1. The LinDA outcomes
The different components developed during the LinDA project are deployable in a common , integrated environment
called the LinDA Workbench hosting all available LinDA tools; nevertheless they are able to operate also independently
from each other, with only front-end components depending on the respective back-end components to fulfil their spe-
cific business functionality. The main available LinDA tools are the following:
The Transformation Engine, intended to data conversion from various input formats to the RDF format
The Vocabulary and Metadata Repository, contains a collection of vocabularies, covering various thematic areas
The Visualisation Tool, to provide a largely automatic visualisation workflow that enables SMEs to visualise data in
different formats and modalities
The LinDA Analytics and Data Mining Ecosystem, A library of basic and robust data analytic functionality is provided
enabling SMEs to utilise and share analytic methods on linked data for the discovery and communication of meaning-
ful new patterns
The Query Builder, enabling users to explore open RDF data and reuse it easily
The RDF2Any converter, to support conversion of RDF to various serialisation outputs like RDB (Relational database
script), JSON, and CSV
The Consumption Apps
IN THIS ISSUE
The LinDA outcomes P.1
The LinDA Publication and Consumption framework P.2
Cost-effective access to linked data for SMEs P.3
Events P.4
LinDA Consumption Apps
Three Consumption Apps are being developed
in the LinDA project, corresponding to the
three pilots run by the Consortium:
Business Intelligence Analytics Pilot
Environmental Analytics Pilot
Media Analytics Pilot
QUARTERLY NEWSLETTER
ISSUE 1 — December 2014
The LinDA quarterly newsletter
This is the first issue of the LinDA newsletter,
aimed at collecting in a freely downloadable
document some of the articles and news ap-
peared on the LinDA website. The newsletter
will be published quarterly and is intended to
reach a broad audience, focusing more on
exploitation and the adoption by the project
stakeholders (from Public Sector Information
(PSI) Providers to SMEs and Enterprises) than
on purely technological issues.
http://linda-project.eu/ 1
2. Due to the proliferation of available
public sector data sources and initia-
tives, the interlinking and combination
of such datasets has become a topic
of major interest within SME infor-
mation managers. While more agile
options for data integration are being
requested, conventional methods of
data integration are not feasible for
use due to the massive size of availa-
ble data. The current state of the
latter data is also mostly unstructured,
thus making it either unaccessible for
SMEs, or else making the cost of utiliz-
ing such data unbearable for SMEs.
This calls for tools that support users
in the re-use of such data, whilst hid-
ing the underlying complexity and al-
lowing the re-use of existing software
applications.
The LinDA Publication and Consump-
tion Framework aims to assist SMEs
and data publishers and consumers in
analyzing and interlinking public sec-
tor information with enterprise data.
The main approach of this framework
towards encouraging data re-use is
the conversion from RDF to a number
of other formats, included but not
limited to CSV, XLS, XML, JSON and
RDB. This conversion will allow users
to import open RDF data into the orig-
inal format of their current system.
The data can then be interlinked with
the entity’s own data, enabling the
potential identification of patterns
and maybe even predictions.
Through a user interface, users of the
framework are enabled to select what
data to access from the available open
datasets. This is possible either
through a SPARQL endpoint, or other-
wise, if the user is not familiar with
SPARQL, through a Query Builder. The
latter provides drag and drop and au-
to-complete features which allow a
user to easily build the desired query
and access the required data. The user
can then access an API server where,
through RESTful calls, the user can
pass the SPARQL query that results in
the data to be converted and the con-
version format to be used. The gener-
ated results can then be downloaded
to the user’s desktop.
Let us take German Tours as a use
case. German Tours is an SME that
provides various tours for tourists vis-
iting Germany. A number of languages
are used for the tours, including Eng-
lish, Italian and German. Alice, the
manager, thinks the tours provided by
German Tours need to be updated to
reflect current tourist trends. She is of
the opinion that they need other rele-
vant data aside from the information
that the SME already has, which in-
cludes the tour type, language used,
and number of tourist bookings.
She therefore starts looking for any
relevant information on the web. She
discovers the statistical data published
by the German NSO, which contains
information about relevant touristic
information such as most popular
tourist nationalities visiting Germany,
as well as the time of the year in which
they visited the country. This data is
ideal for her purpose, as it would ena-
ble her to compare the SMEs tour
bookings with the actual tourists who
visited Germany. Unfortunately how-
ever, the available data is in RDF while
her data is in RDB format. Alice thus
exploits the LinDA Publication and
Consumption Framework in order to
import the required data into the
SMEs system. The German NSO data
can be easily accessed through the
LinDA easy-to use and intuitive inter-
face which allows Alice to create a
SPARQL query in order to query the
desired data. Alice then proceeds to
convert the required data into RDB
format, and download it into the SMEs
system. By linking the SMEs data with
the German NSO open data, Alice re-
alises that a large number of Spanish
tourists visited Germany, however,
since German Tours has no Spanish
tours available, Alice thus manages to
discover a niche in the market that
they do not cater for. Thus, through
the LinDA Publication and Consump-
tion Framework, Alice is given the op-
portunity to enhance the SMEs ser-
vices in order to better reflect current
tourist demands.
LinDA Publication and Consumption Framework
by Judie Attard
Recent news
SDI4APPS/LinDA Cod
Joint SDI4APPS/LinDA Code
Camp
The project SDI4APPS hosted a
Code Camp from 1st to 3rd De-
cember 2014 in Brno, and the
LinDA project has been invited to
take part and show the results
achieved to the invited SMEs.
The Code Camp has been an ex-
cellent opportunity to
“Demonstrate the feasibility
and impact of the LinDA ap-
proach to the European SMEs”
which is one of the project ob-
jectives and move forward in
both its stakeholder involvement
strategy and collaboration with
the development community.
38th Conference of the Italian
Association of Epidemiology
(Naples 5-7 November 2014).
The conference focus was the
role of epidemiology in improv-
ing the planning, management
and evaluation of the prevention
programs to support the citizen’s
wellbeing. LinDA contributed
with a poster “Linked Data Ana-
lytics for the Identification of
Epidemiological Trends”, focus-
ing on the opportunity given by
the availability of data sources in
the health and environmental
sector and the production of ad-
vanced analytics to extract
meaningful conclusions regard-
ing the causes of specific diseas-
es.
http://linda-project.eu/ 2
3. Given the availability of huge amount
of information in heterogeneous pub-
lic and private data sources world-
wide, the realization of advanced
analysis over the available data is con-
sidered crucial for Small and Medium
Enterprises (SMEs) in order to proper-
ly exploit the available information
and turn it into competitive ad-
vantage.
Data analytics have the potential to
help SMEs to identify the data that is
most important to the current and
future business decisions, provide
insights based on the analysis, answer
specific business questions and facili-
tate/guide the decision making pro-
cess. The combination of publicly
available data (e.g. governmental
open data, environmental data) with
privately transformed data, main-
tained by SMEs, can help enhancing
their experience of managing and pro-
cessing of data, in ways not available
before.
It should be noted that many major
companies are already moving to-
wards the transition from business
intelligence to business analytics ap-
proaches, since they consider ana-
lytics as the scientific process of trans-
forming data into insight for making
better decisions. Towards this direc-
tion, the engagement of data scien-
tists in addition to information scien-
tists in the data analysis process is
considered a must.
Given the need for interlinking of
concepts described in different da-
tasets towards the preparation of
meaningful datasets for analysis, the
modern approach adopted is Linked
Data, a set of best practices for repre-
senting and connecting structured
information on the web. Following
these practices enables the creation of
a web of data – a large interconnect-
ed web consisting of integrated data
elements. Within the Linked Data do-
main, the LinDA (Linked Data Ana-
lytics) project is going to provide a set
of tools that will assist SMEs in effi-
ciently developing novel data analyti-
cal services that are linked to the
available public data, therefore con-
tributing to improve their competi-
tiveness and stimulating the emer-
gence of innovative business models.
The proposed approach is building
The exploitation perspective
upon the collection of data from available data sources, their transformation
in proper format (e.g. RDF format) and their interlinking for the creation of
extended linked datasets, fed as input in the analytics extraction process.
Then, the analysis part can be realised, while the output can be fed up to visu-
alisation tools.
LinDA is handling several technical challenges regarding the creation, publica-
tion and consumption of Linked Data. However, in addition to the technical
challenges, a business-oriented challenge regards the learning curve for the
adoption of the provided solutions from SMEs. The adoption process can be
quite steep, because few educational resources actually exist for users new to
the concepts, and very fewer resources can be found that discuss how to ap-
ply these technologies in real world scenarios. The approach followed within
LinDA concerns the design and development of an ecosystem consisting of
well interconnected tools, a set of consumption applications targeted to the
provision of specific functionalities to end users per domain, along with the
preparation of a set of guidelines for the use of each of the considered tools.
It could be argued that the learning curve for SME’s with a basic background
of knowledge organization, web services and analytic tools will be minimal,
given that the deployed ecosystem will hide complex details from the end-
user. Furthermore, concerning the algorithmic part of the tools and the de-
tailed knowledge of the algorithms execution process and configuration pa-
rameters, a simplified version of specific algorithms will be supported with
predefined configuration setup. Advanced configuration will be also support-
ed, however, this will possibly require the engagement of data scientists in
the process with expertise in the data analytics domain.
Summarizing, it could be claimed that the adoption of the LinDA technologies
from SMEs can provide them the potential to produce advanced knowledge,
leveraging the power of linked data analytics and, thus, acquire a significant
competitive advantage in the decision making process and increase their
overall effectiveness.
In this article, Anastasios Zafeiropoulos illustrates the benefits
that SMEs can realize by leveraging the LinDA toolset as a
development accelerator for novel analytical services linked to
available public data.
Cost-effective access to linked data for SMEs
by Anastasios Zafeiropoulos
http://linda-project.eu/ 3
