The document discusses best practices for data standardization and curation, presented by Osthus at BioIT World 2015. It outlines the importance of scientific data management, the complexities and challenges faced in data curation, and proposes a reference architecture for effective data migration and integration. Key benefits of the proposed framework include modular setup, ease of use, and a focus on data rather than technology.

1. Best practice reference architecture for
data standardization and curation
Dr. Michael Engels, OSTHUS
BioIT World, Boston – April 21st 2015

2. Slide 2
Agenda
OSTHUS – Who we are
Painpoints
Reference architecture
Use cases
Benefits

3. Slide 3
Who we are

4. Slide 4
Cutting edge in R&D
Global partner
Independent
Digital Lab Informatics
Innovation
Active network
Open collaboration
Customer orientation
Trust
Who we are

5. Slide 5
Who we are
Focus on value Concepts and
methodology
Approach &
committment

6. Slide 6
Agenda
OSTHUS – Who we are
Painpoints
Reference architecture
Use cases
Benefits

7. Slide 7
Life science data
Scientific data are
 Valuable assets to NGO, academic and industries
 Domain/context specific
 Only interpreted by experts
Scientific data are subject of continuous change:
 Growth
 Formats, standards, and technology
 Concept extensions
 Context changes

8. Slide 8
Change of concepts
Phenomenological based concept Gene-based concept
Pharmacology example: Ion channels taxonomy

9. Slide 9
Painpoints
Data standardization, data curation, master data management,
data migration, ….
 Are complex endeavor's
 Are labor, and alignment-intensive
 Need expert input (technical and scientific)
 Are highly iterative
 Are difficult to frame in time-lines or costs
How to address this challenge?

10. Slide 10
Agenda
OSTHUS – Who we are
Painpoints
Reference architecture
Use cases
Benefits

11. Slide 11
Reference architecture
Data migration
Manage
Curation runs
Manage
Results
Analysis
I
II
III
IV
…...
Manage
Dictionary
Data
Source
Sources
Copy
Copy of targetWorking area
Transformation Glossary and VocabularyProperty Mapping
Extraction &
Loading
Data Concept
Target
Data
SourceGlossary
Vocabulary
Annotation
Rules
Mapping
Rules
Transformation
Rules
Run
Configuration
Data
partitioning
Data
Processing
Filtering
Monitoring &
Audit
Logs & Observ.
Exceptions
Comments
Dashboard
Calculate
Properties
Data
Comparison
Visual
Analytics
Tag
Data
List
Management
CDC
SQL to Load
Audit Trails

12. Slide 12
Agenda
OSTHUS – Who we are
Painpoints
Reference architecture
Use cases
Benefits

13. Slide 13
Use case 1
Chemical cartridge/structure migration
Accord Mol2000
#1: racemic
#1
Big Bang

14. Slide 14
Use case 2
Data integration – DWH
Continuous Growth

15. Slide 15
Agenda
OSTHUS – Who we are
Painpoints
Reference architecture
Use cases
Benefits

16. Slide 16
Benefits
Benefits are
 Modular set up
 All functions available within one integrated framework
 Separate components for technical and scientific experts alike
 Data curation – part of a process not of individual data editing
 Easy-to-use
 Configurable toolbox tailored to any program
 Integrated visual / comparative analysis between source and target data
 Reduction of technical issues
 Error propagation contained, roll backs possible
 Focus on data, not on technology

17. Slide 17
Questions?
For more information:
Visit us at Booth # 451
or at Poster # 47