The presentation of the CESAB group BETSI at the 2016 french ecology conference in the FRB-CESAB session "Using a treasury of knowledge to tackle complex ecological questions." Presenter: Johanne Nahmani
Similaire à Feedback of a couple of eco-informatic tools for soil invertebrate functional traits: an example of interoperability by semantic data integration
Similaire à Feedback of a couple of eco-informatic tools for soil invertebrate functional traits: an example of interoperability by semantic data integration (20)
Feedback of a couple of eco-informatic tools for soil invertebrate functional traits: an example of interoperability by semantic data integration
1. Feedbacks of a couple of eco-informatic tools for soil
invertebrate functional traits: an example of interoperability
by semantic data integration
Johanne Nahmani-CNRS
B. Pey, B. Laporte, M-A Laporte, S. Joimel, M. Hedde
and the BETSI Consortium
2. What is the BETSI project?
A French project, led by Mickaël Hedde, and co-administrated by B. Pey, S. Joimel and me
A consortium of 50 researchers in soil ecology
It means "Biological and Ecological Traits for Soil Invertebrates"
BETSI database requests and contributions are available after quick registration.
Database creation started in February 2011 and is operational since May 2014
The project was funded by the CESAB/FRB
BETSI PROJECT
What are the main objectives?
Summarize and organize data on soil invertebrate traits
Promote the use of trait-based approaches in soil invertebrate ecology
Give a reference structure to archive soil invertebrate trait data
1
4. What the hell are « functional traits » ?
Trait
concept
Body
length
Respiration
type
Reproduction date
Diet
TRAIT:MPPB
Traitvalue
Environmental gradient
pH optimum
Soil humidity
range
Microhabitat
ECOLOGICAL PREFERENCE
EXTENDED PHENOTYPE
Faeces carbon
content
Faeces structural
stability
Pey et al. (2014) BAAE3
5. Heterogeneity
of the data nature & sources
(numeric, discrete, textual)
Semantic heterogeneity
of trait names
(ex: body length / body size…)
These heterogeneities lead to
METHODOLOGICAL & SCIENTIFIC misunderstandings
4
Trait data = a huge heterogeneous set
6. DATABASE / BETSI
Heterogeneity
of the data nature & sources
(numeric, discrete, textual)
Fuzzy coding:
Semantic heterogeneity
of trait names
(ex: body length / body size…)
Trait data = a huge heterogeneous set
4
7. THESAURUS / TSITA
Semantic heterogeneity
of trait names
(ex: body length / body size…)
Classification
Definition
Equivalence
Trait data = a huge heterogeneous set
DATABASE / BETSI
Heterogeneity
of the data nature & sources
(numeric, discrete, textual)
Fuzzy coding:
4
9. An example of interoperability benefit
« body size » « body length »
T-SITA
Thesaurus for soil invertebrate
trait-based approaches
« Body size » term = « Body length » term
BETSI database
Input of data under the same
concept
Requesting data
Mix of data with no scientific misunderstandings
Data
management
Data
interpretation
6
15. 15
Construction of a trait thesaurus
Validated thesaurus version n
EDITION
Add / suppress trait names
and their upper concepts
Modification of their
properties (units,
definitions)
Modification of the global
structure
Add comments
1 year
VALIDATION
Vote of participants
6 months
By means of a collaborative tool to construct ecological thesaurus
17. 17
The BETSI project
• Understand and predict the biological and ecological responses of soil invertebrates to
different environmental filters acting at several scales
Decaëns et al. (2008)
Biogeography filters
Lanscape filters
Habitat filters
Internal community filters
Total pool
Present
community
21. 21
Etat de remplissage de la base
Outils opérationnels
TRAITS
Tableau Q
1250 informations
SAMPLES
Tableaux R & L
2000 informations faune
1750 pour l’environnement
22. Valorisation
Articles :
– A thesaurus for soil invertebrate trait-based approaches (T-
SITA), en préparation
– A database for soil invertebrate functional traits en
préparation
– Pey et al., A review of current use of and future needs for
soil fauna response traits, BAAE en révision
– Pelosi et al., Reducing tillage in cultivated fields: a way to
improve soil, ASE, accepté
Communications : 7 communications colloques
BETSI project is first a human adventure !
This project, lead by… and coadministrate by … gathered actually 50 Members
It means…
Access is available : if you are interested, please contact the administators
The main objectives are to : …
Trait based approach are largely used in plant Ecology to bring as ex. some new insights in the understanding and the prediction of the responses of soil invertebrate diversity to environmental changes.
As you can see here, for animal, soil invertebrates… it’s just the beginning !
Sensus stricto, a trait may be defined as « any morphological, physiological, phenological or behavioural (MPPB) feature measurable at the individual level, from the cell to the whole-organism level” . Sometimes such data are aggregated at a species level.
Sensus largo it can include Ecological preference (such as…) and the extended phenotype such as…
As a consequence, the trait data represent a data set with huge heterogenities. First, the nature and sources of data present a heterogeneity. The other heterogenity is the semantic heterogeneity of trait names. These heterogenities lead to METHODOLOGICAL & SCIENTIFIC misunderstandings.
So first, the question is : how to compare data of heterogeneous natures ? A solution is to use fuzzy coding which allow to compare data from different natures; and to include them into tbe betsi database
Now, to deal with semantic heterogeneity, a solution is to construct a thesaurus which is a controlled vocabulary, permitting to classify, define and establish Equivalence between traits
The great strength of these two ecoinformatics tools is their interoperability : the BETSI database and the T-SITA are connected. If a modification is done in one of the two tools, it is immediatly transfer in the second one.
As an exemple, you can found in the literature data concerning the lenght of the body under two different trait names : body size and body lenght.
As body length and body size are synonymous in the T-SITA, data will be input in the BETSI database under the same concept.
When requesting the data by the BETSI database, the resqueting data is a mix of data
The first major outcome of the Betsi project is the construction the T-SITA which means thesaurus for soil invertebrate trait-based approaches. The T-SITA contains at the moment approximately 100 trait names and their upper concepts. If you click on a term, for instance the body length, you can have access to its properties.
The second outcome is BETSI database. It is fully operational since 2014.
The use of the database is free after a quick registration and the agreement of a data exchange policy which protect the data users and the providers.
Today, BETSI consortium comprise 50 members
THE database host trait data of more than 1300 European sp, 45 TRAITS, and more than 13 000 informations and is associated at about 25 publications
In perspectives, …
So the BETSI consortium, that is to say about thrity researchers constructed a thesaurus for soil invertebrate traits. The construction consisted in two phases : an edition phases during which all participants could modify all the trait names and their properties (definition, unit…), their upper concepts and their hierarchical organization. Comments can be added by participant to lighten their choices. All the versions were conserved. The edition phase lasted about 1 year.
Then the second phase consisted in a voting procedure in which each participant can vote for each modification. The validation phase lasted about six months.
The procedure can be reproduced.
The whole invertebrate taxonomy from Fauna Europeae was input inside the taxonomy module and was amended for certains groups if necessary.
This database allows to store trait data in the trait module, but also data from fields in the sites and experiments modules. This data can contribute to supply trait data. For instance, individual measurement can be performed on samples individuals, and ecological performances can be construct from these data tables (such as carbon preferences).
Finally each input data must be associated with a source.
Furthermore, for continuous data only, fuzzy coding is automatically computed during the requesting procedure by the users.
And in the bottom of the window you can see the data concerning the body lenght trait which has been input in the BETSI database and the taxonomic groups and species which are concerned.