Interoperability Of Tools Research Articles

Best practice guidelines for use of reference points in radiation oncology information systems to aggregate longitudinal dosimetric data.

Tracking patient dose in radiation oncology is challenging due to disparate electronic systems from various vendors. Treatment planning systems (TPS), radiation oncology information systems (ROIS), and electronic health records (EHR) lack uniformity, complicating dose tracking and reporting. To address this, we examined practices in multiple radiation oncology settings and proposed guidelines for current systems. A survey was conducted among members of various professional groups to understand dose reporting practices in TPS, ROIS, and EHR systems. The aim was to identify consistent components and develop guidelines. We identified six treatment scenarios where current ROIS defaults fail in accurately representing dose totals. A standardized approach involving three reference point types - Primary Treatment Plan Reference, Dose Check, and Prescription Tracking - was proposed to address these scenarios. Standardizing naming conventions for reference points was also recommended for easier integration with EHRs. The approach requires minimal modifications to existing systems and facilitates easier data transfer and display in EHRs. Standardizing reference points in commercial TPS and ROIS can bridge infrastructure gaps and improve dose tracking in complex clinical scenarios. This standardization, aligned with AAPM's TG-263, paves the way for continual development of automated, standardized, interoperable tools, enhancing the ease of sharing reference point information.

Integration Traffic Signal Control From Synchro to SUMO

This study investigates the feasibility and challenges of transferring traffic signal control schemes from the macroscopic signal timing optimization tool Synchro to the microscopic traffic simulator SUMO, focusing on Downtown Seattle as a case study. The research assesses the process of sharing and importing traffic signal timing plans, a crucial aspect of transportation simulations, between these two platforms. We conduct a detailed analysis of the traffic signal characteristics and data formats unique to each simulator and identify elements suitable for conversion. Subsequently, a four-stage framework is developed for semi-automatic integration of traffic signal control between the two. Our results indicate a successful conversion rate of approximately 85% of signalized intersections from Synchro to SUMO. This research not only illustrates the challenges and solutions in converting signal control across different platforms but also paves the way for future studies aimed at improving the interoperability of various traffic simulation tools.

Meta-analysis of the Turkish energy and climate pathways to achieve the net-zero emission target

The national energy and climate pathways are gaining importance to achieve the global net-zero emissions target. We surveyed the literature on energy and climate pathways for Turkey, with a 1 % share in global emissions with a historical increase of 118 % from 1990 to 2015. We used the meta-analysis method to compare the national and inter-regional energy and climate pathways. The finding reveals that the CO2 emissions are higher in national energy and climate pathways for 2050. The national energy and climate pathways are medium-sighted, with only three scenarios for having a time horizon of 2050. We recommend further research by considering the small study effect and the interoperability of the meta-analysis tools.

Analysis of the Ability of the OSLC Standard to Improve Data Traceability in System Development

AbstractThe development of systems offers a particular challenge for the interoperability of different tools used by collaborating developers like requirements management, design, or simulation tools. The difficult and time‐consuming process to integrate and exchange data between different systems can lead to data inconsistencies and reduced efficiency in the development process. The integration standard Open Services for Lifecycle Collaboration (OSLC) targets the integration of engineering software applications. Its approach supports loose tool coupling, in which each application autonomously manages its own product data, while providing RESTful web services through which other applications can interact. This paper aims to analyze the suitability of OSLC as an overarching integration mechanism for the complete set of engineering artifacts created during system development. This paper presents use cases for the application of OSLC at the company MAHLE. For these use cases, the employed OSLC based toolchain is assessed. The analysis in this paper confirms that OSLC's capabilities allow users to support traceability and can support the exchange and integrate data according to the defined requirements, but it is not sufficient for sophisticated data processing functionalities, such as safety analysis or simulation. The OSLC integration does correspondingly compare favorably to integration technologies already in use regarding traceability, while transformation of data in domain specific tools is needed to achieve deeper levels of integration.

RDF Stream Taxonomy: Systematizing RDF Stream Types in Research and Practice

Over the years, RDF streaming has been explored in research and practice from many angles, resulting in a wide range of RDF stream definitions. This variety presents a major challenge in discussing and integrating streaming systems due to a lack of a common language. This work attempts to address this critical research gap by systematizing RDF stream types present in the literature in a novel taxonomy. The proposed RDF Stream Taxonomy (RDF-STaX) is embodied in an OWL 2 DL ontology that follows the FAIR principles, making it readily applicable in practice. Extensive documentation and additional resources are provided to foster the adoption of the ontology. Three use cases for the ontology are presented with accompanying competency questions, demonstrating the usefulness of the resource. Additionally, this work introduces a novel nanopublications dataset, which serves as a collaborative, living state-of-the-art review of RDF streaming. The results of a multifaceted evaluation of the resource are presented, testing its logical validity, use case coverage, and adherence to the community’s best practices, while also comparing it to other works. RDF-STaX is expected to help drive innovation in RDF streaming by fostering scientific discussion, cooperation, and tool interoperability.

PHA4GE quality control contextual data tags: standardized annotations for sharing public health sequence datasets with known quality issues to facilitate testing and training.

As public health laboratories expand their genomic sequencing and bioinformatics capacity for the surveillance of different pathogens, labs must carry out robust validation, training, and optimization of wet- and dry-lab procedures. Achieving these goals for algorithms, pipelines and instruments often requires that lower quality datasets be made available for analysis and comparison alongside those of higher quality. This range of data quality in reference sets can complicate the sharing of sub-optimal datasets that are vital for the community and for the reproducibility of assays. Sharing of useful, but sub-optimal datasets requires careful annotation and documentation of known issues to enable appropriate interpretation, avoid being mistaken for better quality information, and for these data (and their derivatives) to be easily identifiable in repositories. Unfortunately, there are currently no standardized attributes or mechanisms for tagging poor-quality datasets, or datasets generated for a specific purpose, to maximize their utility, searchability, accessibility and reuse. The Public Health Alliance for Genomic Epidemiology (PHA4GE) is an international community of scientists from public health, industry and academia focused on improving the reproducibility, interoperability, portability, and openness of public health bioinformatic software, skills, tools and data. To address the challenges of sharing lower quality datasets, PHA4GE has developed a set of standardized contextual data tags, namely fields and terms, that can be included in public repository submissions as a means of flagging pathogen sequence data with known quality issues, increasing their discoverability. The contextual data tags were developed through consultations with the community including input from the International Nucleotide Sequence Data Collaboration (INSDC), and have been standardized using ontologies - community-based resources for defining the tag properties and the relationships between them. The standardized tags are agnostic to the organism and the sequencing technique used and thus can be applied to data generated from any pathogen using an array of sequencing techniques. The tags can also be applied to synthetic (lab created) data. The list of standardized tags is maintained by PHA4GE and can be found at https://github.com/pha4ge/contextual_data_QC_tags. Definitions, ontology IDs, examples of use, as well as a JSON representation, are provided. The PHA4GE QC tags were tested, and are now implemented, by the FDA's GenomeTrakr laboratory network as part of its routine submission process for SARS-CoV-2 wastewater surveillance. We hope that these simple, standardized tags will help improve communication regarding quality control in public repositories, in addition to making datasets of variable quality more easily identifiable. Suggestions for additional tags can be submitted to PHA4GE via the New Term Request Form in the GitHub repository. By providing a mechanism for feedback and suggestions, we also expect that the tags will evolve with the needs of the community.

The Damietta Server: a comprehensive protein design toolkit.

The growing importance of protein design to various research disciplines motivates the development of integrative computational platforms that enhance the accessibility and interoperability of different design tools. To this end, we describe a web-based toolkit that builds on the Damietta protein design engine, which deploys a tensorized energy calculation framework. The Damietta Server seamlessly integrates different design tools, in addition to other tools such as message-passing neural networks and molecular dynamics routines, allowing the user to perform multiple operations on structural models and forward them across tools. The toolkit can be used for tasks such as core or interface design, symmetric design, mutagenic scanning, or conformational sampling, through an intuitive user interface. With the envisioned integration of more tools, the Damietta Server will provide a central resource for protein design and analysis, benefiting basic and applied biomedical research communities.The toolkit isavailable with no loginrequirement through https://damietta.de/.

Enhancing Building Energy Efficiency through Building Information Modeling (BIM) and Building Energy Modeling (BEM) Integration: A Systematic Review

With the ever-increasing population and historic highest energy demand, the energy efficiency of buildings is becoming crucial. Architectural firms are moving from traditional Computer-Aided Design (CAD) to BIM. However, nearly 40% of the energy consumption is due to buildings. Therefore, there is a need to integrate BIM with Building Energy Modeling (BEM), which presents an innovative opportunity to demonstrate the potential of BIM to minimize energy consumption by integrating building information software with data from existing energy-efficient building automation systems (EBAS). BEM is a form of computational analysis that can be used in conjunction with BIM or Computer-Aided Engineering (CAE) systems. In this paper, an attempt has been made to explore the existing literature on BIM and BEM and identify the effect of the integration of BEM in BIM in the design phase of the project. A recent survey from the last ten years (2012 to 2023) was carried out on Google Scholar, Web of Science, Science Direct, and Scopus databases. Inclusion/exclusion criteria were applied, and papers were scrutinized. From the results, it can be observed that the convergence of BIM and BEM is found to be useful in practical applications; however, projects with short life cycles might not be suitable for this solution. Challenges exist in the interoperability tools which have restrictions on data exchange. Binary translation is found to be the most suitable candidate for data exchange. The analysis further showed that the most used program for integrating BIM/BEM is Green Building Studio developed by Autodesk to improve construction and operational efficiencies.

Designing a Tool to Support Online Physical Education

This design case details a seven-year iterative design process to create an app for use in online physical education classes. Each iteration addresses the shortcomings of the previous version. The most recent iteration of the app allows students to use Fitbit™ devices to record heart rate data, which each student sees as progress toward course goals on the homepage of the course. The current version of the app has evolved to provide a seamless student experience using a web application programming interface (API) and data standards such as learning tools interoperability (LTI). The student experience of using the app is thoroughly documented, as are design processes and principles for engaging in similar design processes.

Multiscale co-simulation design pattern for neuroscience applications.

Integration of information across heterogeneous sources creates added scientific value. Interoperability of data, tools and models is, however, difficult to accomplish across spatial and temporal scales. Here we introduce the toolbox Parallel Co-Simulation, which enables the interoperation of simulators operating at different scales. We provide a software science co-design pattern and illustrate its functioning along a neuroscience example, in which individual regions of interest are simulated on the cellular level allowing us to study detailed mechanisms, while the remaining network is efficiently simulated on the population level. A workflow is illustrated for the use case of The Virtual Brain and NEST, in which the CA1 region of the cellular-level hippocampus of the mouse is embedded into a full brain network involving micro and macro electrode recordings. This new tool allows integrating knowledge across scales in the same simulation framework and validating them against multiscale experiments, thereby largely widening the explanatory power of computational models.

A methodology to customise commercial products of SMEs

Product development durations are being drastically reduced, thanks, amongst other reasons, to the use of design automation techniques. But this trend is observed in large companies and to a much lesser extent in SMEs. This article seeks to research the possibility of finding suitable automation technologies for this type of enterprises. Automating the development of commercial offers in SMEs can be a good starting point to the change in this trend. Focusing on this objective, the necessary requirements that a tool of this type must have are established. Different models of assistants have been developed and analysed on different products, deducing from their results an ideal system architecture and methodology. This solution is based on design tables, a technology that links data from a spreadsheet, implements the company’s design process, with parameters of a three-dimensional CAD model, which represents the solution. The rest of the documents that constitute the commercial offer and the possibility of linking them with verification tools are derived from this design core. The main conclusion is the current viability of this method, anticipating the improvement of many aspects, mainly highlighting the link with the rest of the life cycle phases through interoperability tools.

Easy JavaScript Simulation (EJSS) Data Analytics for Singapore

We have integrated Easy JavaScript Simulation (EJSS) Data Analytics into the national Learning Management System for Singapore schools, known as the Singapore Student Learning Space (SLS). EJSS Data Analytics enhances the teaching and learning experience for educators and students by enabling educators to monitor and evaluate students’ interactions with interactive computer simulations. The data analytics and visualisation capabilities are delivered using the Moodle platform and version 1.3 of the specifications for Learning Tools Interoperability (LTI). In this paper, we showcase the potential for EJSS Data Analytics to identify students’ learning difficulties and misconceptions. Four examples of EJSS Data Analytics applications are provided to illustrate insights on aspects that include understanding a student’s sequential actions leading to specific task outcomes, the frequency of task attempts by each student, and the ratio of students achieving correct versus incorrect task completions. We identify five key considerations for designing the EJSS teacher dashboard. These considerations relate to Student Thought Process, Student Behaviour, Student Engagement, Student Choice, and Teacher Feedback. These five facets provide a framework for aligning our design efforts with the needs of students and teachers, also drawing upon research in data analytics for education.

A Methodology for Integrating Hierarchical VMAP-Data Structures into an Ontology Using Semantically Represented Analyses

Integrating physical simulation data into data ecosystems challenges the compatibility and interoperability of data management tools. Semantic web technologies and relational databases mostly use other data types, such as measurement or manufacturing design data. Standardizing simulation data storage and harmonizing the data structures with other domains is still a challenge, as current standards such as the ISO standard STEP (ISO 10303 ”Standard for the Exchange of Product model data”) fail to bridge the gap between design and simulation data. This challenge requires new methods, such as ontologies, to rethink simulation results integration. This research describes a new software architecture and application methodology based on the industrial standard ”Virtual Material Modelling in Manufacturing” (VMAP). The architecture integrates large quantities of structured simulation data and their analyses into a semantic data structure. It is capable of providing data permeability from the global digital twin level to the detailed numerical values of data entries and even new key indicators in a three-step approach: It represents a file as an instance in a knowledge graph, queries the file’s metadata, and finds a semantically represented process that enables new metadata to be created and instantiated.

한국어교육 및 학습 도구로써 AI 활용 가능성 탐색

The purpose of this study is to recognize changes in educational paradigm due to the development of Information and communication technology and the arrival of digital native generation, and to apply new educational tools tailored to learner characteristics to Korean Education. In order to comply with these objectives, the applicability of AI as a tool for teaching and learning Korean was discovered featuring ChatGPT which is a generative Artificial Intelligence currently under the spotlight. Existing discussions for Korean Education using Artificial Intelligence were first investigated and the concept and characteristics of the generative Artificial Intelligence ChatGPT were then explored. Based on this, a commandbased model applicable to teaching and learning Korean and the precautions for use were disclosed in detail. Further, examples of real life applications were presented to promote understanding and educational effects were sought to be maximized by introducing interoperable tools to expand from simply reading and writing to listening and speaking the language. This study is expected to contribute to the expansion of the extent and depth of follow-up research as preliminary data so as to suggest the direction of using AI in Korean Education.

SRNAfrag: a pipeline and suite of tools to analyze fragmentation in small RNA sequencing data.

Fragments derived from small RNAs such as small nucleolar RNAs are biologically relevant but remain poorly understood. To address this gap, we developed sRNAfrag, a modular and interoperable tool designed to standardize the quantification and analysis of small RNA fragmentation across various biotypes. The tool outputs a set of tables forming a relational database, allowing for an in-depth exploration of biologically complex events such as multi-mapping and RNA fragment stability across different cell types. In a benchmark test, sRNAfrag was able to identify established loci of mature microRNAs solely based on sequencing data. Furthermore, the 5' seed sequence could be rediscovered by utilizing a visualization approach primarily applied in multi-sequence-alignments. Utilizing the relational database outputs, we detected 1411 snoRNA fragment conservation events between two out of four eukaryotic species, providing an opportunity to explore motifs through evolutionary time and conserved fragmentation patterns. Additionally, the tool's interoperability with other bioinformatics tools like ViennaRNA amplifies its utility for customized analyses. We also introduce a novel loci-level variance-score which provides insights into the noise around peaks and demonstrates biological relevance by distinctly separating breast cancer and neuroblastoma cell lines after dimension reduction when applied to small nucleolar RNAs. Overall, sRNAfrag serves as a versatile foundation for advancing our understanding of small RNA fragments and offers a functional foundation to further small RNA research. Availability: https://github.com/kenminsoo/sRNAfrag.

Online interoperable resources for building hippocampal neuron models via the Hippocampus Hub.

To build biophysically detailed models of brain cells, circuits, and regions, a data-driven approach is increasingly being adopted. This helps to obtain a simulated activity that reproduces the experimentally recorded neural dynamics as faithfully as possible, and to turn the model into a useful framework for making predictions based on the principles governing the nature of neural cells. In such a context, the access to existing neural models and data outstandingly facilitates the work of computational neuroscientists and fosters its novelty, as the scientific community grows wider and neural models progressively increase in type, size, and number. Nonetheless, even when accessibility is guaranteed, data and models are rarely reused since it is difficult to retrieve, extract and/or understand relevant information and scientists are often required to download and modify individual files, perform neural data analysis, optimize model parameters, and run simulations, on their own and with their own resources. While focusing on the construction of biophysically and morphologically accurate models of hippocampal cells, we have created an online resource, the Build section of the Hippocampus Hub -a scientific portal for research on the hippocampus- that gathers data and models from different online open repositories and allows their collection as the first step of a single cell model building workflow. Interoperability of tools and data is the key feature of the work we are presenting. Through a simple click-and-collect procedure, like filling the shopping cart of an online store, researchers can intuitively select the files of interest (i.e., electrophysiological recordings, neural morphology, and model components), and get started with the construction of a data-driven hippocampal neuron model. Such a workflow importantly includes a model optimization process, which leverages high performance computing resources transparently granted to the users, and a framework for running simulations of the optimized model, both available through the EBRAINS Hodgkin-Huxley Neuron Builder online tool.

PhysiBoSS 2.0: a sustainable integration of stochastic Boolean and agent-based modelling frameworks

In systems biology, mathematical models and simulations play a crucial role in understanding complex biological systems. Different modelling frameworks are employed depending on the nature and scales of the system under study. For instance, signalling and regulatory networks can be simulated using Boolean modelling, whereas multicellular systems can be studied using agent-based modelling. Herein, we present PhysiBoSS 2.0, a hybrid agent-based modelling framework that allows simulating signalling and regulatory networks within individual cell agents. PhysiBoSS 2.0 is a redesign and reimplementation of PhysiBoSS 1.0 and was conceived as an add-on that expands the PhysiCell functionalities by enabling the simulation of intracellular cell signalling using MaBoSS while keeping a decoupled, maintainable and model-agnostic design. PhysiBoSS 2.0 also expands the set of functionalities offered to the users, including custom models and cell specifications, mechanistic submodels of substrate internalisation and detailed control over simulation parameters. Together with PhysiBoSS 2.0, we introduce PCTK, a Python package developed for handling and processing simulation outputs, and generating summary plots and 3D renders. PhysiBoSS 2.0 allows studying the interplay between the microenvironment, the signalling pathways that control cellular processes and population dynamics, suitable for modelling cancer. We show different approaches for integrating Boolean networks into multi-scale simulations using strategies to study the drug effects and synergies in models of cancer cell lines and validate them using experimental data. PhysiBoSS 2.0 is open-source and publicly available on GitHub with several repositories of accompanying interoperable tools.

Epiq: An open-source software for the calculation of electron-phonon interaction related properties

epiq (Electron-Phonon wannier Interpolation over k and q-points) is an open-source software for the calculation of electron-phonon interaction related properties from first principles. Acting as a post-processing tool for a density-functional perturbation theory code (Quantum ESPRESSO) and wannier90, epiq exploits the localization of the deformation potential in the Wannier function basis and the stationary properties of a force-constant functional with respect to the first-order perturbation of the electronic charge density to calculate many electron-phonon related properties with high accuracy and free from convergence issues related to Brillouin zone sampling. epiq features include: the adiabatic and non-adiabatic phonon dispersion, superconducting properties (including the superconducting band gap in the Migdal-Eliashberg formulation), double-resonant Raman spectra and lifetime of excited carriers. The possibility to customize most of its input makes epiq a versatile and interoperable tool. Particularly relevant is the interaction with the Stochastic Self-Consistent Harmonic Approximation (SSCHA) allowing anharmonic effects to be included in the calculation of electron-properties. The scalability offered by the Wannier representation combined with a straightforward workflow and easy-to-read input and output files make epiq accessible to the wide condensed matter and material science communities. Program summaryProgram Title:epiqCPC Library link to program files:https://doi.org/10.17632/f2syws66d7.1Developer's repository link:https://gitlab.com/the-epiq-team/epiqLicensing provisions: GPLv3Programming language: FORTRAN95External routines: BLAS (http://www/netlib.org/blas), LAPACK (http://www.netlib.org/lapack), Quantum ESPRESSO (https://www.quantum-espresso.org/), wannier90 (https://wannier.org/)Nature of problem: Direct first principles calculation of quantities obtained via linear response methods in solid-state systems, such as the deformation potential, can be computationally demanding, hindering proper convergence.Solution method: An interpolation scheme exploiting the localization of the deformation potential in the Wannier function basis and the stationary properties of a force-constant functional with respect to the first-order perturbation of the electronic charge density is implemented in epiq. Within this approach it is possible to calculate many electron-phonon related properties with high accuracy and a low computational effort.

Authoring Terrains with Spatialised Style

AbstractVarious terrain modelling methods have been proposed for the past decades, providing efficient and often interactive authoring tools. However, they seldom include any notion of style, which is critical for designers in the entertainment industry. We introduce a new generative network method that bridges the gap between automatic terrain synthesis and authoring, providing a versatile set of authoring tools allowing spatialised style. We build upon the StyleGAN2 architecture and extend it with authoring tools. Given an input sketch or existing elevation map, our method generates a terrain with features that can be authored, enhanced, and augmented using interactive brushes and style manipulation tools. The strength of our approach lies in the versatility and interoperability of the different tools. We validate our method quantitatively with drainage calculation against other previous techniques and qualitatively by asking users to follow a prompt or freely create a terrain.

Privacy governance not included: analysis of third parties in learning management systems

PurposeThis paper aims to address research gaps around third party data flows in education by investigating governance practices in higher education with respect to learning management system (LMS) ecosystems. The authors answer the following research questions: how are LMS and plugins/learning tools interoperability (LTI) governed at higher education institutions? Who is responsible for data governance activities around LMS? What is the current state of governance over LMS? What is the current state of governance over LMS plugins, LTI, etc.? What governance issues are unresolved in this domain? How are issues of privacy and governance regarding LMS and plugins/LTIs documented or communicated to the public and/or community members?Design/methodology/approachThis study involved three components: (1) An online questionnaire about LMS, plugin and LTI governance practices from information technology professionals at seven universities in the USA (n = 4) and Canada (n = 3). The responses from these individuals helped us frame and design the interview schedule. (2) A review of public data from 112 universities about LMS plugin and LTI governance. Eighteen of these universities provide additional documentation, which we analyze in further depth. (3) A series of extensive interviews with 25 university data governance officers with responsibilities for LMS, plugin and/or LTI governance, representing 14 different universities.FindingsThe results indicate a portrait of fragmented and unobtrusive, unnoticed student information flows to third parties. From coordination problems on individual college campuses to disparate distributions of authority across campuses, as well as from significant data collection via individual LTIs to a shared problem of scope across many LTIs, the authors see that increased and intentional governance is needed to improve the state of student privacy and provide transparency in the complex environment around LMSs. Yet, the authors also see that there are logical paths forward based on successful governance and leveraging existing collaborative networks among data governance professionals in higher education.Originality/valueSubstantial prior work has examined issues of privacy in the education context, although little research has directly examined higher education institutions’ governance practices of LMS, plugin and LTI ecosystems. The tight integration of first and third-party tools in this ecosystem raises concerns that student data may be accessed and shared without sufficient transparency or oversight and in violation of established education privacy norms. However, these technologies and the university governance practices that could check inappropriate data handling remain under-scrutinized. This paper addresses this gap by investigating the governance practices of higher education institutions with respect to LMS ecosystems.