Toward open science at the European scale: Geospatial Semantic Array Programming for integrated environmental modelling

Abstract

Excerpt: 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. This is characteristic of science-based support for environmental policy at European scale, and key aspects have also long been investigated by European Commission transnational research. 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. In WSTMe, the characteristic heterogeneity of available spatial information 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. This challenging shift toward open data and reproducible research (open science) is also strongly suggested by the potential - sometimes neglected - huge impact of cascading effects of errors within the impressively growing interconnection among domain-specific computational models and frameworks. Concise array-based mathematical formulation and implementation (with array programming tools) have proved helpful in supporting and mitigating the complexity of WSTMe when complemented with generalized modularization and terse array-oriented semantic constraints. This defines the paradigm of Semantic Array Programming (SemAP) where semantic transparency also implies free software use (although black-boxes - 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 - called Geospatial Semantic Array Programming (GeoSemAP). GeoSemAP 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. GeoSemAP allows intermediate data and information layers to be more easily and formally semantically described so as to increase fault-tolerance, transparency and reproducibility of WSTMe. This might also help to better communicate part of the policy-relevant knowledge, often diffcult to transfer from technical WSTMe to the science-policy interface. [...] ► How to cite: ◄ de Rigo, D., Corti, P., Caudullo, G., McInerney, D., Di Leo, M., San-Miguel-Ayanz, J., 2013. Toward open science at the European scale: Geospatial Semantic Array Programming for integrated environmental modelling. Geophysical Research Abstracts 15, 13245+. https://doi.org/10.6084/m9.figshare.155703

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2013 Daniele de Rigo, Paolo Corti, Giovanni Caudullo,
Daniel McInerney, Margherita Di Leo, Jes´us San-Miguel-Ayanz.
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Cite as:
de Rigo, D., Corti, P., Caudullo, G., McInerney, D., Di Leo, M., San Miguel-Ayanz, J., 2013.
Toward Open Science at the European Scale: Geospatial Semantic Array Programming
for Integrated Environmental Modelling. Geophys Res Abstr 15,13245+
Authors’ version DOI: 10.6084/m9.figshare.155703 (FigShare Digital Science)

Toward Open Science at the European Scale:
Geospatial Semantic Array Programming for
Integrated Environmental Modelling
Daniele de Rigo 1,2, Paolo Corti 1,3, Giovanni Caudullo 1, Daniel McInerney 1,
Margherita Di Leo 1, and Jes´us San-Miguel-Ayanz 1
1European Commission, Joint Research Centre, Institute for Environment and Sustainability,
Via E. Fermi 2749, I-21027 Ispra (VA), Italy
2Politecnico di Milano, Dipartimento di Elettronica e Informazione,
Via Ponzio 34/5, I-20133 Milano, Italy
3United Nations World Food Programme,
Via C.G.Viola 68 Parco dei Medici, I-00148 Rome, Italy
Interfacing science and policy raises challenging issues when large spatial-scale (regional, continental,
global) environmental problems need transdisciplinary integration within a context of modelling com-
plexity and multiple sources of uncertainty [1]. This is characteristic of science-based support for envi-
ronmental policy at European scale [1], and key aspects have also long been investigated by European
Commission transnational research [2–5].
(a)
Geospatial data
X={X1· · · Xn}
(raw, derived information)
=
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Remote sensing
different spatial, spectral,
radiometric, temporal resolution
(a.1)
Scattered time series and field observations
e.g. irregular spatial density of sampling (a.2)
Statistics over territorial administrative units
coarse spatial aggregation over irregular
polygons, e.g. NUTS, ISO 3166 - 2, ...
(a.3)
Raster/vectorial derived data
e.g. polygons describing focal
habitat patterns, regular grids of
categorical/numerical variables
(a.4)
...
Parameters of the needed data-transformations θ={θ1· · · θm}(a.5)
1

de Rigo, D., Corti, P., Caudullo, G., McInerney, D., Di Leo, M., San Miguel-Ayanz, J., 2013. Toward Open Science at the European
Scale: Geospatial Semantic Array Programming for Integrated Environmental Modelling. Geophys Res Abstr 15,13245+
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].
(b)
Array Programming [30]
array based D-TM f(X, θ)
data-dependent
parameters (sub D-TM) θ(X)
array based semantics
=
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GNU Octave [31,32] (MATLAB language)
concise support for large complex valued
multidimensional D-TM, sparse matrices,
nested mixed arrays, higher order functions
(b.1)
GNU R [33] (R language)
wide libraries of statistical tests,
data analysis, classification, clustering
(b.2)
GNU Bash [34]
commandline robust and scalable tools
for concise text and file based D-TM,
scripting (sed, grep, awk, GNU Core Utilities, ...)
(b.3)
Mastrave [35,36] (MATLAB language, GNU Bash, )
Semantic Array Programming,
support for array based functional programming
(b.4)
Python [37] (Numpy [38], Scipy [39])
Array-oriented (e.g. geo-layers) Javascript libraries
concise interface with geo-tools (c) and data (a)
(b.5)
...
2

de Rigo, D., Corti, P., Caudullo, G., McInerney, D., Di Leo, M., San Miguel-Ayanz, J., 2013. Toward Open Science at the European
Scale: Geospatial Semantic Array Programming for Integrated Environmental Modelling. Geophys Res Abstr 15,13245+
Geospatial Semantic Array Programming
Concise array-based mathematical formulation and implementation (with array programming tools, see
(b) ) have proved helpful in supporting and mitigating the complexity of WSTMe [40–47] when comple-
mented 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) 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).
(c)
Geospatial tools
geospatial D-TM,
geospatial semantics
=
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Systems for supporting geographic resources analysis
(e.g. scriptable GIS such as GRASS GIS [48–50], ... ) (c.1)
Geospatial data abstraction library (GDAL [51]) (c.2)
Geospatial web support
(e.g. with OGC WPS [52]: pyWPS, OpenLayers [53], ... ) (c.3)
Geospatial database support (e.g. scriptable data queries
with PostGIS [54] by using (b.3) [55], ... ) (c.4)
...
3

de Rigo, D., Corti, P., Caudullo, G., McInerney, D., Di Leo, M., San Miguel-Ayanz, J., 2013. Toward Open Science at the European
Scale: Geospatial Semantic Array Programming for Integrated Environmental Modelling. Geophys Res Abstr 15,13245+
geospatial
data (a) X
parameters θ
sub D-TM θ(X)
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(extended)
input data ⇒
Geo SemAP Geo
(c) (b) (c)
geospatial ⇒SemAP ⇒geospatial
pre D-TM D-TM post D-TM
geospatial SemAP geospatial
::pre:: ::pre:: ::post::
::inv::
::post::
| {z }
GeoSemAP D-TM block
⇒(extended)
output data
(d)
where
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data Data definition is extended to include proper geospatial data
(a), static parameters and sub D-TM – when used as
dynamic (e.g. data-dependent) parameters
sub D-TM Callback (function handle) to e.g. empirical equations,
regression families, metrics/distance functions, ...
::pre:: Semantic pre-conditions
::inv:: Semantic invariants
::post:: Semantic post-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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