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Visual Trend Analysis with Digital Libraries
Authors:
Kawa Nazemi,Reimond Retz, Dirk Burkhardt, Arjan Kuijper, Jörn
Kohlhammer & Dieter W. Fellner
Contact:
Dr.-Ing. Kawa Nazemi
Fraunhofer IGD
Fraunhoferstr. 5
64283 Darmstadt
Tel.: +49 6151 155 551
Fax: +49 6151 155 139
Email: kawa.nazemi@igd.fraunhofer.de
© Fraunhofer IGD | Kawa Nazemi | 2015
Presentation at:
Motivation
Increasing development of new technologies, methods, products,
materials etc.
Exploitation of those in various further business areas:
Example: Visual Analytics in
Security
Medicine and healthcare
Policy Modeling
Business Intelligence
Early awareness of technological trends are essential for market
analysis and competitiveness
© Fraunhofer IGD | Kawa Nazemi | 2015
Motivation: Stages of technological awareness
© Fraunhofer IGD | Kawa Nazemi | 2015
R&D B2B
& patents B2C
Distributed Data in various DL resources
Data repositories (e.g., DBLP) with no sufficient information for trend
analysis:
When have technologies or topics emerged and when established?
Where are the key-players and key-locations?
Who are the key-players?
Which technologies or topics are relevant?
How will the technologies probably evolve in the next years?
Motivation: Open Data in Digital Libraries
© Fraunhofer IGD | Kawa Nazemi | 2015
Research Goals
Approach for:
Integrating information from heterogeneous resources
Mining information from the enriched data
Visualizing information for trend analysis
Targeted Solution
a model for gathering trends from heterogeneous digital library source for
interactive visual analysis
the combination of visual layouts with data mining approaches for analyzing
trends
a model for assisted search that enables to explore an unknown domain
© Fraunhofer IGD | Kawa Nazemi | 2015
Research Goals: Main Outcome
A coherent model for the entire transformation of textual and
semi-annotated data from various data sources to aspect-
oriented visualizations for supporting the trend analysis
process.
© Fraunhofer IGD | Kawa Nazemi | 2015
Approach: Visual Data Transformation
© Fraunhofer IGD | Kawa Nazemi | 2015
Approach: Data Enrichment (I)
© Fraunhofer IGD | Kawa Nazemi | 2015
Data Integration:
Data enrichment through external data sources
• IEEE
ACM
ComputerOrg
Springer
Approach: Data Enrichment (II)
© Fraunhofer IGD | Kawa Nazemi | 2015
Data Mining:
Data enrichment through information by
probabilistic models
Approach: Data Enrichment: Example DBLP
© Fraunhofer IGD | Kawa Nazemi | 2015
Approach: Data Transformation (II)
© Fraunhofer IGD | Kawa Nazemi | 2015
Data Transformation:
Aspect-oriented data models for
visualization
Semantic model
Temporal model
Geographical model
Topic model
Approach: Visual Mapping
© Fraunhofer IGD | Kawa Nazemi | 2015
Data Transformation:
Aspect-oriented data visualization for
each data model
Semantic visualization
Temporal visualization
Geographical visualization
Topic visualization
Visual Mapping: temporal overview visualization
© Fraunhofer IGD | Kawa Nazemi | 2015
Visual Mapping: Aspect-oriented visualizations
© Fraunhofer IGD | Kawa Nazemi | 2015
Approach: Visual Orchestration
© Fraunhofer IGD | Kawa Nazemi | 2015
Visual Orchestration:
Coherent interplay of visualizations and interaction
techniques
Static UI elements
Dynamic (responsive) UI elements
Visual facets
Textual facets
Approach: Assisted Search Model
© Fraunhofer IGD | Kawa Nazemi | 2015
Enabling the process of exploration through assisted search:
Appliance to SemaVis
© Fraunhofer IGD | Kawa Nazemi | 2015
http://media.semavis.net/dblp/
Conclusion
We proposed a coherent model for visual trend analysis:
Data Enrichment by data integration from different sources
Data mining for information extraction
Data modeling for a variety of different views on the data
Visual mapping to support the different enabled data perspectives
Visual orchestration to combine dynamic and static visual
representations and different interaction techniques
Assisted search to support the exploration process
The model was applied in SemaVis, a semantics visualization
technology
© Fraunhofer IGD | Kawa Nazemi | 2015
Acknowledgments
This work is part of the SemaVis Technology developed by
Fraunhofer IGD:
www.semavis.net
This work was partially funded by the European Commission:
© Fraunhofer IGD | Kawa Nazemi | 2015
Thank you for your attention!
Please find a video of the system on:
http://media.semavis.net/dblp/
© Fraunhofer IGD | Kawa Nazemi | 2015

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