A Platform for Collaborative e-Science Applications

A Platform for Collaborative
e-Science Applications
Marian Bubak
ICS / Cyfronet AGH Krakow, PL
[email protected]
KUKDM 2009, Zakopane, 12-13 March 2009
Outline
•
•
•
•
•
Motivation
Idea of an “experiment”
Virtual laboratory
Examples of experiments
Summary and challenges
KUKDM 2009, Zakopane, 12-13 March 2009
System-Level Science
• An approach to scientific investigations
which, besides of analyses of individual
phenomena, integrates different,
interdisciplinary sources of knowledge
about a complex system, to acquire
understanding of the system as a whole.
• Foster, I., Kesselman, C., Scaling system-level science: Scientific
exploration and its implications. IEEE Computer 39 (11) 2006
KUKDM 2009, Zakopane, 12-13 March 2009
ViroLab Users
Experiment developer
Scientist
Experiment planning
ViroLab Gem
Development
Experiment
Planning
Clinical virologist
Experiment use
Experiment
Execution
Decision Support System use
Results
management
<<include>>
Decision
support
<<include>>
Experience
feedback
Data Source
registration
Adds data
resources inside
virtual lab
Publishes new
ViroLab Gem
Uses various
ViroLab Gems
and available
data resources
to create
experiments
<<include>>
Results
sharing
Results
storing
Helps developer
improve the
experiment
Runs prepared
experiments to
obtain results
Discuss and
analyses the
results
Stores the
results in
laboratory
data store
KUKDM 2009, Zakopane, 12-13 March 2009
DSS relies on
rules to give
information on
drug resistance
Results regarding
drug resistance
of virus mutants
may become new
rules for DSS
Experiment
• Experiment - a process that combines together
data with a set of activities that act on that data
KUKDM 2009, Zakopane, 12-13 March 2009
Experiment Lifecycle
• Experiment Pipeline - is a collaborative
planning and execution process that may create
a new experiment
KUKDM 2009, Zakopane, 12-13 March 2009
On top of any infrastructure …
Users
Interfaces
Runtime
Services
Infrastructure
Experiment
developer
Experiment
Planning
Environment
Experiment
scenario
Clinical
Virologist
Scientist
ViroLab Portal
Patient Treatment
Support
Virtual Laboratory runtime components
(Required to select resources and execute experiment scenarios)
Computational services
(services (WS, WTS, WS-RF), components
(MOCCA), jobs (EGEE, AHE))
Data services
(DAS data sources, standalone databases)
Grids, Clusters, Computers, Network
KUKDM 2009, Zakopane, 12-13 March 2009
Collaborative Applications on VLvl
KUKDM 2009, Zakopane, 12-13 March 2009
Virus Genotype Analysis
Objective: loads nucleotide sequence of an HIV virus strain
and provides its mutations and drug ranking information
• Gems used:
– Alignment
– Subtype detection
– Drug ranking
– Data Access
Service
• Input: virus
nucleotide sequence
• Output: various analyses
http://virolab.cyfronet.pl/trac/vlvl/wiki/ExperimentDemo
KUKDM 2009, Zakopane, 12-13 March 2009
Experiment Plan
patientID = 6 region = "rt“
Parameters
remoteDB = DACConnector.new( "DAS","virolab.hlrs.de")
sequences = remoteDB.executeQuery(
"select nucleotides from nt_sequence where
Genotype retrieval
patient_ii=#{patientID.to_s};")
regaDBMutationsTool = GObj.create('regadb.RegaDBMutationsTool')
regaDBMutationsTool.align(sequences, region.upcase)
mutations = regaDBMutationsTool.getResult Alignment + Mutation
detection
regaDBSubtypingTool = GObj.create('regadb.RegaDBSubtypingTool')
regaDBSubtypingTool.subtype(sequences[0])
Subtyping
puts regaDBSubtypingTool.getResult
puts drs.drs('retrogram', region, 100, mutatations)
KUKDM 2009, Zakopane, 12-13 March 2009
Drug ranking
Protein Folding
Objective: demonstrate the usage of Virtual Laboratory for
proteomics applications
• Input: protein and chain ID
• Output: 3D structure of protein
• Gems used:
– Protein Data Bank (PDB) Web Service
– Early-stage protein folding
Bryliński M, Jurkowski W, Konieczny L, Roterman I.
Limited conformational space for early-stage
protein folding simulation
Bioinformatics 20(2), 199-205 (2004)
– DAC and WebDAV for result storage
http://virolab.cyfronet.pl/trac/exampleExperiments/wiki/exex/Folding
KUKDM 2009, Zakopane, 12-13 March 2009
Data Mining with Weka
Objective: to analyze the quality of various classification algorithms on large
datasets using Weka data mining library and MOCCA component
framework.
•
Input: sample dataset
•
Output: quality of predictions
•
Gems used:
– Web services for data
retrieval, conversion,
splitting and testing
– MOCCA components
wrapping algorithms
from Weka
– WebDAV server for
data storage
http://virolab.cyfronet.pl/trac/exampleExperiments/wiki/exex/WekaAdv
KUKDM 2009, Zakopane, 12-13 March 2009
Summary
• Collaborative applications
– A new method of collaborative application
development
– Abstract layers to hide technological changes
– Semantic description of applications
– Integration of provenance recording and tracking
• Virtual laboratory
– Semantic description of resources
– Deployment on available Grid systems, clusters, and
single CEs
– Integration of WS, WSRF, components, jobs
– Secure data access and integration
KUKDM 2009, Zakopane, 12-13 March 2009
Challenges
• development of Web-based tools for managing
laboratories, running experiments, gathering results,
refining methods and achieving scientific goals within
virtual groups,
• to support collaborative aspects of research through
dedicated, specialized tools for different groups of users
(administrators, hardware providers, experiment
developers, scientists) to complete their tasks within the
overall goal of their groups,
• a collaborative space for scientific collaborative
application development, facilitating publishing and
sharing of software content.
KUKDM 2009, Zakopane, 12-13 March 2009
Dataneum
•
•
Authorization model enabling e-Scientists to expose the input data and results
of their research to the wider scientific community without violating the security
restrictions inherent in grid computing infra-structures or collaborative working
environments.
Integrated infrastructure and community web portal for:
– Authoring,
– Publishing,
– Managing,
– Sharing,
– Referencing,
– Accessing,
– Reusing,
– Annotating,
scientific data.
KUKDM 2009, Zakopane, 12-13 March 2009
15
Thanks to
– Runtime system
• Tomasz Gubala, Marek Kasztelnik, Piotr Nowakowski, Eryk Ciepiela, Asia Kocot
– Middleware
• Maciej Malawski, Tomasz Bartynski, Jan Meizner
– Presentation and collaboration tools
• Wlodzimierz Funika, Dariusz Krol, Daniel Harezlak, Alfredo Tirado
– Data Access
• Matthias Assel, Stefan Wesner, (Aenne Loehden, Bettina Krammer), Piotr
Nowakowski
– Provenance
• Bartosz Balis, Jakub Wach, Michal Pelczar
– Integration
• Tomasz Gubala, Marek Kasztelnik
• VLvl description, demos, downloads virolab.cyfronet.pl
• ViroLab Project (Peter Sloot)
www.virolab.org
KUKDM 2009, Zakopane, 12-13 March 2009