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| Titel |
Toward Open Science at the European Scale: Geospatial Semantic Array Programming for Integrated Environmental Modelling |
| VerfasserIn |
Daniele De Rigo, Paolo Corti, Giovanni Caudullo, Daniel McInerney, Margherita Di Leo, Jesus San-Miguel-Ayanz |
| Konferenz |
EGU General Assembly 2013
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 15 (2013) |
| Datensatznummer |
250084096
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| Zusammenfassung |
| Interfacing science and policy raises challenging issues when large spatial-scale (regional,
continental, global) environmental problems need transdisciplinary integration within a
context of modelling complexity and multiple sources of uncertainty [1]. This is
characteristic of science-based support for environmental policy at European scale [1], and
key aspects have also long been investigated by European Commission transnational research
[2–5].
(
|| Remotesensing
|||| differentspatial,spectral,
|||| radiometric,temporalresolution (a.1)
||||
||||
|||| Scatteredtime seriesandfieldobservations
|||| e.g. irregularspatialdensityof sampling (a.2)
||||
Geospatialdata |{ Statisticsoverterritorialadministrativeunits
X = {X1 -
-
-
Xn } = | coarsespatialaggregation overirregular
(a) (raw,derivedinformation) |||| polygons,e.g. NUTS, ISO3166 -2,... (a.3)
||||
||||
|||| Raster/vectorialderiveddata
|||| e.g. polygonsdescribing focal
|||| habitatpatterns,regulargridsof (a.4)
|||| categorical/numericalvariables
||(
...
Parameters ofthe neededdata- transformations θ = {θ1-
-
-
θm} (a.5)
Wide-scale transdisciplinary modelling for environment. Approaches (either of
computational science or of policy-making) suitable at a given domain-specific scale may not
be appropriate for wide-scale transdisciplinary modelling for environment (WSTMe) and
corresponding policy-making [6–10]. In WSTMe, the characteristic heterogeneity of available
spatial information (a) and complexity of the required data-transformation modelling
(D- TM) appeal for a paradigm shift in how computational science supports such
peculiarly extensive integration processes. In particular, emerging wide-scale integration
requirements of typical currently available domain-specific modelling strategies may
include increased robustness and scalability along with enhanced transparency and
reproducibility [11–15]. This challenging shift toward open data [16] and reproducible
research [11] (open science) is also strongly suggested by the potential – sometimes
neglected – huge impact of cascading effects of errors [1,14,17–19] within the
impressively growing interconnection among domain-specific computational models and
frameworks.
From a computational science perspective, transdisciplinary approaches to integrated
natural resources modelling and management (INRMM) [20] can exploit advanced geospatial
modelling techniques with an awesome battery of free scientific software [21,22] for
generating new information and knowledge from the plethora of composite data
[23–26].
From the perspective of the science-policy interface, INRMM should be able to provide
citizens and policy-makers with a clear, accurate understanding of the implications of the
technical apparatus on collective environmental decision-making [1]. Complexity of course
should not be intended as an excuse for obscurity [27–29].
(
|||| GNU Octave[31,32](MATLAB language)
|||| concise supportforlarge complex valued
|||| multidimensionalD -TM, sparsematrices, (b.1)
|||| nested mixedarrays,higherorderfunctions
||||
|||| GNU R [33] (R language)
|||| wide librariesofstatisticaltests,
|||| dataanalysis,classification,clustering (b.2)
Array Programming [30] ||||
||||
arraybasedD-TM f(X,θ) |||| GNU Bash[34]
data-dependent { commandlinerobustand scalabletools
(b) parameters(subD -TM ) θ(X) = || forconcisetextand file based D-TM, (b.3)
|||| scripting (sed,grep,awk,GNU CoreUtilities,...)
||||
|||| Mastrave[35,36](MATLAB language,GNU Bash,)
arraybasedsemantics |||| SemanticArray Programming,
|||| supportforarray based functionalprogramming (b.4)
||||
||||
|||| Python[37](Numpy [38],Scipy [39])
|||| Array-oriented(e.g. geo-layers)Javascriptlibraries (b.5)
|||| concise interface with geo-tools(c)anddata (a)
||(
...
Geospatial Semantic Array Programming. Concise array-based mathematical
formulation and implementation (with array programming tools, see (b)Â ) have proved
helpful in supporting and mitigating the complexity of WSTMe [40–47] when complemented
with generalized modularization and terse array-oriented semantic constraints. This defines
the paradigm of Semantic Array Programming (SemAP) [35,36] where semantic
transparency also implies free software use (although black-boxes [12] – e.g. legacy code –
might easily be semantically interfaced).
A new approach for WSTMe has emerged by formalizing unorganized best practices and
experience-driven informal patterns. The approach introduces a lightweight (non-intrusive)
integration of SemAP and geospatial tools (c) – called Geospatial Semantic Array
Programming (GeoSemAP). GeoSemAP (d)Â exploits the joint semantics provided by
SemAP and geospatial tools to split a complex D- TM into logical blocks which are easier to
check by means of mathematical array-based and geospatial constraints. Those constraints
take the form of precondition, invariant and postcondition semantic checks. This way, even
complex WSTMe may be described as the composition of simpler GeoSemAP blocks, each of
them structured as (d).
(| Systemsforsupporting geographic resourcesanalysis
|||| (e.g. scriptableGIS such asGRASS GIS[48–50],... )
|||| (c.1)
||||
|||| Geospatialdata abstraction library(GDAL [51])
Geospatialtools |||| (c.2)
{ Geospatialweb support
(c) geospatialD-TM, = || (e.g. with OGC WPS [52]: pyWPS, OpenLayers [53],... )
geospatialsemantics |||| (c.3)
||||
|||| Geospatialdatabasesupport(e.g. scriptabledataqueries
|||| with PostGIS [54]by using(b.3)[55],... ) (c.4)
|||(
...
|––––––––––––––––|
| Geo SemAP Geo |
| (c) (b) (c) |
geospatial )| | |
data(a) X |||| |geospatial - SemAP - geospatial|
|} (extended) |pre D-TM D-TM postD-TM | (extended)
parameters θ | inputdata - |geospatial SemAP geospatial| - outputdata
|||| | ::pre:: ::pre:: ::post:: |
sub D-TM θ(X) |) | ::inv:: |
| ::post:: |
|––––––––––––––––-
-–––––––---–––––––--
GeoSemAP D-TM block
(d) (
|| data Datadefinitionisextendedtoincludepropergeospatialdata
|||| (a),staticparametersandsubD -TM – whenusedas
|||| dynamic(e.g. data- dependent)parameters
|||| subD-TM Callback (functionhandle)toe.g. empiricalequations,
{ regression families,metrics/distance functions,...
where ||
|||| ::pre:: Semanticpre- conditions
|||| ::inv:: Semanticinvariants
|||| ::post:: Semanticpost- conditions
(
GeoSemAP allows intermediate data and information layers to be more easily and
formally semantically described so as to increase fault-tolerance [17], transparency and
reproducibility of WSTMe. This might also help to better communicate part of the
policy-relevant knowledge, often difficult to transfer from technical WSTMe to the
science-policy interface [1,15].
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