SERONTOA Socio-Ecological Research and Observation Ontology

Bert van der Werf

Mihai Adamescu Minu AyromlouNicolas Bertrand Jakub BorovecHugues Boussard Constatin CazacuToon van DaeleSabina DatcuMark FrenzelVolker HammenHelena Karasti Miklos KerteszPirjo Kuitunen Mandy LaneJuraj Lieskovsky Barbara MagagnaJohannes Peterseil Sue RennieHerbert Schentz Katharina SchleidtLiisa Tuominen

ALTER-Net

A Long Term Biodiversity, Ecosystem, and Awareness Research Network funded by the European Union. ALTER-Net addresses major biodiversity issues at a European scale.

The network is a partnership of 24 organizations from 17 European countries

Work Package I6

A framework for effective information and knowledge management

Objective: To construct a framework within which can be built a system to manage biodiversity data, information and knowledge from the Network of Excellence, and to make them available to scientists, policy makers and the public.

Biodiversity data

• Different domains– ecological, meteorological, chemical, geographical,

sociological, economic, etc.

• Different languages– real language differences; scientific language differences

• Different scaling– Global, regional, site; surveys, ...

• Different purpose– monitoring versus experiments; exploration versus

parameter fitting

• Different storage methods– spreadsheets, databases; local or distributed

Purpose of framework

• data conservation• data sharing• data quality

– provenance (ISO ...)– scientific

• data integration• data mining• analysis and meta analysis

– graphically– advanced techniques

• workflows

Components for analysis• Dependent variables

– measurements/observations• Independent variables

– treatments– classifications in stratified sampling– measurements– often time

• Sources of variation– sampling structure– observer– method– design (blockings)– etc.

• Measurement scale– distributional assumptions– preferred analysis

• Assumptions

Aspects important for combining data from different sources

• methods used – relationship between methods

• units and dimensions– conversion between units

• the entity of observation/treatment– how to group them– how are they selected

Approach for Framework

• Distributed databases

• Ontologies– semantics for concepts– hierarchical structure of concepts– relationships/properties– reasoning and restriction logic– mappings and derivation

SERONTO

• Core ontology– observation ontology– units and dimensions

ontology

• Domain ontologies– taxonomy– ecology– chemistry– sociology– etc.

Domain I

Domain IIIDomain II

Core

Designing the core

• Repeatability:

The ontology should be capable of holding enough meta-data that another person can repeat the experiment or observation at another place and time.

• Transparency:

It must be possible to record and retrieve meta-data describing what actually happened.

Core contains:

• Structures for domain knowledge– Base classes for derivation– Hierarchical reference lists

• Data and meta data for observations– What, When, Where, Who, How?– What went wrong?

• Meta data for administration– Project information

• Units and dimensions• Versioning methods

Core classes:

SERONTO: basic classes

value_set

physical_thing

parameter_method

parametermethodselection_description

hasParameterMethodhasInvestigationItem

hasValue

hasSample hasMethod hasParameter

scale

hasScale

unithasUnit

hasValue

value_nominal

value_floatvalue_

nominalvalue_float

basics: example

Valueset_1

Tree_1 Parmeth_1

Height

5.5

3.3

2.2

Selection_1

hasParameterMethodhasInvestigationItem

hasValue

hasSample hasMethod hasParameter

Triangulation_Method

Real; interval; [0,infinity)

mhasUnit

hasScale

jan-2008

jan 2007

jan-2006hasTime

hasTime

hasTime

Method

Derived classes:

• Measurement method

• Treatment method

• Classification method

Method: simple example

Triangulation_Method

Determine_distance_ to_object

encompasses

Calculate_height_of_objectMeasure_angle predecessor

predecessor

encompasses

encompasses

selection_description

physical_thingintended_sample_

size

hasIntendedSampleSize

selection_description

parameter_method

sampling_method

hasClassification

hasPopulation

physical_thing

total_population_size

deviation_reason

hasSamplingMethod

hasSamplehasDeviation

Reason

hasTotalPopSize

Example Country

selection_description

hasPopulation

Forests

hasSample

Forests

selection_description

hasPopulation

Plots

hasSample

Plot

selection_description

hasPopulation

hasSample

TreeTree

Other classes:

• grouping_description:– design (treatment, measurement, layout in field,

block’s, etc.) – membership– “group by” functions (mean, variance, ...)

• reference lists– species– other nominal value lists

• actors:– persons, institutions

• project• etc.

Proof of conceptProof of Concept JOKL

culturallandscapes

JODIvegetation

2835foodplain

Pythiavegetation

ECN Summary Database

Import OWL Ontology

Connect Databases

Query

SERONTOResults

F-Logic / OntoStudio

http://www5.umweltbundesamt.at/ALTERNet/index.php?title=Main_Page