EuroPython 2012 ( , Florence, Italy) Andreas Schreiber German Aerospace Center (DLR)
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1 Chart 1 > EuroPython 2012 > A. Schreiber > A Laboratory Notebook System > July 5, 2012 A Laboratory Notebook System EuroPython 2012 ( , Florence, Italy) Andreas Schreiber <Andreas.Schreiber@dlr.de> German Aerospace Center (DLR)
2 Chart 2 > EuroPython 2012 > A. Schreiber > A Laboratory Notebook System > July 5, 2012 Overview - Background - Good Laboratory Practice - Scientific Workflows - Laboratory Notebooks - DataFinder - DataFinder-based Laboratory Notebook - Data model - Process documentation - Evidential preservation - Signing data - Future Work
3 Chart 3 > EuroPython 2012 > A. Schreiber > A Laboratory Notebook System > July 5, 2012 Background
4 Chart 4 > EuroPython 2012 > A. Schreiber > A Laboratory Notebook System > July 5, 2012 Background Good Laboratory Practice The principles of Good Laboratory Practice (GLP) have been developed to promote the quality and validity of test data used for determining the safety of chemicals and chemicals products. OECD Principles on Good Laboratory Practice (as revised in 1997) [The recommendations] are designed to provide a framework for the deliberations and measures which each institution will have to conduct for itself according to its constitution and its mission Deutsche Forschungsgemeinschaft: Sicherung guter wissenschaftlicher Praxis (Safeguarding good scientific practice) 1998 (p.50).
5 Chart 5 > EuroPython 2012 > A. Schreiber > A Laboratory Notebook System > July 5, 2012 Background Scientific Workflow Picture adapted from:
6 Chart 6 > EuroPython 2012 > A. Schreiber > A Laboratory Notebook System > July 5, 2012 Background Laboratoy Notebooks The laboratory notebook is the diary of the experimenting scientist (Schreiben und Publizieren in den Naturwissenschaften Von Hans F. Ebel,Claus Bliefert,Walter Greulich; chapter page 16)
7 Chart 7 > EuroPython 2012 > A. Schreiber > A Laboratory Notebook System > July 5, 2012 Background DataFinder - Data management system: DataFinder - Developed by DLR - Open Source Project (BSD License) - Implemented in Python - Data management and work flow management - Supports meta data handling
8 Chart 8 > EuroPython 2012 > A. Schreiber > A Laboratory Notebook System > July 5, 2012 DataFinder User Interface
9 Chart 9 > EuroPython 2012 > A. Schreiber > A Laboratory Notebook System > July 5, 2012 DataFinder Connected to Repository
10 Chart 10 > EuroPython 2012 > A. Schreiber > A Laboratory Notebook System > July 5, 2012 DataFinder Structuring Data - Structuring of data in a standardized way through a data model - Restricting the user to a layout - Forcing the user to enter meta data
11 Chart 11 > EuroPython 2012 > A. Schreiber > A Laboratory Notebook System > July 5, 2012 DataFinder Heterogeneous Storage Resources - Using heterogeneous storage backend for data - Best fitting storage solution depending on data - Existing solutions can be kept - Using offline storage is possible
12 Chart 12 > EuroPython 2012 > A. Schreiber > A Laboratory Notebook System > July 5, 2012 DataFinder Script Extensions - DataFinder is extendable by Python scripts - Integration with existing environment - Automation of data processing steps
13 Chart 13 > EuroPython 2012 > A. Schreiber > A Laboratory Notebook System > July 5, 2012 DataFinder-based Laboratory Notebook
14 Chart 14 > EuroPython 2012 > A. Schreiber > A Laboratory Notebook System > July 5, 2012 Laboratory Notebook Requirements for Good Scientific Documentation Requirements: - Data structure - Traceability - Durability - Credibility Realization: - Data model - Process documentation - Evidential preservation - Signing data
15 Chart 15 > EuroPython 2012 > A. Schreiber > A Laboratory Notebook System > July 5, 2012 Realization Data Model
16 Chart 16 > EuroPython 2012 > A. Schreiber > A Laboratory Notebook System > July 5, 2012 Realization Process Documentation - Process documentation: Recording the Provenance of that process - Provenance (lat. provenire = to come from): origin of data, source - Provenance of process gives traceability and credibility - Steps to add Provenance recording to software (i.e., DataFinder) 1. Developing a provenance model for the Good Laboratory Practice 2. Provide Provenance storing system 3. Integration into DataFinder
17 Chart 17 > EuroPython 2012 > A. Schreiber > A Laboratory Notebook System > July 5, 2012 Process Documentation Provenance Data Model - Apply methodology to define a Provenance model - Representation of the real world s process
18 Chart 18 > EuroPython 2012 > A. Schreiber > A Laboratory Notebook System > July 5, 2012 Process Documentation Provenance Data Model
19 Chart 19 > EuroPython 2012 > A. Schreiber > A Laboratory Notebook System > July 5, 2012 Process Documentation Provenance Storing System Provenance Store proost - Java Implementation - Server: Jetty - Graph Database: Neo4j Store Provenance Processes Gremlin Request of Database - Interfaces - Storing Provenance (REST) - Extracting Provenance (REST) - Extracting Provenance (Servlet) - Open Source (Apache License 2.0) - REST Web Service Provenance-Datenbank (Neo4j) Jetty Server
20 Chart 20 > EuroPython 2012 > A. Schreiber > A Laboratory Notebook System > July 5, 2012 Process Documentation Integration Into DataFinder - User actions on files are recorded in the provenance store - Dialog for asking additional questions
21 Chart 21 > EuroPython 2012 > A. Schreiber > A Laboratory Notebook System > July 5, 2012 Realization Evidential Preservation Recommendation 7: Primary data as the basis for publications shall be securely stored for ten years in a durable form in the institution of their origin. Deutsche Forschungsgemeinschaft: Sicherung guter wissenschaftlicher Praxis (Safeguarding good scientific practice) 1998 (p.55). - Steps to add evidential preservation to software (i.e., DataFinder) 1. Create an archive with all relevant data (e.g., for a publication) 2. Integration of a preservation service
22 Chart 22 > EuroPython 2012 > A. Schreiber > A Laboratory Notebook System > July 5, 2012 Evidential Preservation Create an Archive With All Relevant Data Extraction of data relevant for the preservation process
23 Chart 23 > EuroPython 2012 > A. Schreiber > A Laboratory Notebook System > July 5, 2012 Evidential Preservation Create an Archive With All Relevant Data In DataFinder - User chooses report (publication etc.) - Python script queries relevant files from the Provenance store - Relevant files are added to an archive - Archive is stored in DataFinder
24 Chart 24 > EuroPython 2012 > A. Schreiber > A Laboratory Notebook System > July 5, 2012 Evidential Preservation Integration of a Preservation Service We use the BeLab service (Beweissicheres Laborbuch Project) - DFG Project ( - Physikalisch Technische Bundesanstalt Braunschweig - Karlsruher Institute of Technology - Universität Kassel - The BeLab service - characterizes the preservation time of an item - characterizes the legal trustworthiness of an item - stores the archive securely
25 Chart 25 > EuroPython 2012 > A. Schreiber > A Laboratory Notebook System > July 5, 2012 Evidential Preservation Integration of a Preservation Service In DataFinder - User chooses an archive and activates script - Script sends the archive to BeLab service via WS-Secure - The service processes the archive - Service returns preservation information, which is stored
26 Chart 26 > EuroPython 2012 > A. Schreiber > A Laboratory Notebook System > July 5, 2012 Realization Signing Data - Authenticity in general - Attesting authentication - Steps to add data signing to software (i.e., DataFinder) 1. Concept: - Signing files: signature stored as meta meta item - Meta data: Extraction as XML file, then signed 2. Integration into DataFinder
27 Chart 27 > EuroPython 2012 > A. Schreiber > A Laboratory Notebook System > July 5, 2012 Signing Data Integration Into DataFinder Signature of the data (files) as separate file - User chooses a file and executes script - A signature file is generated (PKCS #7) - Signature file is stored in the DataFinder
28 Chart 28 > EuroPython 2012 > A. Schreiber > A Laboratory Notebook System > July 5, 2012 Future Work
29 Chart 29 > EuroPython 2012 > A. Schreiber > A Laboratory Notebook System > July 5, 2012 Future Work Enhanced User Interface - User interface for taking notes - Annotation of data - Doing calculations and data analysis (similar to MATLAB or Mathematica Notebooks) - Integration of The Larch Environment - Integration of NumPy/IPython - Exploring Provenance data - Insights and understanding of processes - Tablet version - Entering data - Synchronization for offline use
30 > EuroPython 2012 Chart > A. 30 Schreiber > A Laboratory Notebook System > July 5, Questions? 2012 Summary - DataFinder-based Electronic Lab Notebook - Traceability, Durability, and Credibility for data - Documentation, evidential preservation, and data signing Andreas Schreiber Andreas.Schreiber@dlr.de
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