Reusability of model components for environmental simulation – Case studies for integrated coastal zone management

Model constructs in environmental models are seldom reused beyond the project lifetime or in other modelling studies. A library of reusable model components could facilitate the maintenance of existing models and make the design of new models more efficient. Although component-based design is the common standard in software engineering and manufacturing few examples are yet found in environmental science. The multi-disciplinary project SPICOSA used a common, component-based simulation framework for environmental modelling, based on 18 case studies through Europe. The development of high-quality model components with potential for reuse turned out to be a challenge despite of the guidelines and tutorial examples provided. Well-designed components are of appropriate granularity, encapsulated, with a limited use of connectors and proper data handling. Ultimately, the success of a model library depends on a sufficient set of quality components with complementary functionalities, a framework for quality control, and support of the environmental modelling community.     

Design of a framework for modeling, integration and simulation of physiological models

Multiscale modeling and integration of physiological models carry challenges due to the complex nature of physiological processes. High coupling within and among scales present a significant challenge in constructing and integrating multiscale physiological models. In order to deal with such challenges in a systematic way, there is a significant need for an information technology framework together with related analytical and computational tools that will facilitate integration of models and simulations of complex biological systems. Physiological Model Simulation, Integration and Modeling Framework (Phy-SIM) is an information technology framework providing the tools to facilitate development, integration and simulation of integrated models of human physiology. Phy-SIM brings software level solutions to the challenges raised by the complex nature of physiological systems. The aim of Phy-SIM, and this paper is to lay some foundation with the new approaches such as information flow and modular representation of the physiological models. The ultimate goal is to enhance the development of both the models and the integration approaches of multiscale physiological processes and thus this paper focuses on the design approaches that would achieve such a goal.     

A generic framework for deriving process stoichiometry in environmental models

It has been recognized for many decades that the stoichiometry of biological reactions is important for linking ecological and biogeochemical processes. However, only during the past decade has the scientific community become aware that “biological stoichiometry” may also help bridge evolutionary biology and ecosystem ecology. This awareness led to increasing attention to biological process stoichiometry in ecology during the past decade. Despite this trend in ecological data analysis and interpretation, ecological models are still predominantly formulated without sufficient attention to process stoichiometry. To support scientists in formulating stoichiometry in process models based on elemental mass conservation, we transfer techniques from chemical process engineering to achieve the following objectives: (i) develop a generic mathematical framework to formulate and solve stoichiometric equations; (ii) facilitate the extension of currently used process stoichiometries to consider more elements (e.g. adding S and/or Si to C, H, O, N and P); (iii) identify the need for stoichiometric constraints of biogeochemical processes in addition to elemental mass balances; (iv) unify approaches to characterize organic matter by elemental mass fractions, organic carbon, or chemical oxygen demand; (v) provide a small package of functions for the statistics and graphics software R (http://www.r-project.org) to support environmental model building, and (vi) show how to incorporate automatic stoichiometric calculations into next generation environmental simulation software. The small R package “stoichcalc” can be downloaded from http://www.eawag.ch/^～reichert or from the package repository of the R project (http://www.r-project.org).     

Managing software process measurement: A metamodel-based approach

The evaluation of software processes is nowadays a very important issue due to the growing interest of software companies in the improvement of the productivity and quality of delivered products. Software measurement plays a fundamental role here. Given the great diversity of entities which are candidates for measurement in the software process improvement context (process models, projects, resources, products) this measurement must be performed in a consistent and integrated way. This will facilitate the making of decisions in process improvement. In this paper, a proposal for the integrated management of the software measurement is presented. The goal is to provide companies with a generic and flexible environment for software measurement which facilitates and establishes the basis for a common and effective measurement process and which is not restricted to only one kind of software entity or to a single quality or evaluation model. In order to achieve this, the proposal adopts the Model Driven Engineering philosophy and provides: a metamodel for the definition of software measurement models; a flexible method to measure any kind of software entity represented by its corresponding metamodel and GenMETRIC, which is the software tool that supports the framework.     

Asim: a performance model framework

The longevity and usefulness of a microprocessor performance model has historically depended on the model writer's skills and discipline. However, at Compaq the models became extremely complex and unmanageable because designers lacked a structured way to develop them. To cope with these complexities, Compaq researchers began developing Asim in late 1998 to allow model writers to faithfully represent the detailed timing of complex modern machines and effectively manage the large software projects needed to model such machines. Asim addresses these needs by providing a modular and reusable framework for creating many models. The framework's modularity helps break down the performance-modeling problem into individual pieces that can be modeled separately, while its reusability allows using a software component repeatedly in different contexts     

An investigation on the nature of decision support system software

Decision Support Systems (DSS) software is investigated and a conceptual model presented in this paper. The purpose of this model is to facilitate a better understanding of the nature of DSS software. The model is composed of six problem transformational processes linking up seven problem phases. The six transformational processes are: problem transforming system, problem mapping system, problem solving system, procedural program generation system, programming language compiling system, and code generation system, by identifying the seven problem phases this hierarchical provides a conceptual foundation for developing DSS software. Spun-off from this model is a framework for implementing knowledge-based DSS with automatic modeling capabilities. The structure of future DSS software to run on fifth generation computers is also addressed.     

基于SMDA的企业应用系统定制技术

针对中小企业业务流程不规范和变化差异大等特点,指出现有软件定制技术面临的挑战.在SOA和MDA基础上,提出服务模型驱动的架构(SMDA),阐述服务模型和服务模板的概念,设计基于SMDA的软件定制技术平台框架;描述服务抽象和服务模板构造过程,构造一种基于XML的服务模板标记语言,以描述和配置企业应用系统的基本信息需求和个性化定制需求,并通过具体实例展示SMDA架构在软件快速重构与定制中的有效性和实用性.     

Design techniques of a computer program for the identification of processes and the simulation of water quality in aquatic systems

In order to support environmental scientists in finding an “adequate” model for the system they are investigating, a computer program is necessary that allows its users to perform simulations for different models, to assess the identifiability and to estimate the values of model parameters (using measured data), and to estimate prediction uncertainty. These requirements, especially that of providing much freedom in model formulation, are difficult to realize in such a program. In this paper, it is shown how object-oriented program design techniques were employed to facilitate the realization of an identification and simulation program for aquatic systems (AQUASIM) that is very flexible with regard to model formulation and that provides methods of sensitivity analysis, parameter estimation and uncertainty analysis in addition to simulation. It is the goal of this paper to encourage developers of environmental software to revise previously used program structures and to employ modern program design techniques.     

Domain-Specific Modeling Languages to improve framework instantiation

Frameworks are reusable software composed of concrete and abstract classes that implement the functionality of a domain. Applications reuse frameworks to enhance quality and development efficiency. However, frameworks are hard to learn and reuse. Application developers must understand the complex class hierarchy of the framework to instantiate it properly. In this paper, we present an approach to build a Domain-Specific Modeling Language (DSML) of a framework and use it to facilitate framework reuse during application development. The DSML of a framework is built by identifying the features of this framework and the information required to instantiate them. Application generators transform models created with the DSML into application code, hiding framework complexities. In this paper, we illustrate the use of our approach in a framework for the domain of business resource transactions and a experiment that evaluated the efficiency obtained with our approach.     

Cost models for future software life cycle processes: COCOMO 2.0

Current software cost estimation models, such as the 1981 Constructive Cost Model (COCOMO) for software cost estimation and its 1987 Ada COCOMO update, have been experiencing increasing difficulties in estimating the costs of software developed to new life cycle processes and capabilities. These include non-sequential and rapid-development process models; reuse-driven approaches involving commercial off-the-shelf (COTS) packages, re-engineering, applications composition, and applications generation capabilities; object-oriented approaches supported by distributed middleware; and software process maturity initiatives. This paper summarizes research in deriving a baseline COCOMO 2.0 model tailored to these new forms of software development, including rationale for the model decisions. The major new modeling capabilities of COCOMO 2.0 are a tailorable family of software sizing models, involving Object Points, Function Points, and Source Lines of Code; nonlinear models for software reuse and re-engineering; an exponentdriver approach for modeling relative software diseconomies of scale; and several additions, deletions and updates to previous COCOMO effort-multiplier cost drivers. This model is serving as a framework for an extensive current data collection and analysis effort to further refine and calibrate the model's estimation capabilities.     

BirdVis: visualizing and understanding bird populations

Birds are unrivaled windows into biotic processes at all levels and are proven indicators of ecological well-being. Understanding the determinants of species distributions and their dynamics is an important aspect of ecology and is critical for conservation and management. Through crowdsourcing, since 2002, the eBird project has been collecting bird observation records. These observations, together with local-scale environmental covariates such as climate, habitat, and vegetation phenology have been a valuable resource for a global community of educators, land managers, ornithologists, and conservation biologists. By associating environmental inputs with observed patterns of bird occurrence, predictive models have been developed that provide a statistical framework to harness available data for predicting species distributions and making inferences about species-habitat associations. Understanding these models, however, is challenging because they require scientists to quantify and compare multiscale spatialtemporal patterns. A large series of coordinated or sequential plots must be generated, individually programmed, and manually composed for analysis. This hampers the exploration and is a barrier to making the cross-species comparisons that are essential for coordinating conservation and extracting important ecological information. To address these limitations, as part of a collaboration among computer scientists, statisticians, biologists and ornithologists, we have developed BirdVis, an interactive visualization system that supports the analysis of spatio-temporal bird distribution models. BirdVis leverages visualization techniques and uses them in a novel way to better assist users in the exploration of interdependencies among model parameters. Furthermore, the system allows for comparative visualization through coordinated views, providing an intuitive interface to identify relevant correlations and patterns. We justify our design decisions and present case studies that show how BirdVis has helped scientists obtain new evidence for existing hypotheses, as well as formulate new hypotheses in their domain.     

Reusing enterprise models to build platform independent computer models

Enterprises use enterprise models to represent and analyse their processes, products, decisions, organisation, information flows, etc. Nevertheless, the enterprise knowledge that exists in enterprise models is not used beyond these purposes. The main goal of this paper is to present a framework that allows enterprises to reuse enterprise models to build software. The framework includes these dimensions: (1) a methodology that guides the use of the other dimensions in the reutilisation of enterprise models in software generation; (2) a set of metamodels to represent enterprises at the Computation Independent Model (CIM) level; (3) a modelling guide to make enterprise models using the metamodels proposed in this paper; (4) an extraction algorithm to discriminate the part of the CIM model to reuse; and (5) a set of transformation rules to reuse enterprise models to build Platform Independent Models. In addition, a case example is shown to validate the work that was carried out and to identify limitations.     

Mapping malaria risk in West Africa using a Bayesian nonparametric non-stationary model

Malaria transmission is highly influenced by environmental and climatic conditions but their effects are often not linear. The climate-malaria relation is unlikely to be the same over large areas covered by different agro-ecological zones. Similarly, spatial correlation in malaria transmission arisen mainly due to spatially structured covariates (environmental and human made factors), could vary across the agro-ecological zones, introducing non-stationarity. Malaria prevalence data from West Africa extracted from the “Mapping Malaria Risk in Africa” database were analyzed to produce regional parasitaemia risk maps. A non-stationary geostatistical model was developed assuming that the underlying spatial process is a mixture of separate stationary processes within each zone. Non-linearity in the environmental effects was modeled by separate P-splines in each agro-ecological zone. The model allows smoothing at the borders between the zones. The P-splines approach has better predictive ability than categorizing the covariates as an alternative of modeling non-linearity. Model fit and prediction was handled within a Bayesian framework, using Markov chain Monte Carlo (MCMC) simulations.     

A framework for software process deployment and evaluation

ContextSoftware Process Engineering promotes the systematic production of software by following a set of well-defined technical and management processes. A comprehensive management of these processes involves the accomplishment of a number of activities such as model design, verification, validation, deployment and evaluation. However, the deployment and evaluation activities need more research efforts in order to achieve greater automation.ObjectiveWith the aim of minimizing the required time to adapt the tools at the beginning of each new project and reducing the complexity of the construction of mechanisms for automated evaluation, the Software Process Deployment & Evaluation Framework (SPDEF) has been elaborated and is described in this paper.MethodThe proposed framework is based on the application of well-known techniques in Software Engineering, such as Model Driven Engineering and Information Integration through Linked Open Data. It comprises a systematic method for the deployment and evaluation, a number of models and relationships between models, and some software tools.ResultsAutomated deployment of the OpenUP methodology is tested through the application of the SPDEF framework and support tools to enable the automated quality assessment of software development or maintenance projects.ConclusionsMaking use of the method and the software components developed in the context of the proposed framework, the alignment between the definition of the processes and the supporting tools is improved, while the existing complexity is reduced when it comes to automating the quality evaluation of software processes.     

Documenting,storing, and executing models in Ecology: A conceptual framework and real implementation in a global change monitoring program

Many of the best practices concerning the development of ecological models or analytic techniques published in the scientific literature are not fully available to modelers but rather are stored in scientists' digital or biological memories. We propose that it is time to address the problem of storing, documenting, and executing ecological models and analytical procedures. In this paper, we propose a conceptual framework to design and implement a web application that will help to meet this challenge. This tool will foster cooperation among scientists, enhancing the creation of relevant knowledge that could be transferred to environmental managers. We have implemented this conceptual framework in a tool called ModeleR. This is being used to document, share, and execute more than 200 models and analytical processes associated with a global change monitoring program that is being undertaken in the Sierra Nevada Mountains (south Spain). ModeleR uses the concept of scientific workflow to connect and execute different types of models and analytical processes. Finally, we have envisioned the creation of a federation of model repositories where models documented within a local repository could be linked and even executed by other researchers.     

A top-down framework for watershed model evaluation and selection under uncertainty

This study introduces a top-down strategy for model evaluation and selection under uncertainty in which watershed model structures with increasing complexity are applied to twelve watersheds across a hydro-climatic gradient within the United States (US). The models' complexities and their related assumptions provide an indication of the dominant controls on the watershed response at the inter-annual, intra-annual, monthly, and daily time scales as captured in the water balance signatures (or metrics) used in this study. The ability of the models to capture the water balance signatures is evaluated in an ensemble framework with respect to their reliability (Is the model ensemble capturing the observed signature?) and with their shape (Is the model structure capable of representing an observed signature's variability?). Model selection is automated by combining the reliability and shape performance measures in a fuzzy rule system. Our results suggest that the framework can be tuned to function as a screening tool that formalizes our model selection process. This fuzzy model selection framework enhances our ability to automatically select parsimonious model structures for large databases of watersheds and therefore provides an important step towards understanding how controls on the watershed response vary with landscape and climatic characteristics. This understanding further advances our ability for model-based watershed classification.     

基于模型的开发方法在多应用智能卡中的应用

安全性、可靠性是嵌入式软件的重要性质。为了更好地保证开发的嵌入式软件是可靠和安全的,提出了一种基于模型的开发方法学,包括提炼需求、建立抽象模型及逐层精化三个步骤。首先从环境、功能、性质三个主要方面提取需求,同时明确层次化的精化策略;然后利用形式化方法建立抽象模型并对该模型进行形式化验证,在正确的抽象模型上逐层精化,并对每层模型进行验证;最后,基于满足需求的模型,进一步利用工具完成代码自动生成。该方法从抽象到具体,以逐层递增的方式明确被开发系统的需求及性质,进行形式化建模,通过反馈机制确保模型的正确性及可用性。为了证明该方法学的可行性,文章以多应用智能卡为开发实例,基于Event—B方法及Rodin平台给出了实际建模及证明的过程和结果。     

基于有向图的定性模型分解方法

模型分解是减小系统复杂程度、降低仿真运行代价的有效手段，当前许多定性仿真理论，由于仿真代价过高等原因而难以处理大规模系统。针对这种状况，文中对定性理论中常见的因果关系有向图形式表示的结构模型，给出一种模型分解方法，通过实例给出了具体的分解并与定性理论中别的方法作了简要比较。     

Downscaling global information for regional benefit: coupling spatial models at varying space and time scales

Every environmental activity to a large extent is dependent on climate as natural processes are intrinsically linked with the waxing and waning of the seasons. The goal is to integrate global seasonal climate forecasts with local environmental decision support systems within an operational framework to deliver community benefits. This framework is designed to support the downscaling of coarse resolution seasonal forecasts to drive biological or hydrological applications at the regional level. Some of the challenges and complexities in coupling spatial simulations operating at varying spatial and temporal resolutions will be discussed from several viewpoints, illustrating the value of multidisciplinary collaboration in a virtual team and benefits from the globalisation of research. This project demonstrates how a state Government is evolving an existing service to enhance the use of seasonal climate forecasts for sustainable environmental and natural resource management.     

Selecting among five common modelling approaches for integrated environmental assessment and management

The design and implementation of effective environmental policies need to be informed by a holistic understanding of the system processes (biophysical, social and economic), their complex interactions, and how they respond to various changes. Models, integrating different system processes into a unified framework, are seen as useful tools to help analyse alternatives with stakeholders, assess their outcomes, and communicate results in a transparent way. This paper reviews five common approaches or model types that have the capacity to integrate knowledge by developing models that can accommodate multiple issues, values, scales and uncertainty considerations, as well as facilitate stakeholder engagement. The approaches considered are: systems dynamics, Bayesian networks, coupled component models, agent-based models and knowledge-based models (also referred to as expert systems). We start by discussing several considerations in model development, such as the purpose of model building, the availability of qualitative versus quantitative data for model specification, the level of spatio-temporal detail required, and treatment of uncertainty. These considerations and a review of applications are then used to develop a framework that aims to assist modellers and model users in the choice of an appropriate modelling approach for their integrated assessment applications and that enables more effective learning in interdisciplinary settings.