Modular Data-Transformation Modelling with Geospatial Semantic Array Programming

de Rigo, D., <strong>Modular Data-Transformation Modelling with Geospatial Semantic Array Programming</strong>. FigShare Digital Science. DOI: 10.6084/m9.figshare.842695 <strong>Modular Data-Transformation Modelling with Geospatial Semantic Array Programming</strong> Daniele de Rigo <strong>Summary.</strong> 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]. <strong>Caption of the image</strong>. 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]. <strong>References</strong> [1] van der Sluijs, J. P., 2005. Uncertainty as a Monster in the Science-Policy Interface: Four Coping Strategies. <em>Water Science &amp; Technology 52</em> (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. <em>Geophysical Research Abstracts 15</em>, 13292+. http://scholar.google.com/scholar?cluster=13790404181931852043 [3] Peng, R. D., 2011. Reproducible Research in Computational Science. <em>Science 334</em> (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. <em>Science 336</em> (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.), <em>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</em>. 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. <em>Geophysical Research Abstracts 15</em>, 13245+. http://scholar.google.com/scholar?cluster=17118262245556811911德·里戈（de Rigo, D.），《模块化数据转换建模与地理空间语义数组编程（Modular Data-Transformation Modelling with Geospatial Semantic Array Programming）》，发布于FigShare数字科学平台，DOI：10.6084/m9.figshare.842695。 # 模块化数据转换建模与地理空间语义数组编程 达尼埃莱·德·里戈（Daniele de Rigo） 【摘要】 大范围环境跨学科建模（Wide-scale transdisciplinary modelling for environment, WSTMe）是一项科学挑战，其在依托稳健科学支撑开展战略政策讨论与规划的进程中，重要性与日俱增[1]。森林、水、土壤等自然资源，连同气候与人为驱动的变化，构成了一张相互作用的网络，其大范围影响不容忽视。当可用地理空间信息存在固有异质性、系统复杂度较高且存在多源不确定性（包括与科学软件相关的不确定性[2]）时，WSTMe会面临诸多挑战性问题，这些因素可能会损害假设与结果的稳健性、透明度及可理解性。 在此背景下，地球观测与计算科学[3,4]具有内在关联性，需应对这类跨学科维度的模块化组合，同时尽可能保持表述简洁与语义严谨[5]。这一目标对于在不同科学共同体之间以及科学-政策界面之间更好地传递核心信息与关键问题而言至关重要。 地理空间语义数组编程（Geospatial Semantic Array Programming, GeoSemAP）是一种面向WSTMe的新兴方法[6]，该方法实现了语义、地理空间工具与数据转换模型（data-transformation models, D-TM）数组的简洁集成。WSTMe通常可被描述为数据转换模型的组合，初始数据与衍生/中间地理数据的流动凸显了其基于数组的模块化结构与语义。透明度（得益于开放科学理念）同样是核心目标，旨在助力社会清晰理解并把控技术工具对集体环境决策的影响[1–6]。 【图像说明】 大范围环境跨学科建模（WSTMe）通常可被描述为数据转换模型（D-TM）的组合，初始数据与衍生/中间地理数据的流动凸显了其基于数组的模块化结构与语义（地理空间语义数组编程，GeoSemAP）。来源：[2,6]。 【参考文献】 [1] van der Sluijs, J. P., 2005. 科学-政策界面中的不确定性难题：四种应对策略。《水科学与技术（Water Science & Technology）》52卷(6)，第87-92页。http://scholar.google.com/scholar?cluster=3385318353116653032 [2] de Rigo, D., 2013. 综合环境建模中的软件不确定性：语义与开放科学的作用。《地球物理研究摘要（Geophysical Research Abstracts）》15卷，第13292+页。http://scholar.google.com/scholar?cluster=13790404181931852043 [3] Peng, R. D., 2011. 计算科学中的可重复研究。《科学（Science）》334卷(6060)，第1226-1227页。http://scholar.google.com/scholar?cluster=905554772905069177 [4] Morin, A., Urban, J., Adams, P. D., Foster, I., Sali, A., Baker, D., Sliz, P., 2012. 揭开黑箱的面纱。《科学（Science）》336卷(6078)，第159-160页。http://scholar.google.com/scholar?cluster=12575758499484368256 [5] de Rigo, D., 2012. 环境建模中的语义数组编程：Mastrave库的应用。收录于：Seppelt, R., Voinov, A. A., Lange, S., Bankamp, D. (编)，《国际环境建模与软件学会（International Environmental Modelling and Software Society, iEMSs）2012年国际环境建模与软件大会：管理有限星球的资源：不确定性下的路径与愿景，第六届双年会》，第1167-1176页。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. 迈向欧洲尺度的开放科学：面向综合环境建模的地理空间语义数组编程。《地球物理研究摘要（Geophysical Research Abstracts）》15卷，第13245+页。http://scholar.google.com/scholar?cluster=17118262245556811911