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ILTER

LTER-Europe – Ontological, infrastructural and procedural achievements and challenges in the interface of long-term environmental monitoring and research. ILTER. EcoInformatics, 8-11. April 2008 Michael Mirtl & Barbara Magagna (UBA), David Stanners & Stefan Jensen (EEA). Roadmap.

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ILTER

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  1. LTER-Europe – Ontological, infrastructural and proceduralachievements and challenges in the interface oflong-term environmental monitoring and research ILTER EcoInformatics, 8-11. April 2008 Michael Mirtl & Barbara Magagna (UBA), David Stanners & Stefan Jensen (EEA)

  2. Roadmap • LTER-Europe: the network in need of cutting edge information management of environmental/ecological data • Towards a European Ecological Ontology (EEO): contents and procedural aspects • Tools: pilots of ontology based information systems

  3. PART 1: LTER-Europe • Structure • Development 2001-2008 • Coverage and Representativity • Challenges LTER: Long-term environmental/ecosystem research (a network of researchers and research hot spots at different scales)

  4. Structure of LTER-Europe Global (I)LTER LTER-Europe (and its LTER-facilities) Regional Groups National Networks Level of PLATFORMS LTSERRegion LTSERRegion Level of SITES

  5. E discussion started W first concepts network implementation formal ILTER member LTER Time-lapse 2001 2001 ALTER-I3/ M. Mirtl

  6. E discussion started W first concepts network implementation formal ILTER member 2002 LTER Time-lapse 2002 ALTER-I3/ M. Mirtl

  7. E discussion started W first concepts network implementation formal ILTER member 2003 LTER Time-lapse 2003 ALTER-I3/ M. Mirtl

  8. E discussion started W first concepts network implementation formal ILTER member 2004 LTER Time-lapse 2004 ALTER-I3/ M. Mirtl

  9. E discussion started W first concepts network implementation formal ILTER member 2005 LTER Time-lapse 2005 ALTER-I3/ M. Mirtl

  10. E discussion started W first concepts network implementation formal ILTER member 2006 LTER Time-lapse 2006 ALTER-I3/ M. Mirtl

  11. E discussion started W first concepts network implementation formal ILTER member 2007 LTER Time-lapse Feb. 2007 ALTER-I3/ M. Mirtl

  12. 2007 LTER Time-lapse June 2007 Lobbying initiated Discussion started First concepts Network implementation Formal ILTER member ALTER-I3/ M. Mirtl

  13. 2008 LTER Time-lapse January 2008 Lobbying initiated Discussion started First concepts Network implementation Formal ILTER member ALTER-I3/ M. Mirtl

  14. Facilities with LTER-potential

  15. Representativity check: LTER SOCIO-ECOLOGICAL STRATIFICATION (SER) Environmental Zones 12 48 PLUSEconomic Density PLUSPopulation Dynamics 4

  16. 42 43 Number of sites across the socio-ecological regions Economic Density (Euro / km2) 1 2 1 2 1 > 10 million 5 4 6 10 1 – 10 million 2 5 16 17 30 35 3 3 5 8 3 125 0.1 – 1 million 10 38 57 23 59 20 10 28 21 7 < 0.1 million 16 56 28 21 99 17 15 6 26 18 14 ALN BOR NEM ATN ALS CON ATC PAN LUS ANA MDM MDN MDS

  17. PART 2: Towards the European Ecological Ontology (EEO) • User needs: apparently different observations <–> ONE data unit structure • Ecological complexity vs. common denominators • LTER core • Ontology expansion • The ontology building process

  18. Concen-tration Hydrosph Point 551 Nitrate_N

  19. easy Concen-tration Hydrosph mass/vol Point 551 Nitrate_N 23 mg/lConc. OF Nitrate IN waterAT spring point 551 VALUE UNIT

  20. easy Concen-tration Hydrosph Pedosph. mass/mass mass/vol Point 134 Point 551 Norg Nitrate_N 23 mg/lConc. OF Nitrate IN waterAT spring point 551 23 g/kgConc. OF Ntot IN soil AT soil point 1034 VALUE UNIT

  21. easy Concen-tration Hydrosph Pedosph. mass/mass mass/mass mass/vol Point 134 Point 551 Norg Nitrate_N 23 mg/lConc. OF Nitrate IN waterAT spring point 551 23 g/kgConc. OF Ntot IN soil AT soil point 1034 VALUE UNIT

  22. PARAMETER [what] (char.) easy Concen-tration chemical Elements System Layer Observ. location. Hydrosph Pedosph. mass/mass mass/vol Nitrogen Point 134 Point 551 Norg Nitrate_N 23 mg/lConc. OF Nitrate IN waterAT spring point 551 ? 23 g/kgConc. OF Ntot IN soil AT soil point 1034 ? ? VALUE UNIT ?

  23. PARAMETER [what] (char.) PARAMETER [what] (char.) easy Counts Concen-tration Concen-tration chemical Elements System Layer Observ. location. Hydrosph Pedosph. Absolute conc. Relative conc. mass/mass mass/vol mass/vol Nitrogen Point 134 Point 551 Norg Nitrate_N 23 mg/lConc. OF Nitrate IN waterAT spring point 551 ? 23 g/kgConc. OF Ntot IN soil AT soil point 1034 ? ? VALUE UNIT ?

  24. PARAMETER [what] (char.) PARAMETER [what] (char.) OBJECT [of what] (entity) easy Counts Concen-tration Concen-tration chemical Elements System Layer Observ. location. Biota Hydrosph Pedosph. Absolute conc. Relative conc. 2. Main group 5. Main group elements mass/mass mass/vol mass/vol Arsenic Nitrogen Nitrogen Point 134 Point 551 Norg Norg Nitrate_N Nitrate_N 23 mg/lConc. OF Nitrate IN waterAT spring point 551 ? 23 g/kgConc. OF Ntot IN soil AT soil point 1034 ? ? VALUE UNIT ?

  25. PARAMETER [what] (char.) PARAMETER [what] (char.) OBJECT [of what] (entity) OBJECT [where] (entity) Counts Concen-tration Concen-tration chemical Elements System Layer System Layer Observ. location. Observ. location. Biota Devices Hydrosph Hydrosph Veg Water sampl.. Pedosph. Pedosph. Absolute conc. Relative conc. 2. Main group 5. Main group elements Spring sampling points mass/mass mass/mass mass/vol mass/vol Arsenic Nitrogen Nitrogen Point 134 Point 134 Point 551 Point 551 Norg Norg Nitrate_N Nitrate_N 23 mg/lConc. OF Nitrate IN waterAT spring point 551 ? 23 g/kgConc. OF Ntot IN soil AT soil point 1034 ? ? VALUE UNIT ?

  26. PARAMETER [what] (char.) OBJECT [of what] (entity) OBJECT [where] (entity) Use case Counts Concen-tration chemical Elements System Layer Observ. location. Biota Devices Hydrosph Veg Water sampl.. Pedosph. Absolute conc. Relative conc. 2. Main group 5. Main group elements Spring sampling points mass/mass mass/vol Arsenic Nitrogen Point 134 Point 551 Norg Nitrate_N 23 mg/lConc. OF Nitrate IN waterAT spring point 551 23 mg/gConc. OF Norg IN leafAT tree point 122 23 g/kgConc. OF Ntot IN soil AT soil point 1034 23 ppbConc. OF NOx IN airAT station point 01 VALUE UNIT

  27. PARAMETER [what] (char.) OBJECT [of what] (entity) OBJECT [where] (entity) Use case Counts Concen-tration chemical Elements System Layer Observ. location. Biota Devices Hydrosph Veg Water sampl.. Pedosph. Absolute conc. Relative conc. 2. Main group 5. Main group elements Spring sampling points mass/mass mass/vol Arsenic Nitrogen Point 134 Point 551 Norg Nitrate_N 23 mg/lConc. OF Nitrate IN waterAT spring point 551 23 mg/gConc. OF Norg IN leafAT tree point 122 23 g/kgConc. OF Ntot IN soil AT soil point 1034 23 ppbConc. OF NOx IN airAT station point 01 VALUE UNIT

  28. PARAMETER OBJECTS Phys. Par. Sociol. Par. System Spat. Object Biota Vertebr. Society Country Demography Attitudes LTSER Region Hom.sap. BD awareness Adults > years Classific. X Classific. Y Municip. Line Hierarchy METHODS Fieldmeth. A Document META-DATA Interview X Interview Y Acteur Project Testing extensibility e.g. towards socio-ecological data “yes”% BioDiv perceived by Adults inHuman societyin Village x VALUE UNIT

  29. Observation An observation is gaining information on the... • STATUS OF a PROPERTY • OF a MEDIUM(object) • AT a certain LOCATION (object) • AT given TIME(s) • Observed by someone/-what by use of a specific METHOD • Reported by use of and refering to related STANDARDS (unit, reference list) In addition: • Method provides certain quality of information (accuracy, applicability constraints = primary metainformation) • Status observed by an observer acting in the context of a project, pulling individual measurements together • Observation specified by other secondary metadata

  30. Project MofContext determinedBy Triangulation Method ofWhat ofSpecies 7.69 Pinus sylvestris 7.14 6.83 LTER DataUnit – Classes and Relations Height what Tree where when TempCov DU value unit m

  31. Aims of the LTER Ontology The overall aim is sharing data for data analysis Provide a description of the meaning and the structure of ecological and socio-ecological data Provide essential information to properly combine data from different data sources Merge data (various datasources) and metadata (collected via e.g. LTER Infobase) Be understandable by ecologists Be usable for IT-people for the development of a query engine and a webbased data management Be acceptable by the ontology community adhere to W3C standards (and possibly achieve itself the status of a standard or at least provide input for a W3C standard for ecological observations)

  32. OBOE ISO19115 NASA Units norms.owl Vegetation.owl Species.owl Ecosystems.owl Water.owl Geography.owl InfoBase Ecological oberservation Selection description Baseconcepts External ontologies Core ontology Domain ontology The LTER ontology components Ecological Observations Core ontology

  33. METHOD OBJECT DATAUNIT PARAMETER PARAMETER_METHOD OBJECT RESULT VALUE LTER Core: general classes and relations of ecological observations how where howWhat ofWhat hasResult what hasValue

  34. Estimation Plot Foresttype DATAUNIT Classification Classification_Estimation RESULT VALUE LTER Core: specific classes and relations of ecological observations how where howWhat ofWhat hasResult what hasValue

  35. Expanding and formalizing the LTER core

  36. Links and hyperlinked mindmap http://www5.umweltbundesamt.at/ALTERNet/index.php?title=Main_Page LTER_Onto_MindMap_1.mm

  37. The crux (or cruces!!) of expansion Interacion of „Observation“ and architecture of super-classes Domain specific search approaches and requirements Underlying ecosystem model Normalisation Expressiveness vs. computational completeness (decidability) Usability vs. generality

  38. 3 Years experience: Ontology building process Collaborative process consisting of four main steps using tools: • Identify the scope and user scenarios • Structure the information space (loose concepts)  WIKI • Conceptual model (derivation hierarchy, relation structure)  WIKI • Formal model (restrictions and rules)  PROTEGE Contributions of actors with specific roles: • The knowledge provider and user – the domain expert • The ontology design group • The ontology core group • The ontology-system developer • The ontology manager • The project manager April 08

  39. Ontology acceptance process via WIKI Article Discussion* * All other comments about this issue Open issue: ….. Responsible person: ….. Proposed solution (A): ….. Proposed solution (B): ….. Acceptance status: (in discussion, disagreed, agreed) ** For core concepts: members of the core ontology group For domain concepts: members of the ontology design group

  40. PART 3: Ontology based tools • LTER Infobase: ontology compatible metadatabase of LTER sites and data • MORIS, MORIS-site: pilots for ontology based information systems • MORIS 2.x: Incorporation of recent developments; European co-operation started 2008

  41. LTER InfoBase: Hierarchically structured metadata on 1800 LTER facilities

  42. Filling the LTER Infobase: Learning, discussing, preparing domain ontolgies

  43. MORIS Ontology based Information System MORIS: Ontology based information system OWL Editors Flat Files: . CSV .XLS Protege Swoop ….. OWL / RDF Files CMS SPARQL Server

  44. Summary 1 LTER Europe has gained experience in the following collective process of interdisciplinary teams: • Pre-structuring the information space • Formalizing an ecological core sufficing the needs of the terrestrial/aquatic domains, including biodiversity • Cross-checking with individual domains • Developing and using an ontology based pilot tool for real data manatgement (reality check) • Expanding the process to an international community • Running through the process in several iterations Expert groups have been: • Creating an OWL-DL version of an expanded ecological core  (on the WEB), considering ongoing external ontology building processes • Designing a next generation ontology-based information system

  45. Summary 2 • Besides from being a technical/intellectual/semantic challenge the management of the outlined ontology building process requires numerable soft skills • With regard to the highly necessary input of qualified experts we are challenged to change attitudes and create incentives in order to secure appropriate contributions and avoid disenchantment. • LTER-Europe has set up the database of European long-term environmental/ecosystem research facilities (LTER Infobase): It complies with the ontological concepts of LTER. Alongside its completion by scientific site co-ordinators it serves the further development of domain ontologies. • There are major potential synergies between the pragmatic requirements related to data reporting (e.g. SEIS) and environmental research: While the research needs to capitalize on accessible and interoperable environmental trend data it provides the expertise to further develop ecological ontologies which will form the backbone for increasingly sophisticated reporting requirements.

  46. End

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