Conceptual Modeling Tool Research Articles

From specialized knowledge frames to linguistically based ontologies

This paper explains conceptual modeling within the framework of Frame-Based Terminology (Faber, 2012; 2015; 2022), as applied to EcoLexicon (ecolexicon.ugr.es), a specialized knowledge base on the environment (León-Araúz, Reimerink &, Faber, 2019; Faber & León-Araúz, 2021). It describes how a frame-based terminological resource is currently being restructured and reengineered as an initial step towards its formalization and subsequent transformation into an ontology. It also explains how the information in EcoLexicon can be integrated in environmental ontologies such as ENVO (Buttigieg, Morrison, Smith, Mungall & Lewis, 2013; Buttigieg, Pafilis, Lewis, Schildhauer, Walls & Mungall, 2016), particularly at the bottom tiers of the Ontology Learning Layer Cake (Cimiano, 2006; Cimiano, Maedche, Staab & Volker, 2009). The assumption is that frames, as a conceptual modeling tool, and information extracted from corpora can be used to represent the conceptual structure of a specialized domain.

An extended taxonomy of advanced information visualization and interaction in conceptual modeling

Conceptual modeling is integral to computer science research and is widely adopted in industrial practices, e.g., business process and enterprise architecture management. Providing adequate and usable modeling tools is necessary to adopt modeling languages efficiently. Meta-modeling platforms provide a rich and mature set of functionalities for realizing state-of-the-art modeling tools. These tools, albeit their stability and rich set of features, often lack a modern look and feel considering (i) how they visualize the models, and (ii) how modelers interact with the models. Current web technologies enable much richer, advanced opportunities for visualizing and interacting with conceptual models. However, a structured and comprehensive overview of possible information visualization and interaction techniques linked to conceptual models and modeling tools must be established. This paper aims to fill this gap by presenting an extended taxonomy of advanced information visualization and interaction in conceptual modeling. We present a generic taxonomy that is afterward contextualized within the specific domain of conceptual modeling. The taxonomy serves orientation in the vast developing field of information visualization and interaction and hopefully sparks innovation if future modeling tool development.

Effects of Pairing Methods Based on Digital Textbook Logs and Learner Artifacts in Conceptual Modeling Exercises

This paper describes the effects of a pairing method based on digital textbook logs and learners’ artifacts in conceptual modeling exercises. We developed a digital textbook system called Smart E-textbook Application (SEA) and a conceptual modeling tool called KIfU 3.0 to collect conceptual modeling activity logs in exercises. This study proposes a method that makes pairs of learners for group work by considering the characteristics of the artifacts created by them and digital textbook logs. An initial evaluation was conducted to evaluate the learning effects of our proposed pairing method compared to the random pairing method. From its results, this study found the discussion patterns and digital textbook browsing status in the maximum value of improvement and deterioration points of learners’ artifacts in the conceptual modeling.

Modeling Digital Business Ecosystems: A Systematic Literature Review

The changing business landscapes urge organizations to collaborate and combine their expertise to stay competitive. Organizations establish partnerships and collaborate via the Internet, which often happens dynamically and at fast pace resulting in formation of Digital Business Ecosystems (DBEs). DBEs are complex and their management requires having explicit and up-to-date information about them. Modeling enables thorough visual analysis and facilitates the understanding and formation of DBEs. It also allows viewing DBEs through multiple perspectives, as well as exploring alternatives in the course of DBE formation or management. This systematic review aims to synthesize existing studies pertaining to Conceptual Modeling for analysis, design, and management of DBEs. A total of 94 studies were included in the review. The findings suggest that there is a scarcity of existing Conceptual Modeling methods and tools supporting DBEs. Additionally, the extensive emphasis on DBEs’ actors in modeling leads to an urgent need for the methods to be extended to support the establishment of holistic views for integrating multiple perspectives of DBEs. Future research should focus on these areas to facilitate the transformation of how organization’s collaborations are viewed – from a single-organization to a multitude of viewpoints on organizational networks of collaboration, coexistence, and competition. Such models also need to support the key features of DBEs, such as resilience and automation.

HS‐IDEOR—A tool for conceptual modeling and designing of hardware architectures focused on object recognition

AbstractConsidering the increasing demand for object recognition systems, it is crucial that modern engineering courses include tools and methods to ensure that students acquire the theoretical and practical skills necessary to become specialists in designing such systems. This paper introduces a hardware‐software integrated development environment to support and accelerate the teaching/learning process of conceptual modeling and hardware architectures design focused on object recognition. In addition, our proposal facilitates the implementation of modular and hybrid object recognition schemes, offering great flexibility in the study of such systems. An empirical evaluation was conducted with 30 fourth‐year undergraduate students who designed and implemented an object recognition system in the Computer Vision course of the Bachelor's Degree in Computer Science and Engineering at the Universidad Tecnológica de la Mixteca, Mexico. The results achieved from designing, modeling, and implementing a hardware architecture of the convolution process applied to edge detection in an image provided evidence that this approach empowered students with a more dynamic learning process.

A Decision Support Tool For Water Pollution and Eutrophication Prevention In Groundwater-dependent Shallow Lakes From Periurban Areas Based On The DPSIR Framework.

The deterioration of water quality worldwide is a serious environmental problem. Water managers still need operational tools to assess water issues and to inform water planning and decision-making. The aim of this article is to propose a 3-step methodological framework for assessing water pollution problems by combining a conceptual modeling tool (DPSIR) with the development of a quantitative model (Multi-Criteria Decision Model). This contribution provides a practical and flexible evaluation tool for conducting an integrated assessment of eutrophication and agrochemicals delivered to groundwater-dependent shallow lakes. It lays out action guidelines for decision-making environmental managers within the context of intermediate cities in developing countries. Forty-one indicators were identified to characterize the D-P-S-I compartments and for the multi-criteria model conceptualization. In this work, response options analysis consisted of evaluating and choosing water management instruments via a decision support tool. Two lake watersheds located in the peri-urban of two middle-size cities, in Argentina, were chosen to illustrate this methodological approach. The ensuing results allowed establishing a ranking of areas to prioritize, identifying a criteria and sub-criteria to focus on in order to set out action guidelines to minimize water pollution and eutrophication. These action guidelines are urgently needed in emerging countries, where financial, human resources and infrastructure are limited. The scarcity of such causes important implications regarding policy solutions for environmental issues. The implemented decision support tool in both lake watersheds provided a common basis for the understanding of the ongoing water pollution problems and a quantitative ranking (i.e., decision scores) for defining specific actions (responses) for human-induced stresses on such natural systems.

Exploring the Use of Ecosystem Services Conceptual Models to Account for the Benefits of Public Lands: An Example from National Forest Planning in the United States

A shared understanding of the benefits and tradeoffs to people from alternative land management strategies is critical to successful decision-making for managing public lands and fostering shared stewardship. This study describes an approach for identifying and monitoring the types of resource benefits and tradeoffs considered in National Forest planning in the United States under the 2012 Planning Rule and demonstrates the use of tools for conceptualizing the production of ecosystem services and benefits from alternative land management strategies. Efforts to apply these tools through workshops and engagement exercises provide opportunities to explore and highlight measures, indicators, and data sources for characterizing benefits and tradeoffs in collaborative environments involving interdisciplinary planning teams. Conceptual modeling tools are applied to a case study examining the social and economic benefits of recreation on the Ashley National Forest. The case study illustrates how these types of tools facilitate dialog for planning teams to discuss alternatives and key ecosystem service outcomes, create easy to interpret visuals that map details in plans, and provide a basis for selecting ecosystem service (socio-economic) metrics. These metrics can be used to enhance environmental impact analysis, and help satisfy the goals of the National Environmental Policy Act (NEPA), the 2012 Planning Rule, and shared stewardship initiatives. The systematic consideration of ecosystem services outcomes and metrics supported by this approach enhanced dialog between members of the Forest planning team, allowed for a more transparent process in identification of key linkages and outcomes, and identified impacts and outcomes that may not have been apparent to the sociologist who is lacking the resource specific expertise of these participants. As a result, the use of the Ecosystem Service Conceptual Model (ESCM) process may result in reduced time for internal reviews and greater comprehension of anticipated outcomes and impacts of proposed management in the plan revision Environmental Impact Statement amongst the planning team.

Prototype Mechanisms for Supporting the Network of Links to Parameterized Data Objects

The paper considers methods to organize a network of links to parameterized data objects. A data object is an object identified by standard methods, including the network identifiers URI, URL and URN. The data objects can be either atomic or have a complex structure, including links to other objects, and this ensures the linking of objects into a network, which can be considered as an information graph. It turns out to be possible to formulate a number of criteria for supporting the integrity of such a structure; the paper proposes language tools to formulate such criteria.An essential feature of this network is the dependence of the objects’ information content on a number of parameters, first of all, on time. Depending on the parameter, the information content of the object can change both with the preservation of the integrity of the structure, and with its damage. The paper considers methods for a parameterized description of objects while maintaining integrity based on the formalism of category theory. The formalization used allows defining two relations between objects and their names (identifiers): access and links. The paper studies the basic properties of such relations and reveals the differences between them.Category theoretical means of describing objects require appropriate support tools for practical application. The paper proposes a configuration of support tools for a network of links to parameterized data objects based on a combination of conceptual modeling tools and applicative computing tools. The proposed tools provide basic methods of access to the network of information graphs. An essential feature of the proposed tools is the ability to determine the subjective way of considering the information graph (based on the category of correlations), as well as harmonizing an objective and subjective way of considering. The proposed tools were tested in the development of applied information systems in the field of implementation of the best available technologies (BAT).

PENERAPAN TEORI KEPUTUSAN DALAM MODEL PENGAMBILAN KEPUTUSAN TERKAIT MASALAH EKONOMI PERTAHANAN

The shift in global paradigm and threat perspective has led to a wide variety of possible risks and uncertainties. This situation also occurs in the defense economy, so understanding the basic principles of risk and uncertainty is important, especially in a decision-making process. There are several elements and concepts that are usually used in all decision models. Almost all models, whether complex or simple, can be formulated using a standard structure and solved by using general evaluation procedures. For decisions involving a series of decisions and relating to various basic sequential conditions, the decision tree is an appropriate conceptual and schematic modeling tool. A decision tree is a schematic representation of a decision problem. A decision tree is a diagram made like a tree with branches and branches in a chronological order of events, with each having a choice and possibility of occurrence, as well as the results of each choice. The term decision tree is taken from the form of diagrams that have branches and twigs, just like a tree.

Design and Implementation of Active Stream Data Warehouses

In the era of Big Data, more and more stream data is available. In the same way, Decision Support Systems (DSS) tools, such as data warehouses and alert systems, become more and more sophisticated, and conceptual modeling tools are consequently mandatory for successfully DSS projects. Formalisms such as UML and ER have been widely used in the context of classical information and data warehouse systems, but they have not been investigated yet for stream data warehouses to deal with alert systems. Therefore, in this article, the authors introduce the notion of Active Stream Data Warehouse (ASDW) and this article proposes a UML profile for designing Active Stream Data Warehouses. Indeed, this article extends the ICSOLAP profile to take into account continuous and window OLAP queries. Moreover, this article studies the duality of the stream and OLAP decision-making process and the authors propose a set of ECA rules to automatically trigger OLAP operators. The UML profile is implemented in a new OLAP architecture, and it is validated using an environmental case study concerning the wind monitoring.

An introductory guide for hybrid simulation modelers on the primary simulation methods in industrial engineering identified through a systematic review of the literature

Abstract Modeling and simulation are a powerful and effective problem-solving methodology to study how complex real-world systems behave over time. In the literature, many authors have indicated that discrete event simulation, agent-based simulation, and system dynamics are the primary and most important simulation techniques to aid industrial engineers in making decisions. Given this context, this paper is expected to be an introductory guide, especially for novice simulation modelers willing to work with hybrid simulation, by providing knowledge and insight about the primary simulation methods in industrial engineering. This paper is expected to support the decision about which simulation technique best suits the system being studied. For that, a systematic literature review was conducted based on pre-defined search criteria. After applying the filters and including some relevant papers published in the field, a total of 145 papers were selected. Some of the analysis performed in this study include, for each simulation method, the number of publications over the years and a list of the top 10 sources, countries, and authors according to the number of publications. Besides that, a brief history is provided and the definition of the three primary techniques is discussed, as well as the main characteristics of each technique, such as modeling steps, elements, conceptual modeling tools used, software, inputs and outputs, programming languages, advantages, disadvantages, and application areas. Simulation modelers can use this paper as a quick reference to the primary simulation techniques in order to identify the best tool for a specific simulation project in the field of industrial engineering and related areas.

Ocean futures: Exploring stakeholders' perceptions of adaptive capacity to changing marine environments in Northern Norway

Globally, the projected increase in sea surface temperature is expected to facilitate large changes in the marine food web, affect coastal communities, marine ecosystem goods and services, global fisheries, tourism, aquaculture and others. This ongoing change takes place on different time scales, and coincides with increasing global demand for seafood, a growing middle class, and expectations of future need for food security from the marine sector. This article contributes to advances in climate change research by exploring, within the context of the results of the viewExposed program for assessing Integrated Vulnerabilities in different municipalities in Norway, to what extent stakeholders in different industries are willing to accept, or expect to be able to adapt to, these new realities. This was investigated through stakeholder driven workshops with stakeholders from maritime industries, commercial fisheries, tourism and aquaculture in Norway using the conceptual modeling tools of systems thinking and Bayesian Belief Networks. Results showed that commercial fishers are worried about quota allocations with changes in fish distribution. The aquaculture industry was worried about allocations of new areas for industry expansion in contested areas in Northern Norway, and the tourism industry was worried about changes in communications (transport) in light of a changing climate. Only the commercial fishers perceived that their adaptive capacity was low in light of these changes, especially the small-scale coastal fishers. This was because they expected the combination between increased power of the aquaculture industry and new species requiring expensive quotas would be too critical.

Vulnerability assessment of water resources – Translating a theoretical concept to an operational framework using systems thinking approach in a changing climate: Case study in Ogallala Aquifer

Water is an essential natural resource. Among many stressors, altered climate is exerting pressure on water resource systems, increasing its demand and creating a need for vulnerability assessments. The overall objective of this study was to develop a novel tool that can translate a theoretical concept (vulnerability of water resources (VWR)) to an operational framework mainly under altered temperature and precipitation, as well as for population change (smaller extent). The developed tool had three stages and utilized a novel systems thinking approach. Stage-1: Translating theoretical concept to characteristics identified from studies; Stage-2: Operationalizing characteristics to methodology in VWR; Stage-3: Utilizing the methodology for development of a conceptual modeling tool for VWR: WR-VISTA (Water Resource Vulnerability assessment conceptual model using Indicators selected by System’s Thinking Approach). The specific novelties were: 1) The important characteristics in VWR were identified in Stage-1 (target system, system components, scale, level of detail, data source, frameworks, and indicator); 2) WR-VISTA combined two vulnerability assessments frameworks: the European’s Driver–Pressure–State–Impact–Response framework (DPSIR) and the Intergovernmental Panel on Climate Change’s framework (IPCC’s); and 3) used systems thinking approaches in VWR for indicator selection. The developed application was demonstrated in Kansas (overlying the High Plains region/Ogallala Aquifer, considered the “breadbasket of the world”), using 26 indicators with intermediate level of detail. Our results indicate that the western part of the state is vulnerable from agricultural water use and the eastern part from urban water use. The developed tool can be easily replicated to other regions within and outside the US.

Detection of land use/cover change effect on watershed’s response in generating runoff using computational intelligence approaches

Quantifying the potential impacts of changing land use/cover in watersheds especially via the rainfall-runoff modeling remains among the more challenging problems in hydrology. This study presents a new method in detection, quantification and prediction of long term land use/cover change of the South Fork Eel River watershed, based on linear conceptual rainfall-runoff modeling and computational intelligence tools. The methodology was presented via a two-phase modeling procedure: event-based and continuous-based modeling phases. In the first phase, a linear conceptual rainfall-runoff model was proposed based on unequal cascade of reservoirs in which the drainage basin was divided into several sub-basins in a sequence based on the stream gauge locations and drainage network. This model includes two parameters of linear reservoir and channel lag times which were computed using relations based on the watershed’s geomorphology. The parameters were calibrated using observed rainfall-runoff events via genetic algorithm. In the second phase, calibrated lag times of events during each month were averaged to produce monthly time series of lag time to be used for training of classic artificial neural network and hybrid Wavelet-ANN for prediction of land use/cover change effect on the watershed’s response in generating runoff. Results indicate the good capability of such two-phase modeling procedure in quantification and prediction of land use change effects on hydrological response of the watershed. Results show, autoregressive and seasonal patterns of lag time, evapotranspiration and temperature are the most important factors which could affect rainfall-runoff modeling of the watershed. The land use change effect results show a slight improvement in the vegetation cover during long period for the South Fork Eel River watershed.

Conceptual independence: A design principle for the construction of adaptive information systems

This paper examines the problem of conceptual dependence, the coupling of software applications׳ internal structures and logic with their underlying conceptual models. Although conceptual dependence is almost universal in information system design, it produces a range of unintended negative consequences including system inflexibility and increased maintenance costs. Many information systems contain components, such as database tables and classes, whose design reflects the entity types and relationships in underlying, domain-oriented conceptual models. When the models change, work is involved in altering the software components. For example, an e-commerce system might include tables and classes representing product types, customers and orders, with associated code in methods, stored procedures and other scripts. The structure of the entity types and their relationships will be implicit in the tables, classes and code, coupling the system to its conceptual model. Any change to the model (such as the introduction of a new entity type, representing order lines) invalidates existing structures and code, causing rework. In large systems, this rework can be time-consuming and expensive. Research shows that schema change is common, and that it contributes significantly to the high cost of software maintenance. We argue that much of the cost may be avoidable if alternative design strategies are used. The paper describes an alternative design approach based on the principle of conceptual independence, which can be used to produce adaptive information systems (AIS). It decouples the internal structures and logic of information systems from the domain-specific entity types and relationships in the conceptual models they implement. An architecture for AIS is presented which includes soft schemas (conceptual models stored as data), an end-user conceptual modelling tool, a set of archetypal categories (predefined semantic categories), and an adaptive data model which allows data to be stored without conceptual dependence. The archetypal categories allow domain-specific run time behaviour to be provided, despite the absence of domain-specific software structure and logic. An advantage of AIS over conventionally-designed applications is that each AIS can be used in a wide variety of domains. AIS offer the prospect of significantly reduced maintenance costs, as well as increased scope for the development and modification of systems by end users. Work to date on implementation of the AIS architecture is discussed, and an agenda for future research is outlined including development and evaluation of a fully-featured AIS. The paper discusses challenges to be overcome and barriers to adoption.

Model-driven engineering applied to crop modeling

At the crossroads of two disciplines, Computer Science and Agronomy, we propose the use of Model-Driven Engineering which has the potential to be the future of software engineering. This work was initiated to tackle issues met by the ITK Company in developing and designing new crop models for decision support systems. We aim in the long-run at a full-fledge crop modeling and simulation environment. The metamodel and graphical concrete syntax designed are overcoming the lack of formal tool for conceptual modeling. The presented prototype permits to improve ITK production process through the use of code generation techniques and the feedback of its industrial use is given.

Developing statistical modelers and thinkers in an introductory, tertiary-level statistics course

While models are an important concept in statistics, few introductory statistics courses at the tertiary level put models at the core of the curriculum. This paper reports on a radically different approach to teaching statistics at the tertiary level, one that uses models and simulation as the organizing theme of the course. The focus on modeling and simulation—along with inference—was facilitated by having students use TinkerPlots™ software for all modeling and analysis. Results from a 3-month teaching experiment suggest that a course focused on modeling and simulation through randomization and resampling methods in which students learn to think using a powerful and conceptual modeling tool can foster ways of thinking statistically. Furthermore, such an approach seems to help students develop experiences with and appreciation for the science and practice of statistics.

StellaR: A software to translate Stella models into R open-source environment

Stella is a popular system dynamics modeling tool, which helps to put together conceptual diagrams and converts them into numeric computer models. Although it can be very useful, especially in participatory modeling, it lacks the power and flexibility of a programming language. This paper presents the StellaR software which translates a Stella model into a model in R, an open source high level programming language. This allows using conceptual modeling tools provided in Stella, together with computational functionality and programming flexibility provided in R. It also opens access to powerful software libraries available in R, which is especially useful for spatial modeling.

The Innovation Value Chain in New Technology‐Based Firms: Evidence from theU.K.

Innovation is central to the survival and growth of firms, and ultimately to the health of the economies of which they are part. A clear understanding both of the processes by which firms perform innovation and the benefits which flow from innovation in terms of productivity and growth is therefore essential. This paper demonstrates the use of a conceptual framework and modeling tool, the innovation value chain (IVC), and shows how theIVCapproach helps to highlight strengths and weaknesses in the innovation performance of a key group of firms—new technology‐based firms. The value of theIVCis demonstrated in showing the key interrelationships in the whole process of innovation from sourcing knowledge through product and process innovation to performance in terms of the growth and productivity outcomes of different types of innovation. The use of theIVChighlights key complementarities, such as that between internalR&D, externalR&D, and other external sources of knowledge. Other important relationships are also highlighted. Skill resources matter throughout theIVC, being positively associated with external knowledge linkages and innovation success, and also having a direct influence on growth independent of the effect on innovation. A key benefit of theIVCapproach is therefore its ability to highlight the roles of different factors at various stages of the knowledge–innovation–performance nexus, and to show their indirect as well as direct impact. This in turn permits both managerial and policy implications to be drawn.

Towards computer-aided multiscale modelling: A generic supporting environment for model realization and execution

Computer-aided multiscale modelling (CAMM) may be carried out in three consecutive stages, namely conceptual modelling, model realization, and model execution. Following earlier work on a conceptual modelling tool which aims to support the first stage of CAMM, prototypical tools for realizing conceptual models and for the execution of simulation are developed in this work, with the assumption that a multiscale simulation is to be carried out by means of integrating existing single-scale models. More specifically, the tool that supports model realisation helps modellers generate information required for executing the multiscale model. The model execution stage is in turn supported by a component-based simulation environment. Two different multiscale simulation modes, namely “coordinator driven” and “master tool driven”, are identified and supported separately. Details of the design and implementation of these tools are provided. Two reactor modelling examples are used to validate these tools and to demonstrate their application.