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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.

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Presentation on theme: "TDWG Annual Conference 2013, Florence Hannu Saarenmaa University of Eastern Finland Integrating observation and survey data for production of the Essential."— Presentation transcript:

1 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

2 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.

3 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)

4 EU BON and GEO BON: Integration of biodiversity data – across realms Collections Observations Surveys Remote sensing Statistics Biologic / socioeconomic

5 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

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9 Achillea millefolium According to GBIF visualising data gaps… Is this the reality in biodiversity monitoring?

10 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.

11 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

12 Change the way we are dealing with data Data generator User Data generator User Data storage Data storage Data generator User Data generator User Data generators User Data generators User Data generators User Data generators User Data storage Data storage Data storage Data storage Data storage Data storage Tool Interdisciplinary challenges Data infrastructure Support services Slide by courtesy of Wouter Los

13 Domestic storage Bring it to a Bank Direct transfer To a Bank Develop trust Slide by courtesy of Wouter Los

14 European vision of a collaborative Data Infrastructure Data Generators Data Generators Users 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 Trust & Curation Slide by courtesy of Wouter Los

15 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

16 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)

17 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

18 Thank you very much for your attention www.eubon.eu


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