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"Impacto de la Informática en el Conocimiento de la Biodiversidad: Actualidad y Futuro” at Universidad Nacional de Colombia on August 12, 2011. https://sites.google.com/site/simposioinformaticaicn/home
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P. Bryan HeidornUniversity of Arizona and JRS Biodiversity Foundation
8 August 2011Impacto de la informática en el conocimiento de la
biodiversidad: actualidad y futuroUniversidad Nacional de Colombia and Instituto de Ciencias Naturales, Bogotá
Biodiversity Informatics: An Interdisciplinary Challenge
Adapted in part from 2010 KENYA’S INTERNATIONAL CONFERENCE ON BIODIVERSITY, LAND USE AND CLIMATE CHANGENAIROBI 15th to 17th September 2010
University of Arizona
Biodiversity Informatics
The development and use of information technology-based sociotechnical systems to document, understand and protect biological diversity particularly at the organismal level.
Main Themes
• Cyberinfrastructure enabled science• Greater reuse of data• Mobilization of analog data• Data integration• Distributed collaborative research• Citizen science• High volume and high computation
Cyberinfrastructure Vision
“The anticipated growth in both the production and repurposing of digital data raises complex issues not only of scale and heterogeneity, but also of stewardship, curation and long-term access.”
NSF Cyberinfrastructure Vision for 21st Century Discovery, Chapter 3
Recognition of need for data curation
“Recommendation 6: The NSF, working in partnership with collection managers and the community at large, should act to develop and mature the career path for data scientists and to ensure that the research enterprise includes a sufficient number of high-quality data scientists.”
Long-Lived Digital Data Collections: Enabling Research and Education in the 21st Century, Recommendations
• Recognition of the importance of Information
• Recognition of the need for education
• New work roles within traditional institutions
Interagency Working Group on Digital Data
Dark data is the data that we know is/was there but we can’t see it.
Hubble Space Telescope composite image "ring" of dark matter in the galaxy cluster Cl 0024+17
Does NSF’s Data Follow the Power Law?
I do not know but if $1 = X bytes…..
Awarded Amount 2007
$0
$1,000,000
$2,000,000
$3,000,000
$4,000,000
$5,000,000
$6,000,000
$7,000,000
1 586 1171 1756 2341 2926 3511 4096 4681 5266 5851 6436 7021 7606 8191 8776
Heidorn, P. Bryan (2008). Shedding Light on the Dark Data in the Long Tail of Science. Library Trends 57(2) Fall 2008 . Institutional Repositories: Institutional Repositories: Current State and Future. Edited by Sarah Sheeves and Melissa Cragin. (http://hdl.handle.net/2142/9127).
The Future is all about Data
• How do we get it?• How do we analyze it?• How do we disseminate it (Maps, charts
tables..)?• How do we keep it?
– Provenance, Storage, Weeding • How do we make it sustainable?
Data Repurposing
From: To stand the test of time: Long-term stewardship of of digital data sets in science and engineering. Sept 26-27, 2006 Arlington VA
Where is your data now?
Is it doing good or is it sleeping or dead?
Cyberinfrastructure Needs
• Storage• Access• Processing• Communication• Training• Institutions
The iPlant Collaborative
Cyberinfrastructure to Support the Challenges of Modern Biology
Society for Experimental Biology, Glasgow, UK
July 3rd, 2011
Dan Stanzione
Co-PI and Cyberinfrastructure Lead, iPlant Collaborative
Deputy Director, Texas Advanced Computing Center
What is iPlant?
• iPlant’s mission is to build the CI to support plant biology’s Grand Challenge solutions
• Grand Challenges were not defined in advance, but identified through engagement with the community
• A virtual organization with Grand Challenge teams relying on national cyberinfrastructure
• Long term focus on sustainable food supply, climate change, biofuels, ecological stability, etc
• Hundreds of participants globally… Working group members at >50 US institutions, USDA, DOE, etc.
Brief History• Funding by NSF – February 1st, 2008
• iPlant Kickoff Conference at CSHL – April 2008o ~200 participants
Grand Challenge Workshops – Sept-Dec 2008 CI workshop – Jan 2009 Grand Challenge White Paper Review – March 2009 Project Recommendations – March 2009 Project Kickoffs – May 2009 & August 2009 Start of software development; September 2009 First prototypes to public: April 2010 First release with user-driven tool integration: July 2011
iPlant’s Central Challenge
• To define what it means to build a lasting, community driven Cyberinfrastructure for the Grand Challenges of Plant Science, to get community buy-in of this vision, and to execute this vision.
Steve Goff, PIU of Arizona
Dan Stanzione, coPITexas Advanced Computing Center
National Science BoardUpdate on Award Progress: DBI -0735191
Directorate for Biological SciencesJuly 2011
What iPlant Offers
Grand Challenges in Plant Science• Genotype-to-Phenotype
– To understand how DNA blueprints produce a plant’s characteristic traits and functions and to predict how traits change in response to complex environments
– Requires ability to collect, query, interpret, and model high-throughput, genome-scale data sets
• Tree of Life– To understand evolutionary
relationships among green plants– Requires ability to create, display, and query
information in very large phylogenetic trees
iPlant Progress
• Science Planning (Year 1)– Community engagement– Grand Challenge selection
• Cyberinfrastructure Design (Year 2)– Requirements generation– Technology evaluations– Prototyping
iPlant Progress
• Release of CI deliverables (Year 3)– iPlant Discovery Environments and Tools
• iPlant Genotype to Phenotype Tools– Processing and integration of high throughput data– Modeling and visualization of phenotypic expression
• iPlant Tree of Life Tools– Assembly, Reconciliation and Viewing– Taxonomic Name Resolution Service– My-Plant social networking site
• DNA Subway Tool for genome annotation / analysis
Taxonomic Name Resolution Service
Biodiversity: Development of new knowledge and tools to use knowledge
• Progress on digitization of the world’s billion+ museum specimens
• Distribution of digitized products through global networks (e.g. the Global Biodiversity Information Facility).
• Digitization of hundreds of millions of pages of natural history text (begun with the Biodiversity Heritage Library)
• Large online stores of information on species such as the Encyclopedia of Life
The Biodiversity Heritage Library has 34 million pages now
Palaeontology, or, A systematic summary of extinct animals and their geological relations / by Richard Owen. Publication info:Edinburgh :A. and C. Black,1860.
Long Citation Half-lifeCritical use for TaxonomyEcology and Environmental HistoryNaming for genomics and metagenomics
The Rubiaceae of Colombia, by Paul C. Standley. Chicago,1930.Chicago :Field Museum of Natural History,
Mobilizing Data Locked on Paper
• Fine-Grained Semantic Markup of Descriptive Data for Knowledge Applications in Biodiversity Domains Hong Cui [email protected] (Principal Investigator)
• The University of Arizona is awarded a grant to develop and evaluate a set of algorithms/software to help computers to read and “understand” taxonomic descriptions of plants, animals, and other living or fossil organisms. The major functions of the algorithms/software include 1) annotate large sets of text descriptions in a machine-readable way to support various knowledge applications, including producing character matrices and identification keys for various taxon groups.
Semantic Markup System
Trai
ning
Thu
rsda
y fo
r stu
dent
s
The Problem
• It is difficult to find what is already known• Clone specimens may be stored in different
museums around the world• DNA analysis may be conducted on one but
not the other• Micrographs may be in a database• Taxonomic treatments or revisions may exist
Biological Science Collections (BiSciCol) Tracker
S1: KNM
S2: MNHN
Muséum national d'histoire naturelle
Nairobi National Museum
S3: MBG
Living Collection: Missouri Botanical Garden
Determination
?
?
Gene Sequence
GENBANK
?
?
?
?Parasitism
Agave sisalana
?
BiSciCol Tracker
BiSciCol Design
• Insert new design
NSF: Advanced Digitization of Biological Collections
• iDigBio: The National Resource for Advancing Digitization of Biological Collections
Organization
• National Hub (~$7.5M)– Title: A Collections Digitization Framework for the 21st Century– PI: Lawrence Page, University of Florida
• Thematic Hub (~$2M each)– Title: InvertNet–An Integrative Platform for Research on Environmental
Change, Species Discovery and Identification• PI: Christopher Dietrich, University of Illinois, Urbana-Champaign
– Title: Plants, Herbivores and Parasitoids: A Model System for the Study of Tri-Trophic Associations
• PI: Randall T. Schuh, American Museum of Natural History
– Title: North American Lichens and Bryophytes: Sensitive Indicators of Environmental Quality and Change
• PI (Principal Investigator): Corinna Gries, University of Wisconsin, Madison
Virtual Organization and Collaboration
• VOSS: Next Steps in Articulating Success Factors for Distributed Collaborations. Gary Olson [email protected] (Principal Investigator) Judith Olson (Co-Principal Investigator)
• Theory of Remote Collaboration. Evaluation A prototype online Collaboration Success Wizard will be developed for those engaged in collaboration or planning to collaborate to assess their strengths and weaknesses.
Example of Virtual Community in NanoTechnology
Three of the pioneers behind novel light-scattering techniques to detect certain early stage cancers joined an outside expert on biophotonics in a call-in program to discuss new research results that were presented in the Aug. 1, 2007, edition of Clinical Cancer Research. Richard McCourt (right), of NSF's Directorate for Biological Sciences, was the moderator.Credit: National Science Foundation
Features of Virtual Organization
• Common Goals• Geographic dispersal• Distributed strengths and capabilities• Need to multimedia collaboration• Non-residents to be treated as insiders• Document sharing, video and voice, workflow
integration.
Interdisciplinary and high volume data
• Cyberinfrastructure and the Dimensions in Biodiversity - Planning for Success -Madison, WI - Oct 13-15, 2010 Corinna Gries [email protected] (Principal Investigator) Matthew Jones (Co-Principal Investigator)David Vieglais (Co-Principal Investigator)
• Need to make order of magnitude improvements in rate of biodiversity study with 0 increase in cash.
• Development of cyberinfrastructure (CI) supporting integrative research in biodiversity sciences.
Cloud Computing
• Data-Intensive Science Workshops, to be held Sept. 19 to 20, 2010, Seattle, WA; and Mar 20 to 21, 2011, Washington DC
• Needed for most modeling with large data sets including climate models
• Needed for phylogenetic analysis
Occurrence Data Sharing• SilverLining: A highly scalable cloud-based platform for data
distribution and user collaboration. David Vieglais [email protected] (Principal Investigator) Eileen Lacey (Co-Principal Investigator)
• Potential for leveraging a cloud-based Platform as a Service (PaaS) for data publication to address myriad challenges currently faced by existing distributed data service architectures such as Distributed Generic Information Retrieval (DiGIR) and TDWG Access Protocol for Information Retrieval (TAPIR). Specific goals are to 1) simplify and reduce the ongoing cost of publishing data, 2) improve data quality at the source, 3) provide scalable, effective access to published data, 4) stimulate innovation by creating a simple, highly scalable platform for new applications for data interaction, and 5) develop a suite of reference applications demonstrating capacities of the new architecture.
Agile Science
• Disaster: RAPID: Gulf Coast Oil Spill Biodiversity Tracker. A Volunteer-based Observation Network Steven Kelling [email protected] (Principal Investigator)
• RAPID: Enhancement of Fishnet2 for Disaster Impact Assessment Henry Bart [email protected] (Principal Investigator)
http://ebird.org/tools/oilspill/
New Validation Models
• Filtered Push: Continuous Quality Control for Distributed Collections and Other Species-Occurrence Data. James Macklin [email protected] (Principal Investigator) Bertram Ludaescher (Co-Principal Investigator)
• networked solution to enable annotation of distributed biological collection data and to share assertions about their quality or usability.
Improved collection management
• Collaborative Biodiversity Collections Computing. James Beach [email protected] (Principal Investigator)
http://digbiocol.wordpress.com/
Map of Life
Co-Pis: Walter Jetz (Yale) Rob Guralnick (CU Boulder)
An infrastructure for integrating and advancing global species distribution knowledge
Scal
e (G
rain
)
World
200km
50km
1km
100m
1m
1996
: GTO
PO 3
0
2009
: SRT
MV
V4
2003
: GLC
200
0
2009
: Glo
bCov
er
1992
: BIO
ME
2001
: Im
age
2.2
Regi
onal
mod
els
TopographyLandcover
currentLandcover
future
Species distributions(Vertebrates)
?
Advancing species distribution knowledge
2006
W
WF
2005
-9: e
xper
t m
aps
Atla
s da
ta, s
urve
ys
Knowledge Gap
Hurlbert and Jetz (PNAS 2007)Jetz et al. (Conservation Biology 2008)
The “Wallacean shortfall”, i.e. the geographic bias and coarseness of our species distribution knowledge is a (the?) major impediment for biodiversity science and our understanding of global change impacts on biodiversity
Narrowing the knowledge gap:
1) Data mobilization (Museums, NGOs, GBIF)
2) Focused sampling
3) Model-based data integration
4) ‘Crowd-sourcing’
Overcoming the “Wallacean shortfall”
‘Map of Life’ aims to build on and complement the spatial biodiversity aspects of these and other efforts. By addressing key storage, query, visualization and modeling challenges common to all, and by providing mapping and data integration services, the platform is expected to empower region- and taxon-specific efforts, freeing their resources for investment in core competencies, including quality control or specific user-community needs.
Map of Life
An online workbench and knowledgebase to dynamically document, annotate, integrate, validate, advance, and analyze the disparate sources of global biodiversity distribution knowledge.
Map of Life
Display, spatially explicit WIKI
Jetz, McPherson & Guralnick. in review
Cougar
Modeling Software Support• Development of a Data Assimilation Capability Towards Ecological
Forecasting in a Data-Rich Era. Yiqi Luo [email protected] (Principal Investigator) S Lakshmivarahan (Co-Principal Investigator)
• Powerful eco-informatics tool that assimilate data from measurement sensor networks and to generate data products that will be useful for policy making on resource management and climate change mitigation. Ecological Platform for Assimilation of Data (EcoPAD) for data assimilation and forecasting in ecology. EcoPAD will include components of (1) core computational algorithms (e.g., ecological models) that are specifically designed to solve ecological issues, (2) a variety of optimization techniques for data assimilation, (3) various data bases that will feed into EcoPAD, and (4) diverse functions of EcoPAD
Formalizing Location Data
• Improving GEOLocate to Better Serve Biodiversity Informatics Henry Bart [email protected] (Principal Investigator) Nelson Rios (Co-Principal Investigator)
• a software tool for assigning latitude and longitude coordinates to text descriptions of locations where scientific collections were made (Georeferencing)
Collaborative Georeferencing
• Grant Making: about $2M/yr– Animal Tracking in South Africa– Specimen Digitization in Ghana– Social Value of Conservation in Peru– Species Pages and BD Education in Costa Rica– Niche Modeling in Brazil– Travel Grants– Lake Victoria Data Library Project in Tanzania, Uganda and
Kenya– Flora de Colombia en Línea
JRS Biodiversity Foundation
The Future is Collaboration and Data Sharing
• Libraries• Museums• Government• Universities
To bring the best data to the major problems and opportunities of our
time and the future
• NGO• Private Land Holders• Ranches• Farms