GBIF data portal, ECPGR working group (2017-03-16)
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Transcript of GBIF data portal, ECPGR working group (2017-03-16)
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ECPGR Forage and Barley workshop
GBIF data portal
Dag Endresen GBIF Norway UiO Natural History Museum in Oslo University of Oslo Malmö, Sweden, March 16th 2017 Slides: CC-BY-4.0, GBIF.no
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GBIF.orgvisited15thMarch2017
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Asia (lack of data)
Africa (lack of data)
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MAP OF NATIONAL PARTICIPANTS
Updated January 2017
parti
cipa
tion
Asia (lack of data)
Africa (lack of data)
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DATA PUBLISHED THROUGH GBIF.ORG
www.gbif.org/analytics/global
data
ava
ilabi
lity
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TOTAL DATA PUBLISHED BY COUNTRY AS OF 15 MARCH 2016
All others
BE
ES
ZA
GB
NL
DE
AU
FRSE
US
1 United States 337,528,963 2 Sweden 61,423,202 3 France 40,469,687 4 Australia 36,435,662 5 United Kingdom 29,635,764 6 Germany 28,480,795 7 Netherlands 26,075,010 8 Norway 24,189,098 9 South Africa 21,045,000
10 Spain 14,323,393
data
ava
ilabi
lity
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OCCURRENCE RECORDS PUBLISHED DURING 2016 BY COUNTRY
All othersBEES
DKCO
NO
ZA
NL
GB
DE
US
�1
1 United States 83,774,897 2 Germany 15,837,819 3 United Kingdom 15,217,220 4 Netherlands 13,098,430 5 South Africa 9,630,896 6 Norway 4,519,715 7 Colombia 4,122,621 8 Denmark 4,048,381 9 Spain 3,175,906
10 Belgium 2,366,452
http://www.gbif.org/country
data
ava
ilabi
lity
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GBIF provides a data publishing infrastructure
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GBIFprovidesaservicefordatadiscovery
globalregistry dataportal
thatisdependentonresolvablestableiden=fiersforefficientfunc=onality
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Research institute
Biodiversity ConservationBiodiversity
AnalysisGBIF portal
Global information systems
Scientific Research
MULTIPLE-PURPOSE DATA SERVICES
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Genebank dataset
Global Crop Registries
European EURISCO Catalog
European Crop Databases
GBIF
MULTIPLEDATAEXPORTSERVICESFOREACHGENEBANK
11
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Genebank dataset
European EURISCO Catalog
MULTIPLEDATAIMPORTSERVICESFOREACHDATAPORTAL
Genebank dataset
Genebank dataset
Genebank dataset
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Genebank dataset
Global Crop Registries
European EURISCO Catalog
European Crop Databases
GBIF
àMULTIPLE-PURPOSEDATAEXPORTSERVICES
Crop portals
13
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POSSIBLEUPGRADEDPGRNETWORKMODEL
v Each dataset is shared from the holding gene bank.
v The National Inventory (NI) endorse all national gene banks for EURISCO.
v ECPGR Crop databases can access passport data from EURISCO and additional crop specific data from the gene bank IPT interface.
v Standard data sharing tools ensure that the genebank dataset is available to other relevant decentralized thematic, regional or global networks.
Illustra9onfromtheGBIFannualreport2009,page47.
14
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Use of GBIF-mediated data
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DATA DOWNLOAD REQUESTS BY COUNTRY, 2016
All others
IT
CN
IN
ZA GB CO
ES
BR
MX
US
�1
1 United States 14,700 2 Mexico 14,053 3 Brazil 7,437 4 Spain 6,443 5 Colombia 5,431 6 United Kingdom 5,195 7 South Africa 3,492 8 India 3,480 9 China 3,046
10 Italy 2,389
data
acc
ess
and
use
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2016
2015
2014
2013
2012
2011
2010
2009
2008
0 125 250 375 500
52
89
148
169
229
249
350
407
428
�1
DAT
A A
CC
ESS
AN
D U
SE
Peer-reviewed publications using GBIF-mediated data
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PEER-REVIEWED USES, BY COUNTRY AND REGION, 2016
Oceania
North America
Latin AmericaEurope
Asia
Africa
�1
Total # of papers by country 1 United States 148 2 United Kingdom 61 3 Germany 51 4 Brazil 50 5 Australia 48 6 China 41 6 Mexico 41 8 France 39 9 Spain 31
10 Canada 25 10 South Africa 25
Total # of papers by region 1 Europe 351 2 North America 173 3 Latin America 134 4 Asia 94 5 Africa 58 6 Oceania 54
data
acc
ess
and
use
2016
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2016 SCIENCE REVIEW
Annual publication summarizes more than 100 peer-reviewed articles that rely on GBIF-mediated data. Accompanying Sourcebook includes more than 400 citations. Download: § gbif.org/science-review § gbif.org/science-review-
sourcebook-2016
http://www.gbif.org/science-review
dat
a ac
cess
and
use
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GBIF Data examples of use
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USING DATA THROUGH GBIF
GBIF has established itself as an essential infrastructure underpinning science and policy related to biodiversity. Demonstrated by the growing volume of peer-reviewed research using data discovered and accessed through GBIF. Featured examples of use in Agriculture: http://www.gbif.org/newsroom/uses/agriculture
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FEATURED RESEARCH AGRICULTURE
Ramirez-CabralNYZ,KumarL,andTaylorS(2016)CropnichemodelingprojectsmajorshiSsincommonbeangrowingareas.AgriculturalandForestMeteorology.ElsevierBV,102–113.Availableatdoi:10.1016/j.agrformet.2015.12.002.Authorcountries:Australia,Mexico.108601speciesoccurrencedatarecordsused.Crop:Beans,PhaseolusvulgarisL.–(GBIFNewsstory)
Bunn,C,Läderach,P,PérezJimenez,JG,Montagnon,C,&Schilling,T(2015).Mul9classClassifica9onofAgro-EcologicalZonesforArabicaCoffee:AnImprovedUnderstandingoftheImpactsofClimateChange.PloSOne,10(10),e0140490.doi:10.1371/journal.pone.0140490.Authorcountries:Colombia,Nicaragua,UnitedStates.Crop:Arabicacoffee(Coffeaarabica)– GBIFNewsStory
DupinJ,MatzkeNJ,SärkinenTetal.(2016)Bayesianes9ma9onoftheglobalbiogeographicalhistoryoftheSolanaceae.JournalofBiogeographydoi:10.1111/jbi.12898.Authorcountries:UnitedStates,Australia,UnitedKingdom.Crop:Potato,Solanaceae–GBIFNewsStory
SamyAMandPetersonAT(2016)ClimateChangeInfluencesontheGlobalPoten9alDistribu9onofBluetongueVirus.PLOSONE.PublicLibraryofScience(PLoS)11(3):e0150489.Availableatdoi:10.1371/journal.pone.0150489.Authorcountries:UnitedStates,Egypt.40speciesoccurrencedatarecordsused.Crop:GenusCulicoides(insectpest)--GBIFNewsStory
Idohou,Retal.(2013)Na9onalinventoryandpriori9za9onofcropwildrela9ves:casestudyforBenin.Gene=cResourcesandCropEvolu=on60(4):1337-1352.doi:10.1007/s10722-012-9923-6.Authorcountries:Benin,China,UnitedKingdom.266CWRspeciesdataused.Crop:CropWildRela9ves(CWR)– GBIFNewsStory
Shabani,F,Kumar,L,andTaylor,S(2012)ClimateChangeImpactsontheFutureDistribu9onofDatePalms:AModelingExerciseUsingCLIMEXV.Magar,ed.PLoSONE,7(10),p.e48021.doi:10.1371/journal.pone.0048021.Authorcountries:Australia.163speciesoccurrencerecordsused.Crop:datepalms(Phoenixdactylifera)– GBIFNewsStory
data
acc
ess
and
use
Well-storedcommonbeans(Phaseolusvulgaris)byICIPElicensedunderCCBY2.0.
"Coffeaarabica"byForestandKimStarrlicensedunderCCBY2.0.
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FEATURED RESEARCH AGRICULTURE
OstrowskiM,ProsperiJ,andDavidJ(2016)Poten9alImplica9onsofClimateChangeonAegilopsSpeciesDistribu9on:SympatryofTheseCropWildRela9veswiththeMajorEuropeanCropTri9cumaes9vumandConserva9onIssues.PloSone11(4)e0153974.doi:10.1371/journal.pone.0153974
Galluzzi,G,Dufour,D,Thomas,E,vanZonneveld,M,EscobarSalamanca,AF,GiraldoToro,A,…GonzalezMejia,A(2015).AnIntegratedHypothesisontheDomes9ca9onofBactrisgasipaes.PloSOne,10(12),e0144644.doi:10.1371/journal.pone.0144644.Authorcountries:Colombia,CostaRica.Crop:Peachpalm(Bactrisgasipaes)--GBIFNewsStory
Solberg,SØandChou,YY(2017)Conserva9onofIndigenousVegetablesfromaHotspotinTropicalAsia:WhatDidWeLearnfromVavilov?Fron=ersinPlantScience.doi:10.3389/fpls.2016.01982Authorcountry:Taiwan.108787speciesoccurrencerecordsused.Crop:Vegetables.
PranoviF,AnelliMon9M,BrigolinD,andZuccheraM(2016)TheInfluenceoftheSpa9alScaleontheFisheryLandings-SSTRela9onship.Fron9ersinMarineScience.Fron9ersMediaSA3.Availableatdoi:10.3389/fmars.2016.00143.Authorcountries:Italy.25000speciesoccurrencedatarecordsused.
OsawaT,KohyamaKandMitsuhashiH(2016)Trade-offrela9onshipbetweenmodernagricultureandbiodiversity:Heavyconsolida9onworkhasalong-termnega9veimpactonplantspeciesdiversity.LandUsePolicy.ElsevierBV,78–84.Availableatdoi:10.1016/j.landusepol.2016.02.001.Authorcountries:Japan.1000speciesoccurrencedatarecordsused.
PhillipsJ,AsdalÅ,BrehmJM,RasmussenM,andMaxtedN(2016)Insituandexsitudiversityanalysisofprioritycropwildrela9vesinNorway.Diversityanddistribu9ons22(11):1112-1126.doi:10.1111/ddi.12470.Authorcountries:UnitedKingdom,Portugal,Norway.
data
acc
ess
and
use
AegilopscylindricaroadsideinMontanabyMarLavinlicensedunderCCBY2.0.
Peachpalm(Bactrisgasipaes)byCIFORlicensedunderCCBY-NC2.0
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TheGlobalCropWildRela9veOccurrence
Databaseincludedatafromhundredsofdata
sources–includingGBIF
TheCWRDatabaseisagainpublishedinGBIF
(excludingthedatarecordsorigina=ngfromGBIF)
DOI:10.15468/jyrthk
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GBIFprovidesmetricsfortheuseofdatasetsdownloadedfromthe
GBIFportal
EachdownloadedsetofrecordsisassignedauniqueDOIforautoma9ccita9ontracking
doi:10.15468/dl.r1lcg8 doi:10.15468/dl.vx38vkdoi:10.15468/dl.d9hpfzdoi:10.15468/dl.d9hpfz
...
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TheNordicCWRRela9veChecklistispublishedin
GBIF
doi:10.15468/itkype
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TheNordicCWRRela9veChecklistispublishedin
GBIF
doi:10.15468/itkype
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Addyourownobserva9onstothisNordicCWRgroupiniNaturalistObserva9onspeer-reviewvalidatedbyotheramateurnaturalistsarepublishedinGBIF
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Figure. The predicteddistribu9on of 187p r i o r i t y CWR i nNorway under thec u r r e n t c l i m a 9 ccondi9ons. Red areasindicate taxon-richareas with up to 124taxa found there, andgreen areas indicatelow taxon richness.Raster grid cell size0.0416,approximatelyequalto4×8km2
CWRconservaAonDevelopmentofaconserva9onplanforCropWildRela9vesinNorwayextractedtheCWRspeciesoccurrencedatapointsfromGBIFPhillips,J.,MagosBrehm,J.,vanOort,B.Asdal,Å.,Rasmussen,M.,Maxted,N.(2017)Climatechangeandna9onalcropwildrela9veconserva9onplanning.Ambio.DOI:10.1007/s13280-017-0905-yPhillips,J.Asdal,Å.,Brehm,J.M.,MortenRasmussenM.,Maxted,N.(2016)Insituandexsitudiversityanalysisofprioritycropwildrela9vesinNorway.DiversityandDistribu9ons,22,1112–1126.DOI:10.1111/ddi.12470
ExamplesofuseforGBIF-mediateddata
hrp://www.gbif.org/newsroom/uses/2016-phillips-et-al
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ELCmapsDevelopmentofaconserva9onplanforCropWildRela9vesinNorwayextractedtheCWRspeciesoccurrencedatapointsfromGBIFPhillips,J.,MagosBrehm,J.,vanOort,B.Asdal,Å.,Rasmussen,M.,Maxted,N.(2017)Climatechangeandna9onalcropwildrela9veconserva9onplanning.Ambio.DOI:10.1007/s13280-017-0905-yPhillips,J.Asdal,Å.,Brehm,J.M.,MortenRasmussenM.,Maxted,N.(2016)Insituandexsitudiversityanalysisofprioritycropwildrela9vesinNorway.DiversityandDistribu9ons,22,1112–1126.DOI:10.1111/ddi.12470
ExamplesofuseforGBIF-mediateddata
hrp://www.gbif.org/newsroom/uses/2016-phillips-et-al
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IfatreefallsintheforestandnobodypublishtheeventinGBIF,diditreallyhappen?
GlobalBiodiversityInforma9onFacility
freeandopenaccesstobiodiversitydata.
Lunch-seminar30thMarch2017NMHTøyen
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Discover and download data
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hrps://demo.gbif.org/search?q=Hordeum%20vulgare
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WestorealldownloadfilesaslongaspossibleThispagewillalwaysresolve,butthefileitselfmightberemovedinthefuture.Butwhatdoesthismean?Itmeansthatstoragespaceandfundingisn'tinfinite.Westrivetostorealldownloadsforever,butpriori9zedownloadsthathavebeencited.
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Services to enable data analysis
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GBIF DATA PORTAL API An interface to access data published through the GBIF network using web services.
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ROPENSCI : RGBIF library(rgbif) key <- name_backbone(name='Hepatica nobilis', kingdom=‘Plantae')$speciesKey sp <- occ_search(taxonKey=key, return='data', hasCoordinate=TRUE, limit=1000) gbifmap(sp)
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Data citation with DOI
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SCHOLARLY DATA CITATION IS GOOD RESEARCH PRACTICE
• Data citation integrated part of the scholarly system • Supporting research validation and reproducibility • Enable reuse of research output and results • Tracking impact of published data • Scholarly structure to reward and credit people
involved in producing research data
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DOI – DIGITAL OBJECT IDENTIFIER
Persistent resolvable identifiers Standard for scholarly journal papers Simplify citation of references Used for measuring impact
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DataPublishers
Anytool
PublisherestablishesDOIexternally
Anytool
PublisherdoesnotprovideDOIPublisherusesIPTtoregisterdatasetwithDataCite
IPT
Na9onalDataCiteService
GBIF.org
DataCiteDenmark
GBIFregistersdatasetswithoutexis9ngDOIswithDataCiteDenmark
GBIF & DIGITAL OBJECT IDENTIFIERS (DOI)
GBIFdatasetDOIlauncedinSeptember2014:hrp://vimeo.com/107148220#t=6m28s
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Usersearchesfordatathrough
GBIF.org
DataCiteDenmark
GBIF.org
GBIFassignsDOIstodatadownloads
Cleaneddata
Data
Dataarribu9on
DatasetDOI
Researcher
PaperPaperDOI
UserdepositscleaneddatasetinarepositoryandgetsDOIfordataset
Publishedpapercangive
resolvablelinkstoGBIF
downloadand/ortocleaned
dataset
Usercleansdata
Userpublishespaper
GBIFdownload
Data
Dataarribu9on
DownloadDOI
Downloadhistory
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...
GBIF.orgcreatesadownloaddataset
GBIF & DIGITAL OBJECT IDENTIFIERS (DOI)
GBIFdatasetDOIlauncedinSeptember2014:hrp://vimeo.com/107148220#t=6m28s
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WHO HAS CITED YOUR DATA RESOURCE?
CrossRef services link citations between scientific journal articles With CrossRef you can discover who has cited your research paper! Services to link dataset citations (DataCite DOI) with CrossRef systems Towards services in CrossRef to discover who cited your research data …
hrp://blog.crossref.org/?s=DataCite
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(...)
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Data Licenses (machine-readable license)
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LICENSING FOR DATA PUBLISHED THROUGH GBIF
http://www.gbif.org/terms/licences
GBIFGoverningBoardestablishedin2014supportinGBIFforthreelicensesStatus:setforalldatasetspublishedinGBIFsinceAugust2016
GBIFPortal(statusDecember2016)CC0 57%(409millionrecords)CCBY4.0 30%(215millionrecords)CCBYNC4.0 13%(93millionrecords)
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DATA LICENSE REGULATES THE POSSIBILITY FOR REUSE OF DATA
• CC0 data are made available for any use without restriction or particular requirements on the part of users.
• CC BY data are made available for any use provided that attribution is appropriately given for the sources of data used.
• CC NC data are made available for no-commercial use – however, how to limit what is considered to be "commercial use"?
• CC SA data are made available provided conditional that derived products also are shared alike as CC SA – notice that this could block desired commercial products?
• CC ND data are made available for verification read-only, however no modifications or derived products are allowed (blocking reuse)!
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H2020 – OPEN DATA BY DEFAULT FROM 2017
Kilde:OpenAIRE&EUDAT,CC-BY-4.0,2013
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Darwin Core data exchange standard
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Collec9onsprovideauniqueresource–whentheyaredigi=zedandmadepublicallyavailable.Naturalscien9stscanstudyhistoricalsamplesandtheirproper9esforspecimensarchivedtogetherwithinforma9onabout:What–Where–When–WhoThearchivedspecimensprovideaccessforscien9stsoftodaytoDNAfromindividualspecimenssampledhundredsofyearsago–somespecimensevenpre-da=ngCarlLinnaeus(1707-1778).
Illustra9onfromParkes,K.C.(1963)
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Darwin Core – a vocabulary of terms
WieczorekJ,BloomD,GuralnickR,BlumS,DöringM,DeGiovanniR,RobertsonT,andVieglaisD(2012)DarwinCore:AnEvolvingCommunity-DevelopedBiodiversityDataStandard.PLoSONE7(1):e29715.(doi:10.1371/journal.pone.0029715)
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hrp://rs.tdwg.org/dwc/terms/
Record-levelTermsdcterms:type|dcterms:modified|dcterms:language|dcterms:rights|dcterms:rightsHolder|dcterms:accessRights|dcterms:bibliographicCita9on|dcterms:references|insAtuAonID|collecAonID|datasetID|insAtuAonCode|collecAonCode|datasetName|ownerIns9tu9onCode|basisOfRecord|informa9onWithheld|dataGeneraliza9ons|dynamicProper9esOccurrenceoccurrenceID|catalogNumber|recordNumber|recordedBy|individualCount|organismQuan9ty|organismQuan9tyType|sex|lifeStage|reproduc9veCondi9on|behavior|establishmentMeans|occurrenceStatus|prepara9ons|disposi9on|associatedMedia|associatedReferences|associatedSequences|associatedTaxa|otherCatalogNumbers|occurrenceRemarksOrganismorganismID|organismName|organismScope|assocoatedOccurrences|associatedOrganisms|previousIden9fica9ons|organismRemarksMaterialSample|LivingSpecimen|PreservedSpecimen|FossilSpecimenmaterialSampleIDEvent|HumanObservaAon|MachineObservaAoneventID|parentEventID|fieldNumber|eventDate|eventTime|startDayOfYear|endDayOfYear|year|month|day|verba9mEventDate|habitat|samplingProtocol|sampleSizeValue|sampleSizeUnit|samplingEffort|fieldNotes|eventRemarksLocaAonlocaAonID|higherGeographyID|higherGeography|con9nent|waterBody|islandGroup|island|country|countryCode|stateProvince|county|municipality|locality|verba9mLocality|verba9mEleva9on|minimumEleva9onInMeters|maximumEleva9onInMeters|verba9mDepth|minimumDepthInMeters|maximumDepthInMeters|minimumDistanceAboveSurfaceInMeters|maximumDistanceAboveSurfaceInMeters|loca9onAccordingTo|loca9onRemarks|verba9mCoordinates|verba9mLa9tude|verba9mLongitude|verba9mCoordinateSystem|verba9mSRS|decimalLaAtude|decimalLongitude|geode9cDatum|coordinateUncertaintyInMeters|coordinatePrecision|pointRadiusSpa9alFit|footprintWKT|footprintSRS|footprintSpa9alFit|georeferencedBy|georeferencedDate|georeferenceProtocol|georeferenceSources|georeferenceVerifica9onStatus|georeferenceRemarksGeologicalContextgeologicalContextID|earliestEonOrLowestEonothem|latestEonOrHighestEonothem|earliestEraOrLowestErathem|latestEraOrHighestErathem|earliestPeriodOrLowestSystem|latestPeriodOrHighestSystem|earliestEpochOrLowestSeries|latestEpochOrHighestSeries|earliestAgeOrLowestStage|latestAgeOrHighestStage|lowestBiostra9graphicZone|highestBiostra9graphicZone|lithostra9graphicTerms|group|forma9on|member|bedIdenAficaAonidenAficaAonID|iden9fiedBy|typeStatus|iden9fica9onQualifier|dateIden9fied|iden9fica9onReferences|iden9fica9onVerifica9onStatus|iden9fica9onRemarksTaxontaxonID|scienAficNameID|acceptedNameUsageID|parentNameUsageID|originalNameUsageID|nameAccordingToID|namePublishedInID|taxonConceptID|scienAficName|acceptedNameUsage|parentNameUsage|originalNameUsage|nameAccordingTo|namePublishedIn|namePublishedInYear|higherClassifica9on|kingdom|phylum|class|order|family|genus|subgenus|specificEpithet|infraspecificEpithet|taxonRank|verba9mTaxonRank|scien9ficNameAuthorship|vernacularName|nomenclaturalCode|taxonomicStatus|nomenclaturalStatus|taxonRemarksResourceRelaAonship(AuxiliaryTerms)resourceRelaAonshipID|resourceID|relatedResourceID|rela9onshipOfResource|rela9onshipAccordingTo|rela9onshipEstablishedDate|rela9onshipRemarksMeasurementOrFact(AuxiliaryTerms)measurementID|measurementType|measurementValue|measurementAccuracy|measurementUnit|measurementDeterminedDate|measurementDeterminedBy|measurementMethod|measurementRemarks
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MCPD(2012) DarwinCore MCPD(2012) DarwinCore
(missing) dwc:datasetID 15.5 COORDUNCERT dwc:coordinateUncertaintyInMeters
(missing) dwc:occurrenceID 15.6 COORDDATUM dwc:geode9c.Datum
1 INSTCODE dwc:ins9tu9onCode 15.7 GEOREFMETH dwc:georeferenceSources
2 ACCENUMB dwc:catalogNumber 16 ELEVATION dwc:minimumEleva9onInMeters
3 COLLNUMB dwc:recordNumber 17 COLLDATE dwc:eventDate
4 COLLCODE g:collec9ngIns9tuteCode 18 BREDCODE g:breederIns9tuteID
4.1 COLLNAME dwc:recordedBy 18.1 BREDNAME g:breedingIns9tute
4.1.1 COLLINSTADDRESS (dwc:recordedBy) 19 SAMPSTAT g:biologicalStatus
4.2 COLLMISSID dwc:collec9onCode 20 ANCEST g:ancestralData,g:purdyPedigree
5 GENUS dwc:genus 21 COLLSRC g:acquisi9onSource
6 SPECIES dwc:specificEpithet 22 DONORCODE g:donorIns9tuteID
7 SPAUTHOR dwc:scien9ficNameAuthorship 22.1 DONORNAME g:donorIns9tute
8 SUBTAXA dwc:infraspecificEpithet 23 DONORNUMB g:donorsIden9fier
9 SUBTAUTHOR (dwc:scien9ficNameAuthorship) 24 OTHERNUMB dwc:otherCatalogNumbers
10 CROPNAME dwc:vernacularName 25 DUPLSITE g:safetyDuplica9onIns9tuteID
11 ACCENAME g:breedingIden9fier 25.1 DUPLINSTNAME g:safetyDuplica9onIns9tute
12 ACQDATE g:acquisi9onDate 26 STORAGE g:storageCondi9on
13 ORIGCTY dwc:countryCode 27 MLSSTAT g:mlsStatus
14 COLLSITE dwc:locality 28 REMARKS dwc:occurrenceRemarks
15.1 DECLATITUDE dwc:decimalLa9tude
15.2 LATITUDE dwc:verba9mLa9tude
15.3 DECLONGITUDE dwc:decimalLongitude
15.4 LONGITUDE dwc:verba9mLongitude
MappingofDwCtotoMCPD
66
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Evaluation data
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Evalua9ondataispublishedinanextension(notyetfullysearchable)Example:hrp://doi.org/10.15468/gkeszohrp://www.gbif.org/occurrence/1040328345/verba9m
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Publish your biodiversity data with GBIF
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PUBLISH DATA IN GBIF da
ta p
ublis
hing
Step 1: data holding research institutes seek endorsement as an approved data publisher.
Step 2: datasets are identified and converted to standard Darwin Core format.
Step 3: datasets can be published directly from the data node and/or with the assistance from a national GBIF node (helpdesk).
Citizen science data platforms also publish in GBIF.
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WHAT IS DATA PUBLISHING?
“Publishing” refers to making biodiversity datasets publicly accessible and discoverable, in a standardized form, via an access point, typically a web address (a URL).
IPT
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Datapublishingguidelines
hrp://www.gbif.org/resources?f[0]=gr_purpose%3A955
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Thelargestchallengeforefficientu9liza9onofbiodiversitycollec9ondataarelackingaccesstodigiAzedelectronicinformaAonaboutthespecimenobjects(Berendsohnetal.2010).GlobalBiodiversityInforma9onFacility(GBIF)isaglobalorganiza9onwithamissionof"Freeandopenaccesstobiodiversitydata".hrp://www.gbif.org
Photo:OrnithologyCollec9on,SmithsonianNa9onalMuseumofNaturalHistoryMuseum,byChipClark.
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Persistent Identifiers Digital Object Identifiers (DOI)
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The purpose of identifiers …is to name things,
making it possible to refer to them.
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Manythings(inGBIF)arenamed123
Catalognumber:123GBIFID:543392241urn:catalog:CAS:BOT:123Bigelowiajuncea
Catalognumber:123GBIFID:1030591721UAMb:Herb:123Sphagnumgirgensohnii
Catalognumber:123GBIFID:893477175Parideserithalion
Catalognumber:123GBIFID:1050327334Cinchonaledgeriana Catalognumber:123
GBIFID:931031820Bromuskalmii
Catalognumber:123GBIFID:283363urn:occurrence:Arctos:MVZ:Egg:123:164Mercurialisovata
Catalognumber:123GBIFID:231564351Umbrinacanariensis
Catalognumber:123GBIFID:896547722urn:occurrence:Arctos:MVZ:Egg:123:164Contopussordidulusveliei
NAME AMBIGUITY:
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Includingmachine-readableformats
urn:uuid:41d9cbb4-4590-4265-8079-ca44d46d27c3
dc:iden9fier"urn:uuid:41d9cbb4-4590-4265-8079-ca44d46d27c3"
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DATA CITATION PRINCIPLES
1. Data to be legitimate citable products of research. 2. Data citations giving scholarly credit and attribution. 3. In scholarly literature, whenever claims are based on data, data should
always be cited. 4. Persistent method for identification of data, that is machine actionable,
globally unique, universal. 5. Data citation facilitate access to data or at least to metadata. 6. Unique identifiers that persist even beyond the lifespan of the data. 7. Data citation identify and access the specific data that support verification
of the claim (provenance, time-slice, version). 8. Flexible, but attention to interoperability of practices across communities.
Data Citation Synthesis Group: Joint Declaration of Data Citation Principles. Martone M. (ed.) San Diego CA: FORCE11; 2014
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"FAIR" DATA Findable
– assign persistent IDs, provide rich metadata, register in a searchable resource (such as GBIF)
Accessible – Retrievable by their ID using a standard protocol,
metadata remain accessible even if data aren’t
Interoperable – Use formal, broadly applicable languages, use
standard vocabularies, qualified references (e.g. Darwin Core)
Reusable – Rich, accurate metadata, clear licences, provenance,
use of community standards (e.g. Dublin Core, EML)
www.force11.org/group/fairgroup/fairprinciples
Slide source: OpenAIRE & EUDAT, CC-BY-4.0, 2013
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GBIF news
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LATEST NEWS
'Names in November' workshop targets single shared species list Partnership with taxonomic community aims for a single, sustainable information service for species names Read more
63.8 million new observations increase eBird total to 275 million records Annual dataset refresh grows by 30 per cent, with biggest gains in Asia and Europe Read more
http://www.gbif.org/newsroom/summary Photo credits: (center) courtesy of Peter Schalk.
(right) Abdomen of emerald ash borer (Argils planipennis) at 50x magnification by Macroscopic Solutions via Flickr. Photo licensed under CC BY-NC 2.0.
com
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Experts outline strategy for improving alien species information Task group recommends actions for reducing the impacts of invasive species on biodiversity Read more
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LATEST NEWS
First BID grants provide nearly €1 million in funding to 23 African projects ¤ EU-funded programme grantees
represent 34 organizations from 20 African countries (Read more)
¤ Open call for Caribbean and the Pacific (read more)
¤ Read more about BID
http://www.gbif.org/newsroom/summary Photos: (left) One Tree Plain, CC BY-NC-SA 2015 Geoff Livingston, (centre) Peacock pansy (Junonia almana), Ho Chi Minh, Vietnam.
CC BY-SA 2015 Pavel Kirillov via iNaturalist. (right) Photo courtesy of Nestor Engone Obiang.
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BIFA grants to benefit 14 Asian countries Four project share €106,000 in funding to enhance data publishing capacity of current and future network members. Read more
Belgium, Taiwan and Norway nodes provided BIFA funded mentoring for the AESEAN heritage parks in July 2016. Read more (at gbif.no)
Appeal for help after damage Gabon's national herbarium
Post-election riots in September spared collections, but caused major damage to the BID grantee’s headquarters in Libreville, Gabon.
Read English or French
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LATEST NEWS
Four network projects awarded 2016 capacity enhancement support grants (mentoring) ¤ A total of €23,300 in funding will
support the work of GBIF nodes and partners in five countries (Colombia, France, Guinea, Portugal, Spain).
¤ Read more
http://www.gbif.org/newsroom/summary Photos:. (center) courtesy of GBIF Portugal.
(right) Red-crested pochards (Netta rufina) off the eastern shore of Obersee, Switzerland, photo by roby 2016 CC BY-NC via iNaturalist.
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Four countries become the GBIF network’s newest national members ¤ Switzerland (voting) ¤ Ecuador (associate) ¤ Niger (associate) ¤ Nigeria (associate)
New Darwin Core templates released Pre-configured Excel templates simplify data formatting, preparation and publication. – metadata template – checklist template – occurrence template – sampling event template Read more Template tool from GBIF.no
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LATEST NEWS
http://www.gbif.org/newsroom/summary Photos: (far right) © 2016 Williams Fagner.
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Data licensing milestone
All species occurrence datasets on GBIF.org now carry standardized Creative Commons licenses.
CC0 57 % CC-BY 4.0 30 % CC-BY-NC 4.0 13 %
Read initial announcement and update
2016 Ebbe Nielsen Challenge winner
Alejandro Ruete (Argentina, postdoc at SLU, Sweden) seeks to calculate ‘Where and when is there enough data?’
Read more
2016 Young Researchers Awards
Meet the winners!
– Mexican PhD student Juan M. Escamilla Mólgora
– Brazilian Master’s student Bruno Umbelino