TraitBank is the structured data service of the Encyclopedia
of Life. Launched in 2014, it currently hosts 9 million
data records for 1.7 million taxa, including trait records
(eg: cell size, life history traits) and other attributes including
administrative ones (eg: IUCN status, type specimen
repository). Marine datasets include verbal localities
from WoRMS, habitat categories from AlgaeBase, water
temperature ranges based on known occurrence records
from OBIS, and literature derived datasets including cell
masses of phytoplankton and tissue mineralization types
of algae and invertebrates. Hosted records include all
available metadata, including detailed attribution, url of
data source if online; organism information including sex
and life stage; date, locality and method information for
field studies, and any other fields provided by the source.
TraitBank is not a repository. Most hosted records are
deposited with a scholarly publication, or an institutional
or aggregator database. Presence in TraitBank makes
individual records findable by EOL search (http://eol.org/
data_search) or web search engine. Search results on EOL
are available by CSV download and records are available
to semantic web applications via a JSON-LD web service,
including all metadata. Fresh Data is a data search service
in development primarily for the Citizen Science community,
funded by NSF. Interested occurrence data providers
will register to be indexed. Their data will be deposited at
GBIF, using the IPT, if possible, and in TraitBank otherwise
(eg: presence/absence or abundance data, if GBIF
cannot accommodate them). Searchers can query the
index for recent records by time, location and taxonomic
group. Registered researchers will also be able to save and
publish their data queries, which will alert them if new
data appears matching their criteria, and alert the data
provider that their data was delivered to a subscriber.
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1. Data dissemination tools for organism
attributes and new data records
EOL: data retrieval and use 101
Jen Hammock1, Katja Schulz1, Jorrit Poelen3
1- Smithsonian’s National Museum of Natural History
2- Global Biotic Interactions
2. preview
TraitBank: organism attribute data
How can I get at it?
Example: tissue mineralization biogeography
Overview of available datasets
Ecological interactions data
Fresh Data- recent observations (sneak peek)
17. Example: tissue mineralization
biogeography
• Occurrence Data: OBIS (2015). Global biodiversity indices from the Ocean
Biogeographic Information System. Intergovernmental Oceanographic
Commission of UNESCO. Web. http://www.iobis.org (consulted on
2015/05/11)
• Mineralization types from 145 literature sources
• Trait Propagation from higher taxa according to WoRMS and AlgaeBase
18. Marine data summary
Large datasets
Environmental data ranges- lat, long, depth, temperature, water chemistry (OBIS
and World Ocean Atlas)
Geographic distribution keywords (marinespecies.org & marineregions.org)
Habitat keywords textmined from EOL articles
Ecological associations data (GloBI, aggregates from many sources, eg: GoMexSI)
Tissue mineralization
Other interesting datasets
Copepod life history and size
Phytoplankton cell mass, volume, shape
PolyTraits- polychaete life history, physical description
Mollusk shell dimensions
See all datasets
25. Robertson & Van Tassell D. & J., CC-BY-NC-SA
OBIS (2015). Global biodiversity indices from
the Ocean Biogeographic Information System.
Intergovernmental Oceanographic Commission
of UNESCO. Web. http://www.iobis.org
(consulted on 2015/05/18)
26.
27.
28.
29. problem: so many places
records might appear
Citizen reporting platforms
NaturaLista/iNaturalist
iSpot
Reef Life Survey
Small, localized monitoring projects or research projects
Social media and random places on the internet??!!!??
Museums and other natural history collections
Government agency surveys
30. Fresh Data- a community search index
Query the index for occurrence data (powered by GBIF +…)
Available to anyone
Geographical selection
Taxonomic filter
Save query
Initially only available to registered curators
Provide a sentence or two describing your interest in the data
Set email notification preferences (daily/weekly/etc.)
Anonymous or contactable?
Receive notifications when fresh data appears
Data providers will be notified that their data was sent to
someone
31. Engaging the public in scientific
research
What we know from recent studies of citizen science:
Data fit for use? This is a reasonable expectation, though it
will not necessarily take less effort to train and manage
volunteers as it would take to gather the data yourself.
Added benefit: inspired scientific literacy. *Not* necessarily
taught by the citizen science project. Participants are
motivated to go out and acquire more information.
Danielsen, F., P.M. Jensen, N.D. Burgess, R. Altamirano, P.A. Alviola, H. Andrianandrasana, J.S. Brashares, A.C. Burton, et
al. 2014. A Multi-Country Assessment of Tropical Resource Monitoring by Local Communities. BioScience, 64:236-251. [pdf]
Fortson, Lucy, Karen Masters, Robert Nichol, E. M. Edmondson, C. Lintott, J. Raddick, and J. Wallin. "Galaxy Zoo."
Advances in machine learning and data mining for astronomy (2012): 213-236.
32.
33.
34.
35. also…. ask Jen!
Thanks
This work was supported by:
The Smithsonian’s National Museum of Natural History
The Sloan Foundation
David M. Rubenstein
Jen: hammockj@si.edu
Notas do Editor
Taxon selection currently checks Catalog of Life and NCBI. When available, it will use our new consensus classification, to be based closely on Open Tree of Life.
Taxon selection currently checks Catalog of Life and NCBI. When available, it will use our new consensus classification, to be based closely on Open Tree of Life.
Don’t need details, eg: WoRMS propagation
Don’t need details, eg: WoRMS propagation
Don’t need details, eg: WoRMS propagation
Don’t need details, eg: WoRMS propagation
Where did these come from? Andrew Barton, Nick Record, Sarah Faulwetter and colleagues, LifeWatch Greece, Craig McLean, Nescent, Femorale
Call to action! Use data or contribute data. Contact Jen