160x Filetype PPTX File size 0.58 MB Source: ec.europa.eu
Contents Introduction AS IS analysis TO BE Scenarios • Medium-term scenario • Long-term scenario Maturity assessment Roadmap toward a ESS LOD ecosystem PwC 2 Main objective of this gap analysis Assess the maturity of the NSIs against the vision painted in the joint LOD strategy at ESS level PwC 3 How have we assessed the gap? Completing an AS IS analysis by: • Documenting LOD initiatives and activities in the ESS, focusing on what pioneering NSIs are doing with LOD, and analysing it based on the business model canvas; • Identifying the main aspects to make a statistical LOD project successful according to the interviewed NSIs, e.g. enablers, risks, challenges; Defining TO BE scenarios • Based on the prioritisation of LOD activities defined in the joint LOD strategy. This has led to two TO BE scenarios: a medium-term and a long- term one. Performing a maturity pre-assessment of the NSIs by: • Creating an assessment tool for evaluating the current state of the NSIs with regards to the two proposed scenarios; • The pioneer NSIs working on LOD, who have been interviewed in this study: Carrying out an assessment for the interviewed NSIs. Alain Darren Eoin Monica Franck Nadeau Barnes McCuirc Scannapieco Cotton (FSO, (ONS, UK) (CSO, (ISTAT, (INSEE, Switzerland) Ireland) Italy) France) PwC 4 AS IS Analysis Value propositions Flexible data integration Creation of partnerships within NSIs and with others Integration of data requires LOD facilitates statistical data collaboration on LOD initiatives and integration and enables the creation of partnerships between NSIs interconnection of previously as well as with research and industry. disparate datasets of different formats and type, housed in different Innovation and development of data warehouses, data bases, data new services stores and files within and across NSIs. Availability of LOD and its easy integration with other internal or Promoting data external data (both statistical and from standardisation other data domains) can give rise to LOD allows and encourages NSIs to new services offered by the NSIs or enhance the statistical data and other organisations. metadata standardisation process. Increase in data quality LOD in statistics heavily capitalises The increased use of LOD triggers on and promotes standards, such as demands to improve data quality. HTTP URIs, RDF, SDMX and Through crowd-sourcing, feedback StatDCAT-AP. and self-service mechanisms, errors can be progressively corrected. PwC 6 AS IS Analysis Overview of use cases from the ESS Interconnect official Publish official statistics Interconnect datasets statistics datasets from in machine-readable, within a NSI different NSIs and/or linkable formats Eurostat • LOD for territorial bases • Scottish Index of • Providing catalogues of (ISTAT, Italy) Multiple Deprivation linked metadata of open • Selecting the best place (Scottish Government) datasets (EU Open Data to live or to invest • Relate/correlate different Portal and European Data (Maynooth University) sources which provide Portal) • LOD for fact-checking information about a • ModernStats - Linked • Finding data for a specific domain Open Metadata (UNECE) postcode (ONS (Evangelos Kalampokis, • Integrated access to EU Geography) UOM) and BEA data (Eurostat • Accessing and querying and BEA) census data (CSO, Ireland) • Digital Agenda • Evolution of Swiss 1 2 Scoreboard (DG 3 communes (FSO, CONNECT) Switzerland) PwC 7
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