\, Earth Observation\, Internet of Things devices\, crowdsourc
 ing initiatives\, synthetic data from Artificial Intelligence/Machine Lear
 ning algorithms or Digital Twins)\; technology and infrastructures (e.g. c
 loud/edge/fog architectures\, standards to encode and share data\, AI/ML m
 odels)\; actors such as private companies and citizens becoming valuable p
 roviders of data and services\; legislation (e.g. to open up data\, foster
  data sharing and protect privacy)\; and business models and governance me
 chanisms [2\,3].\nWithin this modern and dynamic context\, it becomes incr
 easingly important to setup targeted\, fit-for-purpose\, and efficient mec
 hanisms to monitor the status and evolution of SDIs to extract the insight
 s needed by policy and decision makers. In this work\, we present the expe
 rience of monitoring the implementation of the European SDI established af
 ter the INSPIRE Directive\, reflect on the lessons learnt from the process
 \, and distill some recommendations for future policy-relevant scientific 
 work.\nIn force since 2007\, the INSPIRE Directive [4] set the legal basis
  to create an interoperable pan-European SDI based on the SDIs of the Euro
 pean Union (EU) Member States\, with legal and technical requirements on t
 he FAIRness (Findability\, Interoperability\, Interoperability\, Reusabili
 ty) of data: discoverability through metadata\, accessibility through netw
 ork services\, and interoperability through common data models. The status
  of implementation for each Member State is assessed through an annual mon
 itoring exercise\, in which 19 indicators defined in a legal act [5] are c
 alculated based on the metadata harvested each year from the Member States
  catalogues. These are grouped in 5 categories focused on: i) availability
  of datasets\, ii) conformity of metadata\, iii) conformity of datasets\, 
 iv) accessibility of datasets\, and v) conformity of network services. Sin
 ce the entry into force of the legal act on INSPIRE monitoring [5] in 2019
 \, the Joint Research Centre (JRC) of the Commission has calculated those 
 indicators for 6 consecutive years\, thus producing a valuable time series
  from which to derive insights and lessons learned\, which in the followin
 g are grouped in three categories: i) geospatial resources (data\, metadat
 a and services)\; ii) tools/technology and iii) community/governance.\nReg
 arding the resources shared by the Member States\, over the last 6 years I
 NSPIRE implementation has overall advanced. Although it remains heterogene
 ous across countries\, aggregated statistics on the indicators show that m
 ore datasets have been made available and these are increasingly more inte
 roperable and accessible. Nevertheless\, challenges remain as e.g. i) some
  indicators rely on self-declarations of conformity made by data providers
 \, which were proven to be unreliable\; ii) indicators are provider-centri
 c\, i.e. they describe the offer from data providers but not their actual 
 adoption and reuse by the public\; iii) they do not analyse the quality of
  the datasets\; and iv) while capturing the amount of available datasets\,
  they do not capture the presence or lack of specific datasets. Research s
 hould investigate ways to address these challenges without increasing the 
 required effort\, e.g. by leveraging new\, AI-based solutions.\nTools and 
 technology have played a crucial role in the INSPIRE monitoring process. T
 he calculation of indicators has been fully automated and the software sta
 ck has evolved over the years and currently includes all open source appli
 cations: the [INSPIRE Geoportal](https://inspire-geoportal.ec.europa.eu/sr
 v/eng/catalog.search#/home) based on [GeoNetwork](https://geonetwork-opens
 ource.org/)\, the [INSPIRE Reference Validator](https://inspire.ec.europa.
 eu/validator/home/index.html) based on the [ETF](https://github.com/etf-va
 lidator)\, and a set of custom-made open source Python and SQL [scripts](h
 ttps://github.com/INSPIRE-MIF/mr-tools). The open source nature of the com
 ponents\, with clear release processes allowing data providers to test the
 ir implementations in advance\, ensures objectivity\, transparency and rep
 roducibility of results. The use of a reference validation tool also bring
 s legal certainty to the process. Additionally\, Large Language Models (in
  particular\, the open-source Mixtral) have proven extremely useful in ref
 ining\, testing\, and validating results. Finally\, the monitoring process
  has benefited from integrating newly developed standards such as OGC API 
 - Features for data sharing and GeoPackage for data encoding\, enabling Me
 mber States to streamline and modernise their infrastructures in a legally
  viable way.\nFinally\, the success of the INSPIRE monitoring exercise\, a
 n iterative process undergoing incremental changes over the years\, relies
  on establishing a continuous dialogue and building trust with the relevan
 t community. This is achieved through a clear governance structure\, provi
 sion of open and scientifically sound guidance on indicator calculation\, 
 clear explanation of results\, and targeted\, country-specific feedback on
  potential improvement areas. The process has also highly contributed to t
 he evolution of the open source tools mentioned above.\nThe lessons learne
 d from this unique SDI initiative\, with no equivalent in temporal and spa
 tial extension\, can inform and benefit similar initiatives\, while also h
 ighlighting the need for specific scientific and technological advancement
 s\, including in the field of open source\, to further reduce the distance
  between data and (data-driven) decision-making.
DTSTAMP:20260527T135845Z
LOCATION:PA01 (Quarticle)
SUMMARY:Monitoring the FAIRness of geospatial data: Lessons learnt from the
  European Union - Marco Minghini
URL:https://talks.staging.osgeo.org/foss4g-europe-2025/talk/8GJRDX/
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