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https://ceur-ws.org/Vol-2317/article-11.pdf
A European Strategy for Linked Open Statistics
Luca Gramaglia1, Christine Kormann-Fromageau1, Danny Delcambre1, Jean-Marc
Museux1 and Marta Nagy-Rothengass1
1
Eurostat, Rue Alphonse Weicker 5, Luxembourg
Abstract. Over the past decade, the European Union has promoted the devel-
opment and deployment of Linked Open Data technologies through the financ-
ing of several projects in the framework of the FP7 and Horizon 2020 research
and innovation programs. In recent years, Eurostat, the statistical office of the
European Union, has started to investigate the application of these technologies
in the statistical ecosystem to enable access to new data sources and to improve
the cross-domain discoverability and interoperability of official statistical data.
This paper provides an overview of the different actions Eurostat is taking in
the context of the ESS Vision 2020 modernization program to leverage the sta-
tistical metadata assets of the European Statistical System (i.e. concepts, codes,
nomenclatures) through the use of semantic technologies. In particular, the pa-
per presents the work launched to build and sustain an LOD community of
practice among European statisticians and the ongoing efforts to deepen the
links between well-established standards for the description of statistical data
and the Linked Open Data world. The paper concludes by outlining some ideas
and principles for a reference linked open data architecture in the European Sta-
tistical System.
Keywords: Linked Open Data, European Statistical System, Metadata stand-
ards
1 The role of standards in the European Statistical System – a
brief overview
The European Statistical System (ESS) is the partnership between Eurostat, the statis-
tical authority of the European Union, and the national statistical institutes (NSIs) and
other national authorities responsible in each Member State for the development,
production and dissemination of European statistics. This Partnership also extends
countries belonging to the European Economic Area (EEA) and European Free Trade
Association (EFTA).
Eurostat and the ESS have a long history of promoting harmonization and stand-
ardization in the field of statistics. This is not surprising, as the process of producing
comparable European statistics from several different sources and with the involve-
ment of a large number of stakeholders naturally makes it almost necessary to share a
common language for the collection, processing and dissemination of data. The ESS
2
has adopted its own definition of a standard that is based on the International Organi-
zation for Standardization (ISO) definition and reads as follows:
“A normative document, established by consensus among ESS members and
approved by a recognized body according to the procedure of ESS
standardization, that provides for common and repeated use by several actors
in the ESS. This can be rules, guidelines or characteristics for the
development, production and dissemination of European Statistics, aimed at
the achievement of the optimum degree of order in the context of the
implementation of the mission and vision of the ESS”. [1]
Standards cover all aspects of the statistical production process and are present at
all stages of the statistical production process. The paragraphs provide a non-
exhaustive description of the main areas where the ESS has over the years launched
standardization initiatives.
Standards for data and metadata exchange: Eurostat is one of the Spon-
sors of the SDMX initiative. SDMX 1 (which stands for Statistical Data and
Metadata eXchange) is a standard which supports the automated exchange
of statistical information. It does so by providing an Information Model for
the description of data and metadata assets, statistical guidelines for the
modelling of statistical data, as well as an IT architecture and tools. Moreo-
ver, using SDMX as a basis, Eurostat and the ESS have developed vocabu-
laries for the documentation of the statistical production process. One such
vocabulary, SIMS2 (Single Integrated Metadata System), has established it-
self as the standard for quality and metadata reporting in the ESS.
Harmonized methods: This heading encompasses the methodological re-
sources used by the ESS to produce harmonized data, such as classifications
and methodological manuals. As a general rule, the ESS always tries to
align with global standards (e.g. the International Standard Classification of
Occupations (ISCO) developed by the International Labour Organization)
and develops its own standards only if it needs to collect more detailed in-
formation. Even in these cases, attempts are made to establish mappings be-
tween the global and regional standards. These efforts have given rise to an
integrated network of statistical classifications at global, regional and na-
tional levels. Such an integrated system facilitates comparisons of data sets
based on different classification systems.
IT tools: In recent years, the ESS has expressed increasing interest in the
creation of standards for the sharing and reuse of IT tools. The ESS has ac-
tively participated in the creation of standards such as the Common Statisti-
1
Official website of the SDMX initiative: https://sdmx.org/
2
Description of the SIMS 2.0 standard:
http://ec.europa.eu/eurostat/documents/64157/4373903/SIMS-2-0-Revised-standards-
November-2015-ESSC-final.pdf/47c0b80d-0e19-4777-8f9e-28f89f82ce18
3
cal Production Architecture3 (CSPA), whose stated aim is to help create in-
teroperable tools that can be shared within and between statistical organiza-
tions.
2 The opportunities of Linked Open Data for European
statistics
Against the background of this long-standing commitment to standardization in the
ESS, semantic technologies have created new opportunities and expectations with
respect to metadata and data discovery and analysis. In order to retain its position as
leading providers of statistical information and to contribute to the modernization of
public administration by engaging more with citizen and businesses, National Statisti-
cal Institutes (NSIs) in charge of collecting and disseminating official statistics in the
EU must upgrade their data accessibility, discovery and analytics capabilities and
follow a proactive approach in meeting the needs of their key users.
Firstly, end users of EU statistics are looking for better discoverability of
open/public data. Semantic technologies can help improve discoverability and use of
official statistics data by leveraging the rich European Statistical System (ESS) statis-
tical metadata assets (concepts, codes, nomenclatures …). Statistical metadata needs
to be made machine-readable, discoverable and active in data querying and data inte-
gration jobs. This will contribute, on one side, to easing access to EU statistics and, on
the other side, create the conditions for a wider semantic interoperability and accessi-
bility of statistical data produced by public administrations in general. External data
brokers (collecting and reusing data) will also benefit from well-established standard
semantic metadata encouraging them to align with these standards and thus boosting
the (re)use of statistics published by government agencies.
Secondly, policy analysts in charge of the design and evaluation of government
policies have to embrace the complexity of societal and economic changes. This re-
quires analyzing increasingly detailed official statistics and enriching them with
available external information. Currently the official data are publicly available but
their usage is rather tedious as they require quite some technical skills to access and
combine them and a good knowledge of the concepts involved. Further action is
needed to provide an intuitive and integrated data analytics workbench and metadata
driven services to explore, combine and analyze a broad variety of cross-border data
sources, leveraging the wealth of official statistics and the richness of the metadata
assets compiled in the ESS.
3
Official CSPA specifications:
https://statswiki.unece.org/display/CSPA/Common+Statistical+Production+Architecture
4
3 First implementation actions
In recognition of the potential offered by semantic technologies, Eurostat, the statisti-
cal office of the European Union, has started investigating the application of these
technologies for EU statistics. In line with the subsidiarity principle enshrined in the
EU founding treaties and in Regulation on EU statistics, interoperability is the pre-
ferred mode of collaboration of NSIs and Eurostat to produce and disseminate EU
statistics.
The main vehicle for these first steps towards Linked Open Statistics in the Euro-
pean Statistical System is the DIGICOM project4, which is one of the flagship pro-
jects of the ESS Vision 2020 modernization program. In the context of this project, a
number of actions were set in motion: a study was carried out in 2016 to provide an
overview of LOD experiments in the European Statistical System, a joint framework
for action in the field of LOD was adopted and a set of collaborative cross-country
pilots were launched.
3.1 2016 study on LOD activities and use cases
A study [2] was conducted by Price Waterhouse Coopers on practices in NSIs which
have experimented with Linked Open Data. The study looked in particular at the state
of play in the National Statistical Institutes of France (INSEE), Italy (ISTAT), Ireland
(CSO Ireland), the United Kingdom (ONS) and Switzerland (Federal Statistical Of-
fice of Switzerland). It was complemented by an ESS Workshop on LOD held on 18
and 19 January 2017 in Malta. The study and the workshop led to a shared under-
standing of the key benefits of LOD for official statistics. These include more flexible
means of data dissemination, enhanced data exploration between datasets and the
ability to link with other sources (e.g. within a national statistical system) while keep-
ing the information on data provenance. Indirect benefits include fostering internal
coherence of data and metadata, reinforcing the role of NSI as standard setters and
stimulating partnerships.
However, the study highlighted that LOD is an area in which NSIs are still largely
experimenting. Considering scarce resources and the need for specific skills, the study
concluded that these experiments would benefit from a joint approach in the ESS. The
study identified some key priorities, such as: capacity building at NSI- and ESS-level,
including multidisciplinary teams (IT, dissemination, content and classifications),
joint governance for LOD, evaluation of existing technologies, development of a
community of practice in the ESS, and cooperation with experiments outside the EU.
4
A detailed overview of the DIGICOM project can be found at the following link:
http://ec.europa.eu/eurostat/web/ess/digicom
5
3.2 Joint Framework for action (2017-2018)
Based on the results of the Malta workshop and on the findings of the study, a joint
framework for action for the ESS in the field of LOD was developed and endorsed by
the ESS members in February 2017 [3]. The framework for action takes a holistic
approach to the development of statistical LOD and covers five complementary di-
mensions: strategy and policy; people and capacities; data and metadata; technology
and infrastructure; and governance.
The activities foreseen by the framework include:
Common investment in capacity-building and knowledge sharing across
ESS members. The objective is to assist National Statistical Institutes in the
in-house development of core LOD skills and expertise. This has led to the
inclusion of a training course on Linked Open Data as part of the European
Statistical Training Program.
Definition and implementation of standards. Common vocabularies and on-
tologies for describing the statistical data and metadata assets must be
adopted. The Open data community has already relevant standards for such
metadata (STAT DCAT for catalogue, Data Cube Vocabulary for describing
statistical datasets, SKOS for modelling metadata concepts). The ambition
is to close the gap between these standards and the corresponding standards
in use in the statistical community (e.g. SDMX) and, when needed, to de-
velop new ontologies to express the already rich set of statistical data and
metadata assets (e.g. code lists and classifications) and to link them to key
other resources on the web (e.g. DBpedia).
Selection and development of common, reusable IT tools. In order to create
a highest take-up within the ESS a common approach to access mechanisms
such as APIs, SPARQL endpoints and direct URI resolution is required. Eu-
rostat and NSIs should work together on testing and selecting tools. Moreo-
ver, special attention will be given to the development of intuitive interfaces
for users to query European statistics. The objective is to overcome the rela-
tive difficulty of exploiting the power of SPARQL end points or graph data-
bases and to enrich the experience of non-specialist users.
3.3 ESSnet on Linked Open Statistics
One of the main principles of the joint framework for action is that the various build-
ing blocks it foresees should be created through practical experimentation, and in
particular through collaborative cross-border projects.
In order to jumpstart the realization of proofs of concept that can identify and me-
ter the potential of Linked Open Data for the dissemination of EU statistics, at the
6
end of 2017 Eurostat launched an ESSnet 5 involving NSI Bulgaria, INSEE, ISTAT,
CSO Ireland and academic partners. An "ESSnet" is a multi-beneficiary grant given to
a network of several ESS organizations and which is aimed at providing results that
will be beneficial to the whole ESS. ESSnet projects are one of the primary instru-
ments through which Eurostat fosters harmonization, collaboration and the sharing of
best practices within the ESS.
The ESSnet will deliver two main outputs, pilots and a collaboration platform. The
pilots will focus on linking data and metadata at local, national and international level
as well as on linking statistical data and metadata with non-statistical web-based data
– for example, wiki, georeferenced data, etc. The pilots will demonstrate the benefits
of this approach for users, but also help to assess risks and costs. The ESSnet also
aims to stimulate cooperation and provide capacity building for the whole ESS. For
this purpose, it will set up a platform for collaborative work among ESS experts on
LOD topics and will provide training material and webinars, guidance and toolkit on
how to design and build an LOD portal and to use it for standards.
For its part, Eurostat is also developing pilots in close coordination with the ESS-
net. The pilots focus on exploring how Eurostat data and metadata can be modelled as
linked open data. One point of particular interest is the exploration of how the existing
standards and vocabularies used to describe data, metadata and classifications (e.g.
the SDMX and SIMS standards described in chapter 1) can be expressed in a Linked
Open Data environment.
4 Towards a reference architecture for Linked Open Statistics
in the ESS
The knowledge acquired via the experiences and pilot projects outlined above will
allow the ESS to identify common principles and best practices for the use of Linked
Open Data in the context of European Statistics. The intention is that these principles
and best practices should form the basis for the creation of a reference architecture for
Linked Open Statistics in the ESS.
The purpose of a reference architecture is to provide a template for statistical or-
ganizations in the development of their own LOD capabilities and infrastructure. It
shows what capabilities organizations should acquire and how they should organize
and structure systems to disseminate statistical information based on LOD con-
cepts/standard. It does not have a binding character but helps to spread common
views and definitions and to foster collaboration between partners. It can provide a
basis for mapping ESS activities/Proofs of Concept, for kick-starting LOD activities
5
Homepage of the Linked Open Statistics ESSnet project:
https://ec.europa.eu/eurostat/cros/content/linked-open-statistics_en
7
in Member States and for the identification of shared/common building
blocks/solutions.
The reference architecture under development will identify the major use cases and
contain a list of definitions, required capabilities, recommended standards, building
blocks, principles and governance recommendations for statistical organizations who
would like to invest in Linked Open Data and maintain a high degree of interoperabil-
ity with other ESS partners.
References
1. Nadezda Fursova, Jurate Petrauskiene, Vocabulary of standardization related concepts,
https://ec.europa.eu/eurostat/cros/system/files/ESSnet%20on%20Standardisation_SGA_2_
WP1_Del1.pdf, last accessed 2018/06/15
2. Price Waterhouse Cooper, Study on LOD strategies and use cases in the ESS,
https://ec.europa.eu/eurostat/cros/content/task-2-use-cases-and-analysis_en, last accessed
2018/06/15
3. A joint framework for action on linked open data at ESS level,
https://ec.europa.eu/eurostat/cros/content/item-2-draft-ess-strategy-linked-open-data_en,
last accessed 2018/06/05