openBIS – an open resource for academic laboratories

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| | Scientific IT Services Caterina Barillari Scientific IT Services, ETH Zurich 2018-09-13 Caterina Barillari openBIS – an open resource for academic laboratories 1

Transcript of openBIS – an open resource for academic laboratories

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Caterina BarillariScientific IT Services, ETH Zurich

2018-09-13Caterina Barillari

openBIS – an open resource for academic laboratories

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Research workflow in experimental & computational labs

Sample preparation

Analysis Publication

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Measurement

Processing

Data collection

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What does it take to manage research data?

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Complex process that requires tracking and linking different types of information

Materials/samples

Protocols/ SOPs

Raw data

Processed data

Results

Code

Analysis notebooks

Model

TitleDate

MaterialsMethodsAnalysisResults

Experimental description/notes

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Results Analysis notebooks

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A very common scenario @ ETH

Experimental description/notes

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Materials/samples Code

Raw dataProcessed data

Protocols/ SOPs

Model

Local HD NAS CDS LTS

Cluster Cloud

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The ideal scenario

Central storage

TitleDate

Materials…..

A combined ELN/LIMS can provide such solution

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The ideal scenario

A combined ELN/LIMS can provide such solution

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Central storage

TitleDate

Materials…..

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openBIS facts

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Summer 2007• openBIS

development start (SystemsX)

April 2008• first openBIS

release (v08.04)

Summer 2009• SystemsX

projects start using openBIS

Summer 2013• openBIS ELN-

LIMS UI start

Spring 2014• first ELN-LIMS

beta version

May 2015• first

downloadable ELN-LIMS plugin

May 2016• first ELN-

LIMS official release

May 2017• BigDataLink

v.1

December 2017• JupyterHub

integration

Platform for managing scientific information and supporting research data workflows from “bench” to publication

Can be used in most quantitative science fields (e.g. life sciences, physics, env. sciences, etc)

Used by research groups and facilities @ ETH, Swiss & European Universities, a few companies

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openBIS in a nutshell

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openBIS is a solution for research labs

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openBIS in a nutshell

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openBIS is a solution for research labs

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openBIS in a nutshell

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openBIS is a solution for research labs

TitleDate

MaterialsMethodsAnalysisResults

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ProjectsExperiments

Experimental steps

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openBIS in a nutshell

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openBIS is a solution for research labs

TitleDate

MaterialsMethodsAnalysisResults

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openBIS in a nutshell

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Workflow manager (e.g. Snakemake)

openBIS is a solution for research labs

TitleDate

MaterialsMethodsAnalysisResults

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Jupyter notebooks

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Application that combine documentation, code, input and output generated by the code, e.g. graphs, plots (Nature 515, 151–152)

Useful for exploratory data analysis and reproducibility >40 programming languages supported (Python, R, Scala, Julia, etc) Notebooks can be shared

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openBIS in a nutshell

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openBIS is a solution for research labs

Workflow manager (e.g. Snakemake)

TitleDate

MaterialsMethodsAnalysisResults

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openBIS solutionsopenBIS ELN-LIMS is available in two flavors:

For life sciences: customizable predefined types and fields suitable for most biological labs

Generic: only basic generic types predefined. To be fully customized by users.

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openBIS ELN-LIMS features

Relationships Import/Export

openBIS features

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Ordering

https://labnotebook.ch

User rights management

x

User rights management

Long term storage (tapes)

Audit trail

Data preservation

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Samples' storage manager

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openBIS ELN-LIMS features

Plasmid mapsBLAST search

openBIS features for life sciences

2018-09-13Caterina Barillarihttps://labnotebook.ch

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Best practices for openBIS introduction as ELN/LIMS in a biology lab

Create inventory of materials and samples

• Establish relationship between samples

Create inventory of standard lab protocols

• Link protocols to samples

Describe experiments

• Links to samples• Links to

protocols/copy protocols

• Upload data

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openRDM.swiss - National ARDM Service

Cloud-hosted openBIS ELN-LIMS• Virtual servers per research group, institute or institution• Generic or life-science ‘flavor’• Optionally with JupyterHub server for analytics• Automated deployment (Ansible)• Integration with Community Service Hub

Training & user support (‘best effort’)

Service Marketing & Business Model• Infrastructure & service charges for sustainable long-

term operation

Connection with repositories• Covering the entire data life cycle

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Acknowledgements

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Scientific Software and Data Management

• Matthew Baker (Group Head)• Franz-Josef Elmer• Juan Fuentes• Antti Luomi• Yves Noirjean• Althea Parker• Mikolaj Rybinski• Uwe Schmitt• Swen Vermeul• Cezary Czernecki

Research Informatics

• Thomas Wüst (Group Head)• Caterina Barillari• Vincenzo Capece• Tarun Chadha• Diana Coman Schmid• Henry Lütcke• Michal Okoniewski• Jarunan Panyasantisuk• Emanuel Schmid• Cristian Scurtescu

High-Performance Computing

• Olivier Byrde (Group Head)

• Steven Armstrong• Christian Bolliger• Urban Borstnik• Samuel Fux• Bruno Löpfe• Eric Müller• Allen Neeser• Christiane Pousa Ribeiro

Alex Upton (Community Project Manager)

Bernd Rinn (Section Head)The SIS team

[email protected]