Central Artifacts Research Articles

Limiting money: redesigning the artifact that shapes modern people

AbstractThe transdisciplinary argument in this article is that the social and ecological unsustainability of modern, globalized capitalism ultimately derives from the design of its central artifact: what Polanyi called all- or general-purpose money. The notion of a singular measure of economic value is a peculiar cultural conception that is inherently at odds with physical reality, yet it pervades modern economic thought and practice as if it were immutable. To transcend the political impasse of economic globalization, a complementary national currency (CC) exclusively for local use could distinguish a sphere of exchange and special-purpose currency for basic needs from a global sphere of more remote exchange-values. To avoid the pitfalls and failures of earlier experiments with local currencies, such a CC would require the support of national authorities, the specified objective of sustainable consumption and production, and systematic efforts to provide citizens and entrepreneurs with ample incentives to utilize it. In combining the concept of a CC with that of a universal basic income (UBI), the reform would allow their advantages to complement each other, joining the generalized scale of UBI with the potential of politically influencing consumption patterns that is inherent in CC. An essential difference in relation to earlier experiments would be that the reach of the CC would not be defined in terms of the geographical location of retailers but in terms of the derivation, relative to the consumer, of the products and services into which it could be converted. Although no such system yet exists, this should not stop us from imagining its possibilities.

Phenopacket-tools: Building and validating GA4GH Phenopackets.

The Global Alliance for Genomics and Health (GA4GH) is a standards-setting organization that is developing a suite of coordinated standards for genomics. The GA4GH Phenopacket Schema is a standard for sharing disease and phenotype information that characterizes an individual person or biosample. The Phenopacket Schema is flexible and can represent clinical data for any kind of human disease including rare disease, complex disease, and cancer. It also allows consortia or databases to apply additional constraints to ensure uniform data collection for specific goals. We present phenopacket-tools, an open-source Java library and command-line application for construction, conversion, and validation of phenopackets. Phenopacket-tools simplifies construction of phenopackets by providing concise builders, programmatic shortcuts, and predefined building blocks (ontology classes) for concepts such as anatomical organs, age of onset, biospecimen type, and clinical modifiers. Phenopacket-tools can be used to validate the syntax and semantics of phenopackets as well as to assess adherence to additional user-defined requirements. The documentation includes examples showing how to use the Java library and the command-line tool to create and validate phenopackets. We demonstrate how to create, convert, and validate phenopackets using the library or the command-line application. Source code, API documentation, comprehensive user guide and a tutorial can be found at https://github.com/phenopackets/phenopacket-tools. The library can be installed from the public Maven Central artifact repository and the application is available as a standalone archive. The phenopacket-tools library helps developers implement and standardize the collection and exchange of phenotypic and other clinical data for use in phenotype-driven genomic diagnostics, translational research, and precision medicine applications.

МЕЖДИСЦИПЛИНАРНАЯ ВЫСТАВКА «ДРЕВНЕЕ ЛУКОМОРЬЕ» В МУЗЕЕ ГЕОЛОГИИ, НЕФТИ И ГАЗА ГОРОДА ХАНТЫ-МАНСИЙСКА

The interdisciplinary exhibition “Ancient Lukomorye” opened at the Khanty-Mansiysk Museum of Geology, Oil and Gas in 2021. Its concept presupposes a multi-faceted understanding of “Lukomorye” in different areas of study and in the arts. The key model is supplied by a complex of coastal geo-ecosystems of the paleogenic epicontinental sea basin on the territories of Volga Region and Western Siberia, structured, like a mosaic, by a multitude of straits and archipelagos, and populated in subtropical conditions by a diverse community of organisms. The factual basis of the exposition is provided by the vast collection of Volga Region’s Paleocene deposits, assembled by the scientific-educational expedition “The Flotilla of Floating Universities.” The central artifact of the exhibition is a vertically-oriented, over six meters tall fossilized tree trunk with elements of a root system.

Requirement Design for Software Configuration and System Modeling

Software Configuration Management (SCM) aims to control the development of complex software systems. Traditional SCM systems treat text files as central artifacts, so they are mainly developed for source code. Such a system is not suitable for model-based software development with model-centric artifacts. When applying traditional systems to model-based software development, new challenges such as model mapping, differentiation, and merging arise. Many existing methods mainly use UML or domain-specific languages to determine model differences. However, as far as we know, there is no such technology for System Modeling Language (SysML) models. SysML covers the entire development life cycle of various complex systems, covering information, processes, hardware and software. SysML contains nine types of diagrams for system modeling. One of them is the SysML requirement diagram, which is used to capture the functional requirements of the system. We propose a differentiation method for the SysML demand model. We recommend to create a SysML requirement model in the CASE tool first, and then export the SysML model in the form of XMI. Then, we parse the XMI representation through difference calculations. Finally, we summarize the results in annotated form. We implemented our method in a satellite system case study and demonstrated the experimental use of the method.

Joint creative process in translation

AbstractIn this article, we explore socially distributed cognition (SDC) as a theoretical model of translation and investigate it empirically as an aspect of the collaborative and creative translation workflow. With the aim of developing a better understanding of SDC and collaborative workflows in translation, we analyzed two different settings where more than one person works on a translation: commercial specialized translation (CST) services, and the production of audio descriptions (AD) as teamwork between blind and sighted describers. The analysis focuses on how the process of co-creation unfolds in the communication that binds together the systems of SDC. While the process of co-creation was strikingly similar in the two different translation contexts, the differences were bound to channels of communication (with or without direct contact between participants), and the draft translation was identified as a central artifact that carries much of the communication when the participants do not work in the same space. With an emphasis on socially distributed cognition, our study provides a framework for both the cognitive and social aspects of translation and develops the understanding of collaborative translation processes. It also contributes to the development of translation practices by helping translation operators and trainers make choices between alternative workflows.

Multi-level production process modeling language

The fourth industrial revolution introduces changes in traditional manufacturing systems and creates basis for a lot-size-one production. The complexity of production processes is significantly increased, alongside the need to enable efficient process simulation, execution, monitoring, real-time decision making and control. The main goal of our research is to define a methodological approach and a software solution in which the Model-Driven (MD) principles and Domain-Specific Modeling Languages (DSMLs) are used to create a framework for the formal description and automatic execution of production processes. In that way production process models are used as central artifacts to manage the production. In this paper, we analyze production process modeling domain and present a DSML which can be used to create production process models suitable for automatic generation of executable code. The generated code is used for automatic execution of production processes within a simulation or a shop floor. The language can be used to specify errors that may occur during the process execution and to specify error handling and corrective steps, too. The DSML is evaluated by different groups of users and the evaluation results are presented. Both the DSML and the accompanying modeling tool are still in the prototype phase, as they are created and evaluated in use cases covering just the assembly of goods. To enable wider application of the language and the tool, it is required to have additional use cases from different manufacturing domains.

Integrated “Generate, Make, and Test” for Formulated Products using Knowledge Graphs

In the multi-billion dollar formulated product industry, state of the art continues to rely heavily on experts during the “generate, make and test” steps of formulation design. We propose automation aids to each step with a knowledge graph of relevant information as the central artifact. The generate step usually focuses on coming up with new recipes for intended formulation. We propose to aid the experts who generally carry out this step manually by providing a recommendation system and a templating system on top of the knowledge graph. Using the former, the expert can create a recipe from scratch using historical formulations and related data. With the latter, the expert starts with a recipe template created by our system and substitutes the requisite constituents to form a recipe. In the current state of practice, the three steps mentioned above operate in a fragmented manner wherein observations from one step do not aid other steps in a streamlined manner. Instead of manually operated labs for the make and test steps, we assume automated or robotic labs and in-silico testing, respectively. Using two formulations, namely face cream and an exterior coating, we show how the knowledge graph may help integrate and streamline the communication between the generate, the make, and the test steps. Our initial exploration shows considerable promise.

Assessing test artifact quality—A tertiary study

Modern software development increasingly relies on software testing for an ever more frequent delivery of high quality software. This puts high demands on the quality of the central artifacts in software testing, test suites and test cases. We aim to develop a comprehensive model for capturing the dimensions of test case/suite quality, which are relevant for a variety of perspectives. We have carried out a systematic literature review to identify and analyze existing secondary studies on quality aspects of software testing artifacts. We identified 49 relevant secondary studies. Of these 49 studies, less than half did some form of quality appraisal of the included primary studies and only 3 took into account the quality of the primary study when synthesizing the results. We present an aggregation of the context dimensions and factors that can be used to characterize the environment in which the test case/suite quality is investigated. We also provide a comprehensive model of test case/suite quality with definitions for the quality attributes and measurements based on findings in the literature and ISO/IEC 25010:2011. The test artifact quality model presented in the paper can be used to support test artifact quality assessment and improvement initiatives in practice. Furthermore, the model can also be used as a framework for documenting context characteristics to make research results more accessible for research and practice.

Augmenting metamodels with seamless support for planning, tracking, and slicing model evolution timelines

In model-based software engineering, models are central artifacts for management, design and implementation. To meet new requirements, engineers need to plan and perform model evolution. So far, model evolution histories are captured using version control systems, e.g., Git. However, these systems are unsuitable for planning model evolution as they do not have a notion of future changes. Furthermore, formally assigning responsibilities to engineers for performing evolution of model parts is achieved by using additional tools for access control. To remedy these shortcomings, we provide a method to generate evolution-aware modeling notations by augmenting existing metamodels with concepts for capturing previous performed and planned evolution as first-class entity. To provide a clear overview, we automatically generate a Gantt-style viewer for augmented models and capabilities to slice models for certain time periods. Our method enables engineers to seamlessly plan future model evolution while actively developing the current model state using a centralized access point for evolution. With the generated Gantt-style viewers and the slicing functionality, we enable engineers to inspect relevant model evolution while reducing model size and hiding unnecessary complexity. In our evaluation, we provide an implementation of our method in the tool TemporalRegulator3000 . We show applicability for real-world metamodels and capture the entire evolution timeline of corresponding models.

A possible conceptualization of the information systems (IS) artifact: A general systems theory perspective1

AbstractThis opinion paper addresses and contributes to the discourse on whether there is a central artifact that captures the essence of the information systems (IS) discipline. It argues that the IS discipline can, and should be, faithfully captured by an IS artifact. We offer a theoretical conception of the IS artifact by drawing upon General Systems Theory (GST). Key concepts of GST are distilled as meta‐principles which inform our formulation of the IS artifact. We use the meta‐principles of the IS artifact to develop salient assertions that theorize what an ‘IS’ is. To demonstrate the appropriateness of our conception, we illustrate how the assertions we developed are consistent with patterns related to emerging topics in IS research, notably, healthcare and IT, and Fintech. We formulate a research agenda on these emerging topics—based upon the conceptions developed in the paper—to guide future research. We conclude with the contributions and implications of our study, including the relevance for IT‐enabled work in the era of the COVID‐19 pandemic.

A Feature-Based Evaluation of Model Merge Methods for e-Health Solutions

Model-driven engineering (MDE) paradigm considers models as central artifacts for software development lifecycle during which models evolve. Developing an e-health solution using MDE poses challenges of model version control, model differencing and model merging, which requires appropriate software configuration management (SCM). In this paper we focus on model-driven merging, which refers to combining two or more versions of a model into a single consolidated version. SCM for model-driven merging leverages evolution of valid configurations, which is a highly desired behavior. Our investigation is based on the features that are required for model-driven SCM realization. Initially, we identify these features using which the existing model-driven merging techniques are evaluated. It is observed that though various proposals are made by academia and research community, a standard model-driven SCM solution that can cater to the needs of industry is still absent. This is in contrary to the situation of traditional SCM systems where standard solutions exist. We also present the usefulness of each technique along with the tradeoffs involved. Finally, guidelines are provided to select techniques appropriate for given circumstances.

A Feature-Based Evaluation of Model Merge Methods for e-Health Solutions

Model-driven engineering (MDE) paradigm considers models as central artifacts for software development lifecycle during which models evolve. Developing an e-health solution using MDE poses challenges of model version control, model differencing and model merging, which requires appropriate software configuration management (SCM). In this paper we focus on model-driven merging, which refers to combining two or more versions of a model into a single consolidated version. SCM for model-driven merging leverages evolution of valid configurations, which is a highly desired behavior. Our investigation is based on the features that are required for model-driven SCM realization. Initially, we identify these features using which the existing model-driven merging techniques are evaluated. It is observed that though various proposals are made by academia and research community, a standard model-driven SCM solution that can cater to the needs of industry is still absent. This is in contrary to the situation of traditional SCM systems where standard solutions exist. We also present the usefulness of each technique along with the tradeoffs involved. Finally, guidelines are provided to select techniques appropriate for given circumstances.

Implementation of a continuous delivery pipeline for enterprise architecture model evolution

The discipline of enterprise architecture (EA) is an established approach to model and manage the interaction of business processes and IT in an organization. Thereby, the EA model as a central artifact of EA is subject to a continuous evolution caused by multiple sources of changes. The continuous evolution requires a lot of effort in controlling and managing the evolution of the EA model. This is especially true when merging the induced changes from different sources in the EA model. Additionally, the lack of tool and automation support makes this a very time-consuming and error-prone task. The evolutionary character and the automated quality assessment of artifacts is a well-known challenge in the software development domain as well. To meet these challenges, the discipline of continuous delivery (CD) has emerged to be very useful. The evolution of EA model artifacts shows similarities to the evolution of software artifacts. Therefore, we leveraged practices of CD to practices of EA maintenance. Thus, we created a conceptual framework for automated EA model maintenance. The concepts were realized in a first prototype and were evaluated in a fictitious case study against equivalence classes based on EA model metrics and a set of several requirements for automated EA model maintenance from research. Overall, the concepts prove to be a promising basis for further refinement, implementation, and evaluation in research in an industrial context.

Empire of Guns: The Violent Making of the Industrial Revolution. By Priya Satia (Stanford, Stanford University Press, 2018) 528 pp. $35.00

<i>Empire of Guns: The Violent Making of the Industrial Revolution</i>. By Priya Satia (Stanford, Stanford University Press, 2018) 528 pp. $35.00

Dynamic Inertia: How Organizations Avoid Adapting to Changes in the Environment

What prevents organizations from adapting to substantial environmental changes? Research from a performative perspective has challenged traditional accounts of cognitive and structural inertia by highlighting how organizational actors dynamically enact routines in a manner that engenders change or stability. However, a puzzle remains: When responding to substantial changes in the environment, how do organizational actors generate inertia? We investigate this question by conducting an inductive, historical study of the credit rating routine of Moody’s, an organization that failed to adapt to substantial changes in its environment in the run up to the financial crisis of 2008. Our analysis of the actions associated with the re- designing of central artifacts and the enactment of the routine reveals six mechanisms by which organizational actors generate inertia. First, when re-designing artifacts, actors generate inertia through bounded retheorizing of the model, the sedimentation of assumptions, and mythical modeling of the unknown. Second, when enacting routines, organizational actors generate inertia by justifying their response to environmental changes through maintaining comprehensibility, appeasing prevailing stakeholders, and exercising professional discretion. Our historical case study contributes to our understanding of organizational inertia, routine dynamics, and the financial crisis of 2008.

Automatic contour extraction algorithm for swept-source optical coherence tomography cornea image

In a swept source-optical coherence tomography system, the telecentric scanning mode gives rise to central saturation artifacts,partial structural loss, and low SNR (signal-to-noise ratio) area in the corneal image, which affects the accuracy of corneal contour extraction. In order to solve this problem, in this paper we propose an automatic extraction algorithm for corneal image of low quality. This algorithm divides the image into high and low SNR region according to the standard deviation distribution of the cornea image. For the high SNR region, we localize the peak point to extract the contour. For the low SNR region, image enhancement is achieved by the registration and superposition of successive frames, which provides reference contour points for low SNR areas. Then corneal contour localization is achieved by weighing the advantages and disadvantages of reference contour points and local line fitting results. Finally, global polynomial fitting is used to achieve the whole corneal contour information. Experiments on the optical eye model show that comparing with the existing algorithms, the accuracy of corneal contour extraction is improved by 4.9% on average.

Empowering OCL research: a large-scale corpus of open-source data from GitHub

Model-driven engineering (MDE) enables the rise in abstraction during development in software and system design. In particular, meta-models become a central artifact in the process, and are supported by various other artifacts such as editors and transformation. In order to define constraints, invariants, and queries on model-driven artifacts, a generic language has been developed: the Object Constraint Language (OCL). In literature, many studies into OCL have been performed on small collections of data, mostly originating from a single source (e.g., OMG standards). As such, generalization of results beyond the data studied is often mentioned as a threat to validity. Creation of a benchmark dataset has already been identified as a key enabler to address the generalization threat. To facilitate further empirical studies in the field of OCL, we present the first large-scale dataset of 103262 OCL expression, systematically extracted from 671 GitHub repositories. In particular, our dataset has extracted these expressions from various types of files (a.o. metamodels and model-to-text transformations). In this work we showcase a variety of different studies performed using our dataset, and describe several other types that could be performed. We extend previous work with data and experiments regarding OCL in model-to-text (mtl) transformations.

Situated and distributed cognition in artifact negotiation and trade-specific skills: A cognitive ethnography of Kashmiri carpet weaving practice

This article describes various ways actors in Kashmiri carpet weaving practice deploy a range of artifacts, from symbolic, to material, to hybrid, in order to achieve diverse cognitive accomplishments in their particular task domains: information representation, inter and intra-domain communication, distribution of cognitive labor across people and time, coordination of team activities, and carrying of cultural heritage. In this repertoire, some artifacts position themselves as naïve tools in the actors’ environment to the point of being ignored; however, their usage-in-context unfolds their cognitive involvement in the tasks. These usages-in-context are shown through artifact analysis of their routine, improvised, and opportunistic uses, where cognitive artifacts like talim—the central artifact of this practice—are shown to play not only multifunctional roles beyond representation, but are also complemented by trade-specific skills bearing strong cognitive implications in a task.

Size, Coupling and Cohesion Metrics for Product-Line Architecture Evaluation: Proposal and Experimental Validation

Software Product Line (SPL) is an approach for de facto reusing of software artifacts for a given domain. Amongst the artifacts developed in the context of SPL is the Product-Line Architecture (PLA). It is one of the central artifacts of the SPL core assets responsible for abstracting a common architecture for specific products. Organizations should continuously evaluate the quality of their products by managing their PLA evolution and variabilities. Thus, the PLA evaluation should be taken into consideration as one of the most important activities throughout a SPL life cycle. Existing literature presents different PLA evaluation methods, from which metrics are most used. Thus, metrics allow different PLA quality attributes to be prioritized when deriving existing products, most of the time by trading-off them. Size, Coupling and Cohesion are examples of important attributes related to Maintainability from ISO/IEC 25010. Metrics for size, coupling and cohesion have successfully been applied in SPL, however, not taking into account commonalities and variabilities. Therefore, this paper proposes metrics for measuring Size, Coupling and Cohesion of PLA, as well as their experimental validations. Such validations are performed correlating the values collected for each metric to participants rating for each quality attribute. Results indicate a weak positive correlation for the size and coupling metrics and a weak negative correlation for the Cohesion metric. In view of the presented evidence, new studies and/or investigations must be carried out to make results generalizable.

Investigation of the influence of constructive-technological parameters on the direct graphitization process of electrodes in Castner furnaces

The numerical research was held to determine possible directions for improvement and modernization of the modern domestic technology of direct graphitization. The influence of the changes in circular gasket internal diameter and contact electrical resistance between electrode artifacts on the state in Castner furnace was investigated. It was found out that the diameter decrease leads to overheating in the central axial part of the electrodes. In turn, the diameter increase leads to significant temperature drops. It was also determined that the usage of gaskets with the increased value of electrical resistance during the graphitization process increases the temperature drop in the central artifacts. Based on the obtained results, the following measures to enhance the energetic efficiency of Castner furnaces operation were proposed: the usage of gaskets with the internal diameter, which is 50-70% from the external artifact diameter; the usage of gaskets with the increased value of electrical resistance on the ends of electrode candles. As a material for end electrocontact gaskets, it is possible to use graphite intercalation material with an increased value of electrical resistance, a multilayer structure, which consists of two paired layers of thermo-extended graphite of high and low density, graphite powder, etc. These measures enable to decrease the time for carbon production graphitization, diminish energy expenses and enhance the quality of the electrode products