Collaborative Science: Technologies & Examples - Cameron Kiddle, Grid Research Centre

Collaborative Science: Technologies & Examples

Cameron Kiddle Research Fellow, Grid Research Centre (GRC)

University of Calgary

Outline   Technologies

  Web 2.0/Social Networking   Motivation   Examples

  Academia.edu, Sciweavers, myExperiment, HUBzero

  Examples GRC is working on   GeoChronos, CyberSKA, WaterCloud

Cybera Summit Sep. 22, 2010

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Web 2.0 – “The Social Web”   Aimed at:

  Providing feature rich user environments   Making it easier for users to generate Web content   Improving online social connectivity

  Web 2.0 technologies   Blogs/Microblogs (WordPress, TypePad, Twitter)   Wikis (Wikipedia)   Mashups (HousingMaps, ChicagoCrime)   Widgets/Gadgets (iGoogle, Netvibes)   Social networks (Facebook, MySpace)

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Social Networking   Personal

  Business

  Academic

  White label


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Social Networking Motivation   Can enhance collaboration capabilities

around data and applications – “Facebook for Scientists”

  Facebook Widely adopted   People: > 500 million users (50% log on to Facebook

on any given day), average user has 130 friends   Data: > 30 billion pieces of content shared each

month   Applications: > 550 thousand applications on

Facebook Platform


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Academia.edu   Search for others

based on research interests, institution, department, position

  Follow work of others (via news feed)

  Share your own publications, presentations, research interests


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Sciweavers (www.sciweavers.org)

  Bookmarking network   Aimed at promoting

research work and researcher visibility

  Share links to presentations, notes, source code, datasets, etc.


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myExperiment (www.myexperiment.org)

  Developed at Universities of Southampton, Manchester and Oxford

  Share scientific workflows and other research objects

  Contacts, groups, tagging, rating, reviews, comments


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HUBzero (hubzero.org)   A collaborative platform for

scientists developed at Purdue University

  Recently released as open source (spring 2010)

  Share publications, presentations, courses, seminars

  Groups, wikis, blogs, ratings, citations, tagging, …

  On-line, interactive access to tools/applications

  Supports over 20 hubs   nanoHUB.org,

pharmaHUB.org, thermalHUB.org, …


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GeoChronos (geochronos.org)

  CANARIE NEP-I Project

  Partners   CANARIE, UofA,

Cybera, UofC (GRC)   On-line collaborative

portal for Earth observation scientists

  Aimed at enabling sharing of scientific data and applications


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GeoChronos - Collaboration   Social networking portal

  Elgg-based (elgg.org)

  Social networking services   Blogs   Tags   Media/document sharing   Wikis   Friends/contacts   Groups   Discussions   Message boards   Calendars   Status   Activity Feeds


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GeoChronos – Interactive Application Service   On-line, on-demand

access to scientific applications

  Share application sessions and data with other users

  Access control to applications

  Hosted on top of a cloud computing platform that can dynamically provision resources on-demand


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GeoChronos – Spectral Libraries   Store, share and

browse spectral data   Manage metadata for

spectra   Create and share

metadata schemas   View spectral plots,

metadata, ancillary files and maps


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GeoChronos – MODIS Workflows   Creation/execution/monitoring of

workflows (mosaic, reprojection and subsetting of MODIS satellite data)

  Upload or selection of shapefile/region of interest

  Selection of data products   Extraction of quality control

information   Thumbnail generation for output

files for viewing/verification of data

  Browsing of MODIS and workflow output data/metadata from workflows via same data management system developed for Spectral Library


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GeoChronos – Next Steps   Development/integration of additional

collaboration tools/plugins   Generalization of data management system

to support other data types (other satellite data, flux and phenology tower data, meteorological data, ...)

  Distributed data management   Employ Semantic Web technologies to

better link/relate data and enable ontological mapping of metadata from different schemas


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CyberSKA (www.cyberska.org)   CANARIE NEP-II Project   Partners

  CANARIE, Cornell, Cybera, IBM Canada, McGill, NRC, UBC, UBCO, UofC (Physics/GRC)

  On-line collaborative portal for radio astronomers

  Aimed at addressing evolving science needs of future radio telescopes such as the Square Kilometer Array (SKA) will be largest radio-telescope when completed


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CyberSKA - Collaboration   Social networking portal

  Elgg-based (elgg.org)   Initially adapted from

GeoChronos with significant development/customization since



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CyberSKA - Visualization   Recognition of FITS

Mime Type   In-line display of FITS

headers   On-line visualization of

FITS files   Interactive panning and

zooming   Histogram correction   Color map adjustment   Display data values for

each pixel


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CyberSKA – Data Access   Access/download

multi-dimensional FITS data

  Select region of interest, stokes parameters, channel range and width

  Requested data generated on virtualized Condor Pool


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CyberSKA – Next Steps   Development/integration of additional

collaboration tools/plugins   Develop distributed data management system

  Have an initial iRODS-based prototype   Establish cloud environments at each site   Develop Facebook-like third party application API   Establish a framework for users to integrate data

processing and analysis tools/algorithms they have developed

  Improve scalability of on-line visualization tool Cybera Summit Sep. 22, 2010

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WaterCloud   Cybera Pilot Project   Partners

  Alberta Advanced Education and Technology, Alberta WaterSMART, Cybera, Tesera Systems Inc, UofC (GRC)

  Aimed at exploring use of cloud services to store, manipulate and expose data related to water management


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WaterCloud - Collaboration   Social networking portal

  Elgg-based (elgg.org)



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WaterCloud – Visualization Tool   Map for displaying

and selecting monitoring stations to analyse data for

  Manage monitoring stations and collections

  Select and plot data


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WaterCloud – Collection Management   Save a set of monitoring

stations and affiliated descriptions, date ranges and data types as a collection

  Share collections with other contacts, groups, or make public

  Load previous saved/shared collections for instant data analysis


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WaterCloud – Next Steps   Employment of Semantic Web

technologies to better link data of different types and better automate analysis of data

  Explore different ways for visualizing and integrating data in a meaningful way

  Explore value added services for processing and analysing data


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Contact Information Cameron Kiddle [email protected] http://pages.cspc.ucalgary.ca/~kiddlec/

http://geochronos.org/ [email protected]

http://grid.ucalgary.ca/

CyberSKA http://www.cyberska.org/ [email protected]