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A decadal view of biodiversity informatics: challenges and priorities Alex Hardisty, Dave Roberts, and the
biodiversity informatics community*
* 80 people took part in the open debate that led to this paper
Virtual BiodiversityViBRANT
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A decadal view of biodiversity informatics: challenges and priorities Alex Hardisty, Dave Roberts, and the
biodiversity informatics community*
* 80 people took part in the open debate that led to this paper
“We are drowning in information, while starving for wisdom. The world henceforth will be run by synthesizers, people able to put together the right information at the right time, think critically about it, and make important choices”
E. O. Wilson, "Consilience: The Unity of Knowledge" (1998)
Virtual BiodiversityViBRANT
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A decadal view of biodiversity informatics: challenges and priorities Alex Hardisty, Dave Roberts, and the
biodiversity informatics community*
* 80 people took part in the open debate that led to this paper
“We are drowning in information, while starving for wisdom. The world henceforth will be run by synthesizers, people able to put together the right information at the right time, think critically about it, and make important choices”
Time to model all
life on Earth.
Purves et. al. (2013) Nature, 493: 295-297
E. O. Wilson, "Consilience: The Unity of Knowledge" (1998)
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An infrastructure to allow the available data to be brought into a coordinated coupled modelling environment, capable of addressing questions relating to our use of the natural environment, that captures the variety, distinctiveness and complexity of all life on Earth
A decadal view of biodiversity informatics: challenges and priorities Alex Hardisty, Dave Roberts, and the
biodiversity informatics community*
* 80 people took part in the open debate that led to this paper
The Grand Challenge for Biodiversity Informatics
To achieve it we need:To build user confidenceIntegrative flexible e-Science environmentsPredictive models across multiple scales, coupled
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1. Open Data should be normal practice;
Virtual BiodiversityViBRANT
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1. Open Data should be normal practice;2. Data encoding should
allow analysis across multiple scales;
Virtual BiodiversityViBRANT
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1. Open Data should be normal practice;2. Data encoding should
allow analysis across multiple scales;
3. Infrastructure projects should devote significant resources to market the service they develop;
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Actinobacillus actimomycetemcomitansActinobacillus actimycetemcomitansActinobacillus actinmycetemcomitansActinobacillus actinomicetemcomitansActinobacillus actinomyActinobacillus actinomyceActinobacillus actinomycemcomitansActinobacillus actinomyceremcomitansActinobacillus actinomycetamActinobacillus actinomycetamcomitansActinobacillus actinomycetecomitansActinobacillus actinomycetemcmitansActinobacillus actinomycetemcomintansActinobacillus actinomycetemcomitanceActinobacillus actinomycetemcomitansActinobacillus actinomycetemcomitants
Actinobacillus actinomycetemcommitansActinobacillus actinomycetemocimitansActinobacillus actinomycetencomitansActinobacillus actinomycetumActinobacillus actinomyctemcomitansActinobacillus actinomyectomcomitansActinobacillus actinomyetemcomitansActinobacillus actinonmycetemcomitansActinobacillus actionomycetemcomitansActinobacillus actynomicetemcomitansActinobacillus antinomycetemcomitans
Difficulties with Latinized NamesTranscription errors
Nomenclator provides correct spelling. Indexing infrastructure resolves to it.
Names as strings of characters… 4. A list of taxon names
DOI: 10.4289/0013-8797.115.1.75
5. Persistent Identifiers
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Actinobacillus actimomycetemcomitansActinobacillus actimycetemcomitansActinobacillus actinmycetemcomitansActinobacillus actinomicetemcomitansActinobacillus actinomyActinobacillus actinomyceActinobacillus actinomycemcomitansActinobacillus actinomyceremcomitansActinobacillus actinomycetamActinobacillus actinomycetamcomitansActinobacillus actinomycetecomitansActinobacillus actinomycetemcmitansActinobacillus actinomycetemcomintansActinobacillus actinomycetemcomitanceActinobacillus actinomycetemcomitansActinobacillus actinomycetemcomitants
Actinobacillus actinomycetemcommitansActinobacillus actinomycetemocimitansActinobacillus actinomycetencomitansActinobacillus actinomycetumActinobacillus actinomyctemcomitansActinobacillus actinomyectomcomitansActinobacillus actinomyetemcomitansActinobacillus actinonmycetemcomitansActinobacillus actionomycetemcomitansActinobacillus actynomicetemcomitansActinobacillus antinomycetemcomitans
Difficulties with Latinized NamesTranscription errors
Nomenclator provides correct spelling. Indexing infrastructure resolves to it.
Names as strings of characters… 4. A list of taxon names
DOI: 10.4289/0013-8797.115.1.75
5. Persistent Identifiers
6. Author identifiers
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7. 3rd party authentication
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8. Classification Bank
Embley & Stackebrandt (1994) Bergey’s Manual, 2nd Edition (2012)
Actinomycetes: the antibiotic factories
Atopobium minutumSphaerobacter thermophilus
strain TH3
Bifidobacteriaceae
Actinomycetaceae
Arthrobacteriaceae, Cellomonadaceae, Microbacteriaceae, Dermatophilaceae and realtives
Propionibacteriaceae
Nocardioidaceae
Frankiaceae
Corynebacteriaceae, Mycobacteriaceae, Nocardiaceae and realtives
Actinoplanaceae
Pseudonocardiaceae
Streptomycetaceae, Streptosporangiaceae and relatives
Insertion element in 23S rRNA
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9. Accepted names
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I . P . N . I
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10. Tools to make LOD
Implicit semantics“Compound 2a melted at 119oC”
Humans are good at interpreting this:
Explicit semantics CML Schema<cml:molecule ref=“2a”> <cml:property> <cml:scalar dictRef=“prop:mpt” units=“units:celsius” dataType=“xds:float” >119</cml:scalar> </cml:property></cml:molecule>
Molecules in CML/InChl
propertyDictionaryunitsDictionary
W3CSchema
4 namespaces, 3 dictionaries
Machines need this:
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GBIF/GBIC – 2-4 Jul 2012 – Copenhagen, © 2012, R. J. Robbins
The generation of important new insights while handicapped with limited technology, indirect measurement, and fuzzy data is the mark of scientific greatness.
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11. Data fit for purposeData are received at face-value, examined and tested. If the user is satisfied, then the data will be applied.
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12. Observational data infrastructure
Agriculture Systems
Climate Change
Forest Management
Invasion Biology
Urban Ecosystems
http://www.teamnetwork.org
http://www.earthobservations.org/geobon.shtml
http://www.eubon.eu
http://www.neoninc.org
http://mooreabiocode.org/
Moorea Biocode Project
http://www.ilternet.edu
GBIO Document
Courtesy of Donald Hobern: http://tinyurl.com/BIH13-hobern
http://www.biodiversityinformatics.org/
RESEARCH INFRASTRUCTURE INVESTMENTS
OTHER INFORMATION
DOMAINS
ASSESSMENTS AND INDICATORS
GBIO Framework
Courtesy of Donald Hobern: http://tinyurl.com/BIH13-hobern
Focus Area: Evidence
• Organised views of biodiversity data– Consistent assessment of quality and fitness-for-use– Comprehensive digital nomenclature and taxonomy– Access to all evidence for recorded species occurrence– Access to species traits, measurements and interactions– Services and interfaces to access data as needed
• Provide comprehensive organised views of all relevant data
• Act as a “lens” into primary data
Courtesy of Donald Hobern: http://tinyurl.com/BIH13-hobern
http://tinyurl.com/oalvv8rStructuring the biodiversity informatics community at the European level and beyond
Clarity of vision, greater focus on end-goals;Good, simple tools with syntactic operability;Community identity;Better links within our community and with other disciplines - ecology, agriculture, socioeconomics, remote sensing, etc..
The biodiversity informatics community needs :
We have a lot of data. Now we need to show that those data are actually useful.
What questions can these data address?Stop mobilising just any data. Invert the system and direct what
data are to be recovered by the question that is being addressed. This will also dictate the quality level.
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To build user confidence
Thus far, all projects share a common problem of keeping services running after project funding ended
New models are needed
To create translational pipelines to industry adoption
To encourage institutional adoption for care and maintenance
For recognition of contribution other than through publication of academic papers
Stronger marketing and outreach
Invest more in up-skilling and hand-holding
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Integrative flexible e-Science environmentsUsing standardised building blocks and workflows
Interoperable components
With access to data from multiple sources
Recognise different kinds of VRE
General-purpose / specialised / single scientific objective
- cf. chemistry laboratory vs forensics lab vs HIV vaccine lab
- Scratchpads & BioVeL / AquaMaps and iMarine / CarbonWaterCloud
Must generate immediate benefit for users
Science driven, with scientists as active participants in creation of infrastructure
Functions people find useful: simple and intuitive Technology invisible (disappears into background)
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Predictive models across multiple scales
A new framework of methods, techniques, standards to bring about interoperability of data and models across different biological scales
From Genetic through species and ecosystem to landscape
Learn from Virtual Physiological Human and from Numerical weather prediction and climatology Edwards (2010). A Vast Machine
“General Ecological Models” Purves et al. (2013). doi:10.1038/493295a
Evolvable to incorporate new scientific insights
Re-analysis models
Making data we have global
Implies ‘inversion’ of existing infrastructure
‘inversion’ of existing infrastructure is about re-examining every element of data we have to re-construct the past biodiversity, as a guide and calibrator of models that can predict the future
http://h2020.myspecies.info
ViBRANTVirtual Biodiversity
Structuring the biodiversity informatics community at the European level and beyond
Our goal, sine qua non, is to deliver predictive
modelling of the biosphere.