Visualization and Search Approaches for Time-Oriented Scientific Primary Data A WGL-TIB Project Jürgen Bernard Technische Universität Darmstadt Fachgebiet Graphisch-Interaktive Systeme (GRIS) Visual Analysis Group Fraunhoferstraße Darmstadt Germany Tel.: +49 (6151) 155 – 666 Fax: +49 (6151) 155 –

Outline 1.Motivation 2.Practical Approach 3.Outlook | Interactive-Graphics Systems | Visual Search and Analysis Group | Jürgen Bernard | 2

Trends Content-based search and presentation available for many document types Text documents Digital image, video, audio, etc. Repositories for new kinds of non-textural documents Like scientific primary data PANGAEA, PsychData, Dryad, ELEXIR, KoLaWiss Information overload: need for visual retrieval and data exploration 1 Motivation | Interactive-Graphics Systems | Visual Search and Analysis Group | Jürgen Bernard | 3

Time-oriented scientific primary data Massive amounts of time-oriented scientific primary data that may be valuable for future research Heterogenity of standards in different research disciplines Exploration of scientific primary data repositories currently restricted to meta- search 1 Motivation PANGAEA PanPlot Tool. ( | Interactive-Graphics Systems | Visual Search and Analysis Group | Jürgen Bernard | 4

Development of a Visual Catalog for time series data Interactive-graphic access to huge amounts of scientific primary data Combination of content-based, and meta data retrieval Explorative data analysis by searching, browsing and zooming techniques User-adaptive search methods Establish higher data transparency and deeper user comprehension 1 Motivation | Interactive-Graphics Systems | Visual Search and Analysis Group | Jürgen Bernard | 5

Possible Use Case Scenario Natural scientist detects interesting curve progression Hypothesis: curve progression indicates future event Search for similar curve progressions in related data sets Visual overview of the most similar data elements Filter result set, adapt the reference example 1 Motivation | Interactive-Graphics Systems | Visual Search and Analysis Group | Jürgen Bernard | 6

Outline 1.Motivation 2.Practical Approach 3.Outlook | Interactive-Graphics Systems | Visual Search and Analysis Group | Jürgen Bernard | 7

2.1 Overview | Interactive-Graphics Systems | Visual Search and Analysis Group | Jürgen Bernard | 8 Back End Front End Bernard, J. and Brase, J. and Fellner, D. and Koepler, O. and Kohlhammer, J. and Ruppert, T. and Schreck, T. and Sens, I. A Visual Digital Library Approach for Time-Oriented Scientic Primary Data. Accepted at the 14th European Conference on Research and Advanced Technology for Digital Libraries (ECDL), 2010

2.2 Data Import Parse primary data Initialy: use Pangaea data files In principle: inclusion of additional repositories by customized data parsers Define a generic time series data structure Feature based approach Store meta data as bag of words Special attributes: time stamp, parameter/unit Defined data base schema MySQL data base Efficient data management | Interactive-Graphics Systems | Visual Search and Analysis Group | Jürgen Bernard | 9

2.3 Preprocessing Problem: time series primary data may not be directly applicable for clustering, consider: Outliers, noise Missing values format of time stamps in data files Inhomogenous time quantization, timestamp compatibility Possible approaches Aggregation (binning) Transformation Interpolation | Interactive-Graphics Systems | Visual Search and Analysis Group | Jürgen Bernard | 10

2.4 Feature Extraction Descriptors: representations of time series in a reduced dimensionality space Basis for similarity measures (clustering, indexing, search) Problem: full sequence vs. sub sequence search Huge amount of descriptors published, suitable descriptor approaches: Binning, (current approach), Discrete Fourier Transformation (DFT), Discrete Wavelet Transformation (DWT), SAX-Descriptor (symbolic representation) | Interactive-Graphics Systems | Visual Search and Analysis Group | Jürgen Bernard | 11 Lin, J. and Keogh, E. and Lonardi, S. and Chiu, B. : A symbolic representation of time series, with implications for streaming algorithms. Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery, 2003

2.5 Visual Catalog Visualization of clustering results (global und local) Self-organizing Map as a basis for smart visualization of huge amounts of time series Provide a single grid view for details (zooming) We also explore other layout algorithms | Interactive-Graphics Systems | Visual Search and Analysis Group | Jürgen Bernard | 12

2.5 Visual Catalog Visual-interactive time series search Query by example, query by sketch Problem: fullsequence vs. subsequence search Colormaps for the indication of similarity List-based visualizations for result sets Save session, export results | Interactive-Graphics Systems | Visual Search and Analysis Group | Jürgen Bernard | 13

2.5 Visual Catalog Meta data search Additional search functionality, combination with content-based search Search by Bag of words Search by special attributes Physical unit, example: temperature, humidity, etc. Use time stamp: define time interval and quantization Combine multiple search operations: filtering | Interactive-Graphics Systems | Visual Search and Analysis Group | Jürgen Bernard | 14 Filtering

Outline | Interactive-Graphics Systems | Visual Search and Analysis Group | Jürgen Bernard | 15 1.Motivation 2.Practical Approach 3.Outlook

3 Outlook Summary WGL-TIB project: visual access to scientific primary data Project start: 01/2010, project duration: 3 years Facing time-series data Feature-based descriptor approach Interfaces for visualization, browsing and search | Interactive-Graphics Systems | Visual Search and Analysis Group | Jürgen Bernard | 16

3 Outlook Requirements, use-cases and evaluation model (TIB Hannover) Test visual catalog prototype with real world problems Collaboration with scientific users to capture user view User in the loop approach Technical future work (GRIS, FhG) Establish an application prototype Similarity search operations, based on evaluation results Special user interface | Interactive-Graphics Systems | Visual Search and Analysis Group | Jürgen Bernard | 17

Thank you for your attention Comments very welcome Do you have any questions? Acknowledgements | Interactive-Graphics Systems | Visual Search and Analysis Group | Jürgen Bernard | 18

Related Work PANGAEA Publishing Network for Geoscientic & Environmental Data. ( PsychData National Repository for Psychological Research Data. ( (in German)) Dryad Digital Repository for Data Underlying Published Works. ( ELIXIR European Life Sciences Infrastructure for Biological Information. ( KoLaWiss: Society for Scientic Data Processing Goettingen: Cooperative long-term preservation for research centers (in German).Project Report (2009) PANGAEA PanPlot Tool. ( Bernard, J. and Brase, J. and Fellner, D. and Koepler, O. and Kohlhammer, J. and Ruppert, T. and Schreck, T. and Sens, I.: A Visual Digital Library Approach for Time- Oriented Scientic Primary Data. Accepted at the 14th European Conference on Research and Advanced Technology for Digital Libraries (ECDL), 2010 Lin, J. and Keogh, E. and Lonardi, S. and Chiu, B.: A symbolic representation of time series, with implications for streaming algorithms. Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery, | Interactive-Graphics Systems | Visual Search and Analysis Group | Jürgen Bernard | 19