Linked Statistical Open Government Data

Orebro, 28 April 2015

Linked Statistical Open Government Data

Efthimios Tambouris University of Macedonia and ITI-CERTH, Greece

[email protected]

(Some aspects of) Open Data

Statistical Data and Linked Open Data Technologies

Linked Statistical Data Lifecycle

Tools for Linked Statistical Open Government Data

The OpenCube Project

Conclusions

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Table of Contents


More than 180 Open Government Data portals around the globe provide data that “can be freely used, reused and redistributed by anyone”

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Open Government Data (OGD)

Huge potential for transparency and economic growth

First Step: understand the big picture


1. Understanding OGD: A Classification Scheme

Kalampokis, E., Tambouris, E., Tarabanis, K.: A

Classification Scheme for Open Government Data:

Towards Linking Decentralized Data. International

Journal of Web Engineering and Technology 6(3), 266–

285 (2011)

24 official OGD initiatives were

classified based on that framework

in 2010 (this classification may now

have changed)


3. A Stage Model for OGD + OSMD

Kalampokis, Ε., Tambouris Ε. and Tarabanis Κ., Open Government Data: A Stage Model. In: M. Janssen et

al. (Eds): EGOV2011. LNCS 6846, 235-246, 2011.


2. Understanding Open Social Media Data: An Analysis Framework

E. Kalampokis, E. Tambouris and K. Tarabanis (2013) Understanding the Predictive Power of Social Media, Internet

Research, Vol.23, No.5, pp. 544-559

Based on the

review of ~60

relevant scientific

publications


Promises of OGD initiatives largely not fulfilled

Next Step: dig into data themselves

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Problem







Conclusions

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Table of Contents


Open (Gov) Data are very important for the EU

A big portion of Open Data concerns statistics e.g. 6875 out of 7682 datasets of the EU Open Data Portal are of statistical nature.

Statistical data is often organized as data cubes, where each cell contains a measure described based on a number of dimensions.

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Nature of Open Gov Data


Data Cube

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Dimensions Hierarchy

Measure


Users frequently want to blend & combine statistical data from multiple sources

But, these data usually resides in files and databases (data silos) that are hard to combine

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Focus


Linked Data has the potential to enable combining and performing analytics on top of disparate and previously isolated statistical data

The RDF Data Cube Vocabulary has been proposed for modelling multi-dimensional data as RDF graphs.

However, tools for handling linked data cubes:

are only few and scattered

have not been tested under real-life conditions

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Linked Data

Potential of using LOD in statistical data analysis unexploited







Conclusions

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Table of Contents


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The OpenCube project

OpenCube is a 2-year project funded by the EU within FP7

The project aims to develop and test processes and tools for managing statistical

linked open data.

The results will:

Facilitate data publishers to create linked data cubes from legacy formats

Empower data users to browse, visualise, link, expand and analyse data cubes.

Enable analysis not possible before (merging data cubes at a Web scale)


We propose a lifecycle for statistical LD

The lifecycle is divided into two phases: publish and reuse (or consume)

The lifecycle prescribes the steps that raw data cubes* should go through in order to create value.

OpenCube also develops tools to support the whole lifecycle of linked statistical data.


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* We assume statistical data is organized as data cubes, where each cell

contains a measure described based on a number of dimensions.







Conclusions

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Table of Contents


Publishing components TARQL extension

D2RQ /R2RML-QB extension

JSON-stat

Grafter

Consuming components OpenCube Browser

OpenCube MapView

R Analysis Chart

Linking components

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OpenCube Toolkit

Developed using Information Workbench open source as underlying linked data management platform

License scheme OpenCube components are

provided under open source licenses

Check http://opencube-toolkit.eu

But, commercial solutions are also offered by consortium members


http://opencube-toolkit.eu/



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Publishing Components


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Consume: OpenCube browser Summarize observations

across a dimension

(dimension reduction)

Change the axes

of the table

Change the

language

Change the fixed

values

It enables the exploration of an RDF data cube by presenting a two-dimensional slice of the cube as a table.

The slice is created by setting a fixed values for each dimension that is not presented in the table.


Visualization of RDF data cubes on a map.

It supports: Markers

Bubble

Choropleth maps

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Consume: OpenCube MapView


Visualisation of analysis results (charts & tables)

Reuse of analysis results: preserving R output as linked data

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Consume: Integration with R


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Consume: Other Visualizations

Analytics and Reporting Visualization and Exploration

Stock chart


Enables Performing analytics on top of combined data cubes

Steps: 1. Select a data cube

2. Discover cubes on the Web of Linked Data having compatible structure; i.e. cubes with dimensions, measures etc. that can expand the initial cube

3. Create expanded views of the initial cube

4. Consume the new cube(s)

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Linking Statistical Data


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Example: Start with an initial cube


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Example: Discover & Select compatible cubes


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Example: Browse an expanded view of the initial cube


Can be from different domain, e.g. access to medical records

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Applications

19 October 2014, Riva del Garda, Italy ISWC 2014 – SemStats 2014

Query

Data consumer Data provider

Linked Data Cubes and

Metadata

Access

Policies

Authorization Mechanism

...

...

...

User

Profiles ..

.

..

.

..

.

Access Policies

..

.

..

.

..

.

Query

Results

Data-Cubes

Metadata

User

profiles

Authorized

Results

Create Profile

Create Profile

Request

Authorized

Results

SPARQL

Query

Au

tho

riza

tion

Inte

rfac

e

Query

Results

Qu

ery

Re

su

lts

E. Kamateri, E. Kalampokis, E. Tambouris, and K. Tarabanis (2014) The Linked Medical Data Access Control Framework,

Journal of Biomedical Informatics, Vol.5, pp. 213-225






Conclusions

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Table of Contents


For more information

http://opencube-project.eu

http://opencube-toolkit.eu

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OpenCube consortium













Conclusions

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Table of Contents


Open Statistical data are rapidly increasing due to Open Data policies

Linked Data technologies can provide web-scale linking and analysis of statistical data

OpenCube project develops processes and tools for statistical data management

These can be divided into: Tools for producing linked open statistical data

Tools for linking (expanding) open statistical data

Tools for consuming linked open statistical data

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Conclusions


For more information



Project coordinators:

Konstantinos Tarabanis, [email protected]

Themis Tambouris, [email protected]

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Questions?








mailto:[email protected]

mailto:[email protected]

Government & Nonprofit

Linked Statistical Open Government Data