NTTS 2015, Brussels, 10-12 March 2015
ICT Tools for statistical linked open data: the OpenCube toolkit
E. Tambouris, E. Kalampokis, K. Tarabanis
University of Macedonia and ITI-CERTH, Greece {tambouris, ekal, kat}@uom.gr
Open Statistical Data are very important for the EU
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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Problem definition
Linked Data (LD) technology has the potential to enable combining and performing analytics on top of disparate and previously isolated statistical data
However, relevant tools are few, scattered and un-tested under real-life conditions
Potential of using LD in statistical data analysis unexploited
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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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Linked Statistical Data Lifecycle
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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.
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
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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
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Publishing Components
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Consume: OpenCube browser
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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
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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
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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
Practical use of the tools is possible in the NTTS 2015 satellite workshop session 21B on Linked Statistics (today 18:00-20:00)
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Conclusions
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For more information
http://opencube-project.eu
http://opencube-toolkit.eu
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Questions?
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OpenCube consortium