{"data":{"id":"10.6084/m9.figshare.842695.v4","type":"dois","attributes":{"doi":"10.6084/m9.figshare.842695.v4","prefix":"10.6084","suffix":"m9.figshare.842695.v4","identifiers":[],"alternateIdentifiers":[],"creators":[{"name":"Rigo, Daniele De","nameType":"Personal","givenName":"Daniele De","familyName":"Rigo","affiliation":[],"nameIdentifiers":[{"schemeUri":"https://orcid.org","nameIdentifier":"https://orcid.org/0000-0003-0863-2670","nameIdentifierScheme":"ORCID"}]}],"titles":[{"title":"Modular Data-Transformation Modelling with Geospatial Semantic Array Programming"}],"publisher":"figshare","container":{},"publicationYear":2013,"subjects":[{"subject":"Statistics"},{"subject":"FOS: Mathematics","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Mathematics","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Science Policy"},{"subject":"Applied Computer Science"},{"subject":"Environmental Science"},{"subject":"80309 Software Engineering","subjectScheme":"FOR"},{"subject":"FOS: Computer and information sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Computer and information sciences","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Ecology"},{"subject":"FOS: Biological sciences","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Biological sciences","subjectScheme":"Fields of Science and Technology (FOS)"}],"contributors":[],"dates":[{"date":"2013-12-06","dateType":"Created"},{"date":"2016-01-18","dateType":"Updated"},{"date":"2013","dateType":"Issued"}],"language":null,"types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceType":"Dataset","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[{"relationType":"IsPreviousVersionOf","relatedIdentifier":"10.6084/m9.figshare.842695","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":["3992098 Bytes"],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"de Rigo, D., \u003cstrong\u003eModular Data-Transformation Modelling with Geospatial Semantic Array Programming\u003c/strong\u003e. FigShare Digital Science. DOI: 10.6084/m9.figshare.842695 \u003cstrong\u003eModular Data-Transformation Modelling with Geospatial Semantic Array Programming\u003c/strong\u003e Daniele de Rigo \u003cstrong\u003eSummary.\u003c/strong\u003e Wide-scale transdisciplinary modelling for environment (WSTMe) is a scientific challenge with an increasingly important role in allowing strategic policy-making to be effectively discussed and programmed with the support of robust science [1]. Natural resources such as forests, water and soil, along with climate and human-driven changes, are subject to a network of interactions, whose large scale effects may be significant. WSTMe raises challenging issues when the characteristic heterogeneity of available geospatial information, complexity of systems and multiple sources of uncertainty (including those related to scientific software [2]) may affect the robustness, transparency and comprehensibility of hypotheses and results. In this respect, earth observation and computational science [3,4] are intrinsically linked and expected to deal with such a modular array of transdisciplinary aspects while preserving as much as possible conciseness and a terse semantics [5]. This is desirable in order to better communicate key messages and issues, both among different scientific communities and at the science-policy interface. Geospatial Semantic Array Programming (GeoSemAP) is a new approach [6] for WSTMe that has recently emerged in which a concise integration is introduced among semantics, geospatial tools and the array of data-transformation models (D-TM). WSTMe may often be described as a composition of D‑TMs where the flow of initial and derived/intermediate geo‑data highlights its array-based modular structure and semantics. Transparency (even due to the open science approach) is also a goal, to aid society in clearly understanding and controlling the implications of the technical apparatus on collective environmental decision-making [1–6]. \u003cstrong\u003eCaption of the image\u003c/strong\u003e. Wide-scale transdisciplinary modelling for environment (WSTMe) may often be described as a composition of data-transformation models (D‑TM) where the flow of initial and derived/intermediate geo‑data highlights its array-based modular structure and semantics (Geospatial Semantic Array Programming, GeoSemAP). Sources: [2,6]. \u003cstrong\u003eReferences\u003c/strong\u003e [1] van der Sluijs, J. P., 2005. Uncertainty as a Monster in the Science-Policy Interface: Four Coping Strategies. \u003cem\u003eWater Science \u0026amp; Technology 52\u003c/em\u003e (6), 87-92. http://scholar.google.com/scholar?cluster=3385318353116653032 [2] de Rigo, D., 2013. Software Uncertainty in Integrated Environmental Modelling: the role of Semantics and Open Science. \u003cem\u003eGeophysical Research Abstracts 15\u003c/em\u003e, 13292+. http://scholar.google.com/scholar?cluster=13790404181931852043 [3] Peng, R. D., 2011. Reproducible Research in Computational Science. \u003cem\u003eScience 334\u003c/em\u003e (6060), 1226-1227. http://scholar.google.com/scholar?cluster=905554772905069177 [4] Morin, A., Urban, J., Adams, P. D., Foster, I., Sali, A., Baker, D., Sliz, P., 2012. Shining Light into Black Boxes. \u003cem\u003eScience 336\u003c/em\u003e (6078), 159-160. http://scholar.google.com/scholar?cluster=12575758499484368256 [5] de Rigo, D., 2012. Semantic Array Programming for Environmental Modelling: Application of the Mastrave Library. In: Seppelt, R., Voinov, A. A., Lange, S., Bankamp, D. (Eds.), \u003cem\u003eInternational Environmental Modelling and Software Society (iEMSs) 2012 International Congress on Environmental Modelling and Software. Managing Resources of a Limited Planet: Pathways and Visions under Uncertainty, Sixth Biennial Meeting\u003c/em\u003e. pp. 1167-1176. http://scholar.google.com/scholar?cluster=6628751141895151391 [6] 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. \u003cem\u003eGeophysical Research Abstracts 15\u003c/em\u003e, 13245+. http://scholar.google.com/scholar?cluster=17118262245556811911","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"xml":"<?xml version="1.0" encoding="UTF-8"?>
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    <title>Modular Data-Transformation Modelling with Geospatial Semantic Array Programming</title>
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    <description descriptionType="Abstract">&lt;p&gt;de Rigo, D., &lt;strong&gt;Modular Data-Transformation Modelling with Geospatial Semantic Array Programming&lt;/strong&gt;. FigShare Digital Science. DOI: 10.6084/m9.figshare.842695&lt;/p&gt;
&lt;p&gt; &lt;/p&gt;
&lt;p&gt;&lt;strong&gt;Modular Data-Transformation Modelling with Geospatial Semantic Array Programming&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt; &lt;/p&gt;
&lt;p&gt;Daniele de Rigo&lt;/p&gt;
&lt;p&gt; &lt;/p&gt;
&lt;p&gt;&lt;strong&gt;Summary.&lt;/strong&gt; Wide-scale transdisciplinary modelling for environment (WSTMe) is a scientific challenge with an increasingly important role in allowing strategic policy-making to be effectively discussed and programmed with the support of robust science [1]. Natural resources such as forests, water and soil, along with climate and human-driven changes, are subject to a network of interactions, whose large scale effects may be significant.&lt;/p&gt;
&lt;p&gt;WSTMe raises challenging issues when the characteristic heterogeneity of available geospatial information, complexity of systems and multiple sources of uncertainty (including those related to scientific software [2]) may affect the robustness, transparency and comprehensibility of hypotheses and results. In this respect, earth observation and computational science [3,4] are intrinsically linked and expected to deal with such a modular array of transdisciplinary aspects while preserving as much as possible conciseness and a terse semantics [5]. This is desirable in order to better communicate key messages and issues, both among different scientific communities and at the science-policy interface.&lt;/p&gt;
&lt;p&gt;Geospatial Semantic Array Programming (GeoSemAP) is a new approach [6] for WSTMe that has recently emerged in which a concise integration is introduced among semantics, geospatial tools and the array of data-transformation models (D-TM). WSTMe may often be described as a composition of D‑TMs where the flow of initial and derived/intermediate geo‑data highlights its array-based modular structure and semantics. Transparency (even due to the open science approach) is also a goal, to aid society in clearly understanding and controlling the implications of the technical apparatus on collective environmental decision-making [1–6].&lt;/p&gt;
&lt;p&gt; &lt;/p&gt;
&lt;p&gt;&lt;strong&gt;Caption of the image&lt;/strong&gt;. Wide-scale transdisciplinary modelling for environment (WSTMe) may often be described as a composition of data-transformation models (D‑TM) where the flow of initial and derived/intermediate geo‑data highlights its array-based modular structure and semantics (Geospatial Semantic Array Programming, GeoSemAP). Sources: [2,6].&lt;/p&gt;
&lt;p&gt; &lt;/p&gt;
&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;[1] van der Sluijs, J. P., 2005. Uncertainty as a Monster in the Science-Policy Interface: Four Coping Strategies. &lt;em&gt;Water Science &amp; Technology 52&lt;/em&gt; (6), 87-92. http://scholar.google.com/scholar?cluster=3385318353116653032&lt;/p&gt;
&lt;p&gt;[2] de Rigo, D., 2013. Software Uncertainty in Integrated Environmental Modelling: the role of Semantics and Open Science. &lt;em&gt;Geophysical Research Abstracts 15&lt;/em&gt;, 13292+. http://scholar.google.com/scholar?cluster=13790404181931852043&lt;/p&gt;
&lt;p&gt;[3] Peng, R. D., 2011. Reproducible Research in Computational Science. &lt;em&gt;Science 334&lt;/em&gt; (6060), 1226-1227. http://scholar.google.com/scholar?cluster=905554772905069177&lt;/p&gt;
&lt;p&gt;[4] Morin, A., Urban, J., Adams, P. D., Foster, I., Sali, A., Baker, D., Sliz, P., 2012. Shining Light into Black Boxes. &lt;em&gt;Science 336&lt;/em&gt; (6078), 159-160. http://scholar.google.com/scholar?cluster=12575758499484368256&lt;/p&gt;
&lt;p&gt;[5] de Rigo, D., 2012. Semantic Array Programming for Environmental Modelling: Application of the Mastrave Library. In: Seppelt, R., Voinov, A. A., Lange, S., Bankamp, D. (Eds.), &lt;em&gt;International Environmental Modelling and Software Society (iEMSs) 2012 International Congress on Environmental Modelling and Software. Managing Resources of a Limited Planet: Pathways and Visions under Uncertainty, Sixth Biennial Meeting&lt;/em&gt;. pp. 1167-1176. http://scholar.google.com/scholar?cluster=6628751141895151391&lt;/p&gt;
&lt;p&gt;[6] 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. &lt;em&gt;Geophysical Research Abstracts 15&lt;/em&gt;, 13245+. http://scholar.google.com/scholar?cluster=17118262245556811911&lt;/p&gt;</description>
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