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“Conservation Biology publishes groundbreaking papers and is instrumental in defining the key issues contributing to the study and preservation
- f species and habitats.”
Biodiversity Research and Biodiversity Research and Conservation in - - PowerPoint PPT Presentation
Biodiversity Research and Biodiversity Research and Conservation in - - PowerPoint PPT Presentation
Biodiversity Research and Biodiversity Research and Conservation in a Digital World Conservation Biology publishes groundbreaking papers and is instrumental in defining the key issues contributing to the study and preservation of species and
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General Experimental Design
- Focused Surveys
- Broad-scaled Monitoring
- Synthesis and Modeling
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Conservation Biology
80 60 70 40 50 FOCUSED SURVEY BROAD‐SCALE MONITORING 20 30 BROAD SCALE MONITORING SYNTHESIS/MODELING 10 20 2004 2005 2006 2007 2008 2009
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Global change
Smith, Knapp, Collins. In press.
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Increasing Human Population
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“Megapolitan”ization
Business 2 0 (November 2005) Business 2.0 (November 2005)
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Computation resources and a growing cyberinfrastructure is now an equal and indispensible partner for the advance of scientific knowledge.
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Presentation Goals
The computational framework for biodiversity research The computational framework for biodiversity research. The cyberinfrastructure for data curation and access. Define environmental observational data networks. Describe the Data Intensive Science research paradigm. Provide a domain example.
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The computational framework for biodiversity research. Moore’s Law The number of transistors that can be placed inexpensively on an integrated circuit will increase exponentially, doubling approximately every two years.
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The computational framework for biodiversity research.
- Computational power
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The computational framework for biodiversity research.
Multivariate Madness
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The computational framework for biodiversity research. The coupling of human and natural systems.
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The computational framework for biodiversity research.
http://sciencepipes.org
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The computational framework for biodiversity research.
Support application scripts in R, Matlab, etc. http://kepler-project.org Streaming Data from observatory D t T bi S Modular components, il d d h d DataTurbine Server easily saved and shared
Publish to workflow repository with accession number Documents the linkage between Documents the linkage between publication, analysis, and data
Graphs and derived data can be archived and displayed
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The cyberinfrastructure for biodiversity research.
- Access
- Data organization
- Archive
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The cyberinfrastructure for biodiversity research. P d t ti Poor data practice
“data entropy”Time of publication
Specific details General details
ent
General details Retirement or h
tion Conte
Accident career change
Informat
Death
Time
(Michener et al. 1997)
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The cyberinfrastructure for biodiversity research. Data loss
- Natural disaster
- Facilities infrastructure failure
- Storage failure
- Server hardware/software failure
- Application software failure
Application software failure
- External dependencies (e.g. PKI
failure)
- Format obsolescence
- Legal encumbrance
- Legal encumbrance
- Human error
- Malicious attack by human or
automated agents
- Loss of staffing competencies
- Loss of staffing competencies
- Loss of institutional commitment
- Loss of financial stability
- Changes in user expectations
and requirements and requirements
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The cyberinfrastructure for biodiversity research.
Transient information
- r unfilled
demand for demand for storage
Source: John Gantz, IDC Corporation: The Expanding Digital Universe
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The cyberinfrastructure for biodiversity research. Data deluge
“the flood of increasingly heterogeneous data”
- Data are heterogeneous
- Data are heterogeneous
– Syntax
- (format)
S h – Schema
- (model)
– Semantics
- (meaning)
Jones et al. 2007
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The cyberinfrastructure for biodiversity research. S ti th d t lif l Supporting the data lifecycle
ORC UCSB Node UNM Node Node
1. Deposition/acquisition/ingest 2. Curation and metadata management 3 Protection including privacy The data } 3. Protection, including privacy 4. Discovery, access, use, and dissemination 5. Interoperability, standards, and integration 6. Evaluation, analysis, and visualization lifecycle }
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Building global communities of practice: … creating long-lived CI enterprises,
- Broad, active community engagement
– Involvement of library and science educators engaging new generations of students in best practices generations of students in best practices – Existing outreach and education programs
- Transparent, participatory governance
- Adoption/creation of innovative and sustainable business
and organizational models
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The Earth Observation Network Metcalf’s Law
The value of a network grows by the square of the size of the network. g y q
- Sensors
- Sensor Networks
- Observational Data
Global Internet Network Image from the Lumeta Internet Mapping Project
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The Earth Observation Network Sensors, sensor networks, and remote sensing gather observations. Se so s, se so et o s, a d e
- te se s g gat e obse
at o s
Photo courtesy of www.carboafrica.net
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The Earth Observation Network Sensors, remote sensing, sensor networks, and observational data Se so s, e
- te se s g, se so
et o s, a d obse at o a data
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The Earth Observation Network
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The Earth Observation Network
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The Earth Observation Network
e ge Coverag Knowledg g Spatial Process K ecreasing reasing P De Incr
Adapted from CENR-OSTP p
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Data Intensive Science
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Avian Knowledge Network http://avianknowledge.net
Access to data in a standardized format Tools to explore and visualize data New analysis techniques to discover patterns of species occurrence
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Avian Knowledge Network
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Avian Knowledge Network
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Avian Knowledge Network
Data Synthesis and Access
htt // i k l d t http://www.avianknowledge.net
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Avian Knowledge Network
Exploratory Analysis: Partial Dependency Plots using Bagged Decision Trees
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Avian Knowledge Network
Exploratory Analysis: Modeling Dynamic Patterns of Species Occurrence Eastern Phoebe
Sullivan et al Biological Conservation 2009
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Biodiversity Research and Conservation in a Digital World Gaining insight into the complexities and processes of natural systems is no longer an exclusive realm of theory and systems is no longer an exclusive realm of theory and experiment; computation is now an equal and indispensible partner for advances in scientific knowledge, land management and informed decision making management, and informed decision making.
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