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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

TDWG Annual Conference 2013, Florence

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Integrating observation and survey data for production of the Essential Biodiversity Variables – the EU BON approach. TDWG Annual Conference 2013, Florence. Hannu Saarenmaa University of Eastern Finland. Main objective of EU BON building a European contribution to GEO BON - PowerPoint PPT Presentation

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Page 1: TDWG Annual Conference 2013, Florence

TDWG Annual Conference 2013, Florence

Hannu SaarenmaaUniversity of Eastern Finland

Integrating observation and survey data for production of the Essential Biodiversity Variables

– the EU BON approach

Page 2: TDWG Annual Conference 2013, Florence

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.

Page 3: TDWG Annual Conference 2013, Florence

• 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)

Page 4: TDWG Annual Conference 2013, Florence

EU BON and GEO BON: Integration of biodiversity data – across realms

• Collections• Observations• Surveys• Remote sensing• Statistics• Biologic / socioeconomic

Page 5: TDWG Annual Conference 2013, Florence

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

Page 6: TDWG Annual Conference 2013, Florence
Page 7: TDWG Annual Conference 2013, Florence
Page 8: TDWG Annual Conference 2013, Florence
Page 9: TDWG Annual Conference 2013, Florence

Achillea millefolium

According to GBIFvisualising data gaps…

Is this the reality in biodiversity monitoring?

Page 10: TDWG Annual Conference 2013, Florence

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.

Page 11: TDWG Annual Conference 2013, Florence

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

Page 12: TDWG Annual Conference 2013, Florence

Change the way we are dealing with data

Data generator

User

Data storage

Data generator

User

Data generators

User

Data generators

User

Data storage

Data storage

Data storage

Tool Tool Tool Tool

Interdisciplinarychallenges

Datainfrastructure

Supportservices

Slide by courtesy of Wouter Los

Page 13: TDWG Annual Conference 2013, Florence

Domestic storage

Bring it toa Bank

Direct transferTo a Bank

Develop trust

Slide by courtesy of Wouter Los

Page 14: TDWG Annual Conference 2013, Florence

European vision of a collaborative Data Infrastructure

DataGenerators Users

Common Data Services

Community Support Services

Persistant storage, identification, authencity, workflow execution

Data discovery & navigation, workflow generation, annotation, interpretability

User functionalities, data capture and transfer, virtual research environments

Trus

t & C

urat

ion

Slide by courtesy of Wouter Los

Page 15: TDWG Annual Conference 2013, Florence

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

Page 16: TDWG Annual Conference 2013, Florence

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)

Page 17: TDWG Annual Conference 2013, Florence

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

Page 18: TDWG Annual Conference 2013, Florence

Thank you very much for your attention

www.eubon.eu