tdwg annual conference 2013, florence hannu saarenmaa university of eastern finland integrating...
TRANSCRIPT
TDWG Annual Conference 2013, Florence
Hannu Saarenmaa
University of Eastern Finland
Integrating observation and survey data for production of the Essential Biodiversity Variables
– the EU BON approach
Main objective of EU BON building a European contribution to GEO BON
A key feature of EU BON delivery of relevant biodiversity information and analysis – from on-ground / in-situ
observation and remote sensing – to various stakeholders and end users, ranging from local to global levels
The new, integrative EU BON approach will facilitate (political) decisions in different sectors concerned with biodiversity for human well-being at different levels, ranging from local park management to
national governments, and IPBES.
• gap analysis for available data layers at different scales, mainly in/for Europe (WP1)
• strategies for targeted data mobilization (WP1)• new and improved data standards for advancing interoperability
and new generation of data provider tools (WP2)• new, scalable/customized European Biodiversity Portal (WP2 /
WP8)• software tools for improved recording / mapping of habitats,
species distributions and patterns (WP3)• Improved models for impacts of different drivers on abundance &
distribution, applicable at different scales (WP4)• guidelines for improved, integrated monitoring schemes at
different scales / levels (WP4)
EU BON outputs and products (1)
EU BON and GEO BON: Integration of biodiversity data – across realms
• Collections• Observations• Surveys• Remote sensing• Statistics• Biologic / socioeconomic
Conceived by GEO BON Collaborators (Pereira et.al. (2013) “Essential Biodiversity Variables”, Science, Vol. 339, 18 Jan 2013)
EBVs facilitate data integration by providing an intermediate abstraction layer between primary observations and indicators.
EBVs aim to help observation communities harmonise monitoring, by identifying how variables should be sampled and measured.
EBVs standardise an ontology for biodiversity and harmonise measurements, observations, and protocols.
Endorsed by Convention on Biological Diversity (CBD) and in line with the 2020 Aichi Targets
Provide focus for GEO BON and hence for the interoperability thrust within GEO BON
A Use Case for EU BON to focus on
Essential Biodiversity Variables
Achillea millefolium
According to GBIFvisualising data gaps…
Is this the reality in biodiversity monitoring?
Coordination of biodiversity observation
CBD Adequacy Report:Observation systems related to the
state of biodiversity all have significant global-scale observation systems, typically with national or better resolution, already in place. There are deficiencies in the evenness of global coverage and data quality, and some of the observations are too narrow in scope, but in the opinion of the experts, fit-for-purpose adequacy is technically achievable in all cases if sufficient resources are made available.
EU BON description of work:The fragmentation and heterogeneity of environmental datasets and biodiversity observation systems remains a major challenge ... Data-collection and observation systems are unbalanced in terms of geographic, temporal, topical, and taxonomic coverage. Information currently available differs across countries and continents due to their different traditions in, and societal frameworks for biodiversity monitoring, and is often heavily biased towards easily recognizable and high profile taxa. Terrestrial, freshwater, and marine environments are studied and monitored by largely different independent communities, rarely sharing concepts, data or infrastructures.
Gap analysis
• EU BON is carrying out a gap analysis• Data gap is a gap only in context of data use.• Not same as data quality.
• In Europe there are about 2000 biodiversity observation networks (643 listed in EUMON)
• There is a massive duplication of effort in data management, and lack of data sharing
Change the way we are dealing with data
Data generator
User
Data generator
User
Data storageData
storage
Data generator
User
Data generator
User
Data generators
User
Data generators
User
Data generators
User
Data generators
User
Data storageData
storageData
storageData
storageData
storageData
storage
ToolTool ToolTool ToolTool ToolTool
Interdisciplinarychallenges
Datainfrastructure
Supportservices
Slide by courtesy of Wouter Los
Domestic storage
Bring it toa Bank
Direct transferTo a Bank
Develop trust
Slide by courtesy of Wouter Los
European vision of a collaborative Data Infrastructure
DataGenerators
DataGenerators UsersUsers
Common Data Services
Community Support ServicesCommunity Support Services
Persistant storage, identification, authencity, workflow execution
Persistant storage, identification, authencity, workflow execution
Data discovery & navigation, workflow generation, annotation, interpretability
Data discovery & navigation, workflow generation, annotation, interpretability
User functionalities, data capture and transfer, virtual research environments
User functionalities, data capture and transfer, virtual research environments
Tru
st &
Cur
atio
n
Slide by courtesy of Wouter Los
LifeWatch architecture
Virtual laboratories
for scientific cooperation
Select the data, software,
computing power
Integrate resources
Linking to resources (databases, sensors, software, computing power)
Slide by courtesy of Wouter Los
Sampling Event (DC)- Date Time- Agents- Methods
MeasurementOrFact; DwC)-Attribute (examples: identification, quantity)-Value (examples: Aus beus, 1000)-Unit (examples: species, count)-Range (examples: certain, 200)
Locality (GML, shared, external)-UUID
Sampling Object – popular fields from DwC, VegCore, O&M which are not practical to put in MeasurementOrFacts, in classes such as:-Organism occurrence, vouchered specimen, image-Plot, subplot, transect -Instrument, machine
Project or Survey (EML)-Protocol
Taxon (DwC, shared external checklist)-UUID
Need to reorganise our data standards to fit in common data services
Collection or Experimental Site (shared, external)
New generation of data sharing tools• Common data services will be based on
networked data repositories and few portals.
• Repostories need to support basic biodiversity data, AND ecological measurements, AND [what?]
• Based on existing tools• GBIF IPT: Beyond a fixed ”star
schema” to a flexible relational model
• Metacat: Start requiring use of standard terms in data
• Both need to implement an extended Darwin Core standard
• EU BON is working on a review of standards