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Statusreport Masterthesis > Miriam Ney > 13 .01.2011
Enabling a data management system to support the
good laboratory practice
Masterthesis Status Report – Miriam Ney (13.01.2011)
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Overview
Description of Task
Approach to Complete Task
Phase 1: Requirements Analysis
Phase 2: Implementation
Phase 3: Testing and Evaluation
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Enabling a data management system to support the
good laboratory practice
Data management system: DataFinder
Open Source Project developed by DLR
Data management and workflow management
Heterogenous data store concept
Meta Data handling
Good laboratory practice (GLP)
Scientific conduct
Regulatories from DFG, OECD, Universities, …
Part of GLP: Laboratory Notebook
Description of Task:
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Requirements analysis (November, December)
What is the good laboratory practice?
How does a scientific workflow look like?
What do other implementation have?
What is part of a laboratory notebook?
Implementation
Feature 1: Origin of Data (January, February)
Feature 2: Evidentially Archiving (February)
Feature 3: Signing digitally (March)
Testing the Implementation (April)
NANO in GBK
Writing the thesis (concurrently)
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Plan:
Organizing the Master Thesis
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Requirements analysis
What is the 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).
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Requirements analysis
How does a scientific workflow look like?
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Requirements analysis
What do other implementations have?
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Requirements analysis:
What is part of a laboratory notebook?
Paper based
Immediate documentation
Protocol style
Short notes
Attesting authentication
Genuineness
Authenticity in general
Integrity
Chain of events
“Das Laborbuch ist ein Tagebuch des experimentierenden Naturwissenschaftlers”
(The laboratory notebook is the diary ofthe experimenting scientist)
(Schreiben und Publizieren in den NaturwissenschaftenVon Hans F. Ebel,Claus Bliefert,Walter Greulich; chapter 1.3 - page 16)
Electronically based
Durability
Collaboration
Versioning
Rights management
Variety of dataformats
Searchability
Device integration
Individual Sorting
Infrastructure
Environmental specialisation
Availability
Complexity
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Implementation
Feature 1: Origin of Data – Provenance IntegrationProvenance (lat. pro venire = to come from): origin of data , source
Motivation:
Requirements:
Integrity
Chain of events
Genuineness
TODO:
Provenance Model
Provenance System adjusting
„noblivious“
Integration into DataFinder
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Implementation
Feature 1: Origin of Data – Provenance Integration
Model
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Implementation
Feature 2: Evidentially Archiving
Motivation:
„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).
TODO:
Requirements analysis:
BeLab project results
Developing concept:
DataStore integration in DataFinder of WS-Secure
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Implementation
Feature 3: Signing digitally
Motivation:
Requirements:
Authenticity in general
Attesting authentication
TODO:
Developing concept:
Authentification methods
Saving methods of signatures
Integration into DataFinder
Signing of data as MetaData
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Testing the Implementation
NANO: „Gasdynamisch initiierte Partikelerzeugung“
TODO:
Adjusting DataFinder for test data (datamodel)
Testing the system with the data
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Stand #
Fragen?
Kontakt:
Miriam Ney
DLR Simulations- und
Softwaretechnik, Berlin
Email: [email protected]