Data Exchange Format Research Articles

FILE FORMAT SELECTION FOR EFFICIENT DIGITAL PROCESS CHAINS IN ADDITIVE MANUFACTURING

AbstractSelecting a suitable file format for data exchange in additive manufacturing is fundamental when designing these digital process chains. Within the scope of this investigation, alternatives to the de-facto industry standard STL are to be found to overcome the disadvantages of the STL-based digital process chain.Therefore, suitable file formats are identified by conducting literature and market research and evaluated regarding their suitability to support a continuous digital process chain. In addition, typical use cases in additive manufacturing are defined, and their requirements for a file format for data exchange are derived. Finally, for each use case defined, recommended and suitable file formats are proposed.

Heritage-BIM for energy simulation: a data exchange method for improved interoperability

ABSTRACT The use of Building Information Modelling (BIM) for Building Energy Simulation (BES) is challenged by inadequate data integration and unreliable data and geometry conversion. Despite recent efforts to address critical interoperability issues, the effective exchange of data between the two digital environments remains a non-truly fulfilled promise of the digital transformation agenda for the industry. To contribute to the broader community effort in mitigating this deficiency, the present article proposes an alternative method for securing an improved BIM to BES workflow for existing and heritage buildings. The proposed method suggests an alternative way for integrating environmental analysis data to the Heritage BIM model, as well as an easy to develop visual programming process for missing data recovery, through auxiliary exchange operations. The article also presents lessons learned for the geometrical conversion of BIM elements with non-standard and irregular attributes, evaluated through the energy retrofit application of a colonial heritage building. The proposed method demonstrates how visual programming tools and common data exchange formats can supplementary assist existing practises to deal with major interoperability obstacles. The overall findings contribute to current efforts in the field, for the establishment of good practices of using Heritage BIM for energy retrofit architectural interventions.

Problems of information technology support for implementation BIM concepts

Objective. The purpose of the study is to analyze the current level of development of the digital infrastructure of the urban planning sector, to identify the features of information technology support for the implementation of the BIM concept at the stages of the life cycle of the CCS and the functionality presented on the national market of solutions that support BIM technology. Method. Within the framework of the study, the methods of logical, structural, comparative, system analysis were used; modeling and graphical presentation of results.Result. It has been established that in the current period, most companies in the Russian architecture and construction industry are considering the transition to a fully integrated BIM as a long-term development format. An objective obstacle to a quick transition is the complexity of complex IT support for BIM processes and the level of current development of digital infrastructure. It has been established that the priority direction for the development of the IT industry in the context of ensuring the implementation of the BIM concept is the formation of a single ecosystem of Russian BIM software. Along with the need to develop competitive Russian software products, ensuring their interoperability and standardization of data exchange formats are highlighted as the main problems. The key parameters for assigning a software product to the BIM group are determined, the levels of maturity of the BIM data exchange process are identified, and approaches to the organization of exchange processes are considered.Conclusion. The proposed criteria for classifying software products as solutions that support the BIM concept can be used in the formation of functional requirements for the developed import-independent software products. The interpretation of the interoperability reference model in relation to BIM technology can be used to develop the integration capabilities of BIM tools in a single information technology environment of general data, and also become a methodological basis for creating an open national data exchange standard.

Generalized Tree Structure to Annotate Untargeted Metabolomics and Stable Isotope Tracing Data.

In untargeted metabolomics, multiple ions are often measured for each original metabolite, including isotopic forms and in-source modifications, such as adducts and fragments. Without prior knowledge of the chemical identity or formula, computational organization and interpretation of these ions is challenging, which is the deficit of previous software tools that perform the task using network algorithms. We propose here a generalized tree structure to annotate ions in relationships to the original compound and infer neutral mass. An algorithm is presented to convert mass distance networks to this tree structure with high fidelity. This method is useful for both regular untargeted metabolomics and stable isotope tracing experiments. It is implemented as a Python package (khipu) and provides a JSON format for easy data exchange and software interoperability. By generalized preannotation, khipu makes it feasible to connect metabolomics data with common data science tools and supports flexible experimental designs.

Inventory analytics: A teaching case using excel and Alteryx

The emergence of big data and analytics has motivated the audit profession to incorporate additional business analytical procedures into existing auditing processes. In response, educators must find ways to integrate data analytics into existing audit curriculum to prepare students for the audit profession. One possible way to integrate analytics into the audit curriculum is to supplement the teaching of traditional audit topics with data analytics case studies. The purpose of this paper is to describe a teaching case that integrates the auditing topics of inventory and fraud with basic data analytics. We develop a teaching case motivated by practice that describes an Excel-based fraud related to the audit of inventory. As Excel remains a common tool for accounting analytics, as well as a common format for data exchange between the auditor and client, the case begins with data analysis using Excel. After completing the initial Excel analysis, you perform a similar analysis using a more advanced analytics tool (Alteryx), which provides you an opportunity to use a new tool to detect the spreadsheet irregularities. The case concludes with you assessing the advantages and disadvantages of Alteryx versus Excel. As the context of this case is the audit of inventory, the case is especially suited for use in an audit class when covering the financial statement area of inventory. Alternatively, this case can be used in an accounting analytics class to introduce advanced analytics tools using a real-world audit setting.

FAIR and scalable management of small-angle X-ray scattering data.

A modular research data management toolbox based on the programming language Python, the widely used computing platform Jupyter Notebook, the standardized data exchange format for analytical data (AnIML) and the generic repository Dataverse has been established and applied to analyze small-angle X-ray scattering (SAXS) data according to the FAIR data principles (findable, accessible, interoperable and reusable). The SAS-tools library is a community-driven effort to develop tools for data acquisition, analysis, visualization and publishing of SAXS data. Metadata from the experiment and the results of data analysis are stored as an AnIML document using the novel Python-native pyAnIML API. The AnIML document, measured raw data and plots resulting from the analysis are combined into an archive in OMEX format and uploaded to Dataverse using the novel easyDataverse API, which makes each data set accessible via a unique DOI and searchable via a structured metadata block. SAS-tools is applied to study the effects of alkyl chain length and counterions on the phase diagrams of alkyltrimethyl-ammonium surfactants in order to demonstrate the feasibility and usefulness of a scalable data management workflow for experiments in physical chemistry.

A REVIEW OF 3D SPATIAL DATA MODELS FOR SURFACE AND SUBSURFACE INTEGRATION OF SPATIAL OBJECTS

Abstract. Three dimensional (3D) spatial data models have been known as a geographic information system platform for representing the dimensionality of spatial objects with respect to the real world. They can be used to mimmick the real-world objects above the ground, on the ground and underground. A 3D spatial data model that can integrate surface and subsurface elements will have a significant impact on engineering, spatial and urban planning, and the built environment. Such an impact includes good infrastructure development, proper planning, result-oriented installation of utilities, location-specific excavation of existing utilities, and cost-effective economy resulting from minimal damage of infrastructures. This article explores and documents the state-of-the-art with respect to 3D spatial data models specifically for the integration of surface and subsurface objects based on a thorough review of the literature in academic articles, technical reports, and web-based materials. To better understand the scope, this paper reviews the different 3D spatial modelling approach for surface spatial objects, subsurface spatial objects, and with keen focus on surface and subsurface spatial objects integration. The Open Geospatial Consortium (OGC) has played an important role in data integration and has a core space in 3D spatial data model evolution. One of the recent data models for such task is CityJSON due to its simplicity in data storage, visualization, manipulation, and data update compared to CityGML. The parameters influencing the choice of models can be attributed to the availability of data structure, applicability, exchange format and relevance. Based on the range of 3D spatial data model reviewed, a unified model is expedient for integration of surface and subsurface spatial objects.

Adaptive technologies for rapid web interface design of corporate educational systems within the framework of the 1C:Enterprise 8.3 platform

The article discusses technologies for fast web application deployment design based on continuous information exchange with a corporate system developed using the 1C:Enterprise 8.3 platform. We identify data exchange formats between a web application and a software product based on the 1C:Enterprise 8.3 platform to handle the tasks of dynamically generated and adaptable interfaces. The study proposes the concept of a modifiable component-based architecture for the interaction of a web application with commercial data storage and processing systems. This concept makes it possible to implement a dynamic web application interface design and to automate the data management functionality directly from the enterprise solution based on the 1C:Enterprise 8.3 platform. The article formulates the criteria and operating principles for such an application. We have also developed system technologies to design a web application that can be integrated into replicated software solutions permitting control of the mechanisms for dynamic interface design and data transfer from the solution to a web application. The launched application for web application interfaces designing makes it possible to dynamically change the components of web forms as well as determine the details displayed to the user in the output interface. In addition, we describe the principles of dynamic interaction between a web application and the data interface management component. The research enabled us to identify the components of the module for interaction of interfaces with the web application. A conceptual universal control scheme for generating dynamic interfaces has been formulated. It can be implemented to create almost any kind of web forms, including processing incoming data from a web application using the REST interchange in JSON format. The article provides a comparison of interchange formats. We describe implemented IT-projects for organizing a prospective student’s personal account and the applicant’s dynamic rating. These projects are the result of the ideas proposed in the article.

Syntax Tree Development for Automated Serial-to-Parallel Code Translator for Multicore Processors

The emergence of multicore architectures has extremely stimulated the area of parallel computing. However, developing a parallel program and manually paralleling inherited sequential program codes are time-consuming work. The programmer should have good skills in using parallel programming methods. This fact determines the relevance of the subject of the research – the development of a serial-to-parallel code translator. The article gives a review of existing solutions in the chosen direction of research and considers their advantages and disadvantages. The principle of formation of a syntactic tree which is based on JSON format (the text format of data exchange based on JavaScript) is offered and an example of formation of a syntactic tree on the basis of this principle is considered. The result of the work is an approach for building a program platform for translating sequential code into parallel code. The distinctive feature of the developed platform is the web-service, which potentially allows you to extend the translator with other programming languages. The interaction with the programming environment is realized by means of REST-requests (HTTP-requests designed to call remote procedures). The developed software platform consists of three modules: the query processing module, which provides interaction with external systems through REST-requests; the tree building module, which forms a syntax tree on the basis of the source program code; the code conversion module, which obtains parallel program code on the basis of the syntax tree.

The Near Infrared Imager and Slitless Spectrograph for JWST. V. Kernel Phase Imaging and Data Analysis

Kernel phase imaging (KPI) enables the direct detection of substellar companions and circumstellar dust close to and below the classical (Rayleigh) diffraction limit. The high-Strehl full pupil images provided by the James Webb Space Telescope (JWST) are ideal for application of the KPI technique. We present a kernel phase analysis of JWST NIRISS full pupil images taken during the instrument commissioning and compare the performance to closely related NIRISS aperture masking interferometry (AMI) observations. For this purpose, we develop and make publicly available the custom Kpi3Pipeline data reduction pipeline enabling the extraction of kernel phase observables from JWST images. The extracted observables are saved into a new and versatile kernel phase FITS file data exchange format. Furthermore, we present our new and publicly available fouriever toolkit which can be used to search for companions and derive detection limits from KPI, AMI, and long-baseline interferometry observations while accounting for correlated uncertainties in the model fitting process. Among the four KPI targets that were observed during NIRISS instrument commissioning, we discover a low-contrast (∼1:5) close-in (∼1 λ/D) companion candidate around CPD-66 562 and a new high-contrast (∼1:170) detection separated by ∼1.5 λ/D from 2MASS J062802.01-663738.0. The 5σ companion detection limits around the other two targets reach ∼6.5 mag at ∼200 mas and ∼7 mag at ∼400 mas. Comparing these limits to those obtained from the NIRISS AMI commissioning observations, we find that KPI and AMI perform similar in the same amount of observing time. Due to its 5.6 times higher throughput if compared to AMI, KPI is beneficial for observing faint targets and superior to AMI at separations ≳325 mas. At very small separations (≲100 mas) and between ∼250 and 325 mas, AMI slightly outperforms KPI which suffers from increased photon noise from the core and the first Airy ring of the point-spread function.

Review of current ECG consumer electronics (pros and cons)

BackgroundSeveral wearable, medical-grade consumer ECG devices are now available and integrated into consumer electronics like multi sensor fitness watches and scales. Specific consumer ECGs can also come in the form of patches or thin sensor plates in credit card or other shapes. Watches with ECG capabilities are often multi vital sign sensor devices. The majority of these devices are usually connected to a mobile smartphone. However, there are pros and cons to their use. MethodsWe review here an exemplary selection of modern consumer ECG devices based on device type, recording method and the number of standard ECG channels derived. ResultsSingle-channel consumer ECG devices such as Smart Watches can be useful for detecting and monitoring atrial fibrillation and flutter and other arrhythmias, as well as ectopic complexes. However, they are currently limited with respect to recording duration and information content (a single-channel or limb‑lead ECG having less diagnostic information than a 12‑lead ECG). While some non watch-based consumer ECG devices can now record all 6 limb leads to yield increased information, no consumer ECG devices can currently reliably detect ST-segment deviations, potentially indicating myocardial infarction or ischemic episodes. Moreover, barriers to use still exist for at-risk elderly people. Finally, there currently is no universal data exchange format. ConclusionConsumer ECG devices, whether in fitness or fashionable design, allow for reliable detection of atrial fibrillation. Timely detection of atrial fibrillation and subsequent treatment might protect against stroke, especially in high-risk groups, yet prospective evidence is still lacking. Six-channel consumer ECG and longer data collection capabilities extend potential functionality, including for the monitoring of ST-segments and QT intervals. However, no currently available devices are sufficiently suitable for the detection of myocardial infarction or ischemia, which is why portable 12-channel technologies are desirable. For the reliable detection of a myocardial infarction, the determination of specific myocardial infarction blood markers and evaluation of patient medical history still is indispensable in addition to the 12 lead ECG.

Impact of Free Trade Area on Trade, Revenue and Welfare in Nigeria

This study offers an analytical evaluation of the effects of Free Trade Area (FTA) agreements on trade, revenue, and welfare in Nigeria. The study applied World-Integrated Trade Solution/Software for Market Analysis and Restrictions on Trade (WITS-SMART), anchored on a partial equilibrium model (PEM) for its simulations. The study simulated 100% tariff elimination on selected products under Harmonized System (HS)-2 classification code sourced from Trade Analysis Information Systems (TRAINS) and Common Format for Transient Data Exchange (COMTRADE). The study’s findings show that the African Continental Free Trade Area (AfCFTA) agreement will benefit Nigeria’s economy from trade creation estimated at US$8,860.419 million, including a favorable welfare gain to the value of US$740.571 million. Nevertheless, Nigeria will sustain losses in trade revenue, valued at US$6,142.061 million. The study recommends proficient revenue management and well-diversified revenue collection sources, such as improvement in Value Added Tax and Ad-Valorem duty, to cushion the effects of the revenue loss resulting from tariff elimination in the FTA. JEL Classification F1, F2, F4, F5, F6, I3

An Approach for Securing JSON Objects through Chaotic Synchronization

Abstract Nowadays the interoperability of web applications is carried out by the use of data exchange formats such as XML and JavaScript Object Notation (JSON). Due to its simplicity, JSON objects are the most common way for sending information over the HTTP protocol. With the aim of adding a security mechanism to JSON objects, in this work we propose an encryption approach for cipher JSON objects through the use of chaotic synchronization. Synchronization ability between two chaotic systems offers the possibility of securing information between two points. Our approach includes mechanisms for diffusing and confusing JSON objects (plaintext), which yields a proper ciphertext. Our approach can be applied as an alternative to the existing securing JSON approaches such as JSON Web Encryption (JWE).

Enhancing RDM in Galaxy by integrating RO-Crate

Enhancing RDM in Galaxy by integrating RO-Crate

ManIAS: A community-driven data model and data exchange format for the management of invasive alien species and wildlife

Invasive alien species (IAS) are recognised as one of the major threats to biodiversity. The European Union (EU) Regulation 1143/2014 on the prevention of introduction and spread of invasive alien species imposes an obligation on Member States to develop management responses against a list of IAS of Union Concern and requires reporting on those interventions. However, the actors involved in IAS management are typically diverse and include authorities, managers, businesses and non-governmental organizations (NGOs). Reporting on management actions, if performed at all, is often crude and does not capture essential information. Data on management are heterogeneous both in quality and format as well as what information is captured. They are recorded using a plethora of tools, are managed in data silos and not openly available. Here, we propose a community-driven data model and data exchange format for IAS and wildlife management data, called manIAS (management of Invasive Alien Species, Fig. 1). This was drafted in two consecutive workshops (Oldoni et al. 2022), building on the experience of the managerial community, combined with the existing european network of wildlife professionals (ENETWILD) standard (Body et al. 2020) for management reporting in the framework of animal health. We feel the development of such a data model is necessary and can bring multiple benefits within and outside the IAS management community. First, the data model can create awareness with data providers and project managers on the minimum quality standards for reporting on IAS management such as the target species, the management objective, the methods used, the effort spent, the results of the action and any encountered non-target effects. Second, the data exchange format will allow for easy aggregation of management data across taxa, regions, management actors and projects. Such exchanges of data on management, for example through visualisations, are necessary for running coordinated management programmes. Thirdly, it will ease the reporting on management for the EU IAS Regulation since authorities will have to spend less time in collecting and standardizing data from different actors. Lastly, the standardisation will allow more straightforward analysis of the effectiveness of management methods and the efficiency of control programmes.

Organizing and Maintaining a Taxonomic Expert Network: Lessons from the Caryophyllales TEN

The Caryophyllales TEN is one of the Taxonomic Expert Networks for the World Flora Online (WFO, worldfloraonline.org). It was initiated in 2011 with the aim to create a global taxonomic synthesys of the angiosperm order Caryophyllales (about 6% of the angiosperm species). The network currently includes about 170 scientists from 36 countries. The first priority is creating a dynamic taxonomic backbone for the order using the EDIT Platform for Cybertaxonomy (cybertaxonomy.org). One key product is an online portal (caryophyllales.org) that serves as a single entry point for expert-reviewed information. The EDIT Data Portal is one of the software components of the EDIT Platform (see the list of reference projects for further examples). Data entry, imports and editing is managed by the Taxonomic Editor component. Web services and data exchange via standardized formats will be used to connect to international biodiversity informatics initiatives such as the Global Biodiversity Information Facility and the International Plant Name Index. The data are available in a standardized format for open data exchange. Completed checklist projects with accompanying data papers so far consist of a genus-level checklist of the whole order (Hernández-Ledesma et al. 2015) and species-level treatments for Nepenthaceae (Berendsohn et al. 2018), Cactaceae (Korotkova et al. 2021) and Dianthus, Caryophyllaceae (Fassou et al. 2022). The entire Caryophyllaceae, Plumbaginaceae and the Amaranthaceae are under revision, Aizoaceae and most of the smaller families have been revised based on literature. These projects all aimed to network existing specialists for the respective families and to produce checklists that reflect the current state of research on the given group, where possible based on phylogenetic studies. The Caryophyllales TEN is coordinated by a scientist at the Botanic Garden Berlin but otherwise has no explicit governance or committees. The experiences from the aforementioned projects allow for some general insights as to organizing and maintaining a taxonomic expert network. Whereas a scientific network is usually a relatively loose connection between collaborators with varying levels of commitment over time, a strong expert network that works towards a specific product needs a firmer structure. According to our experience, five aspects are important. 1. Clarity. A clearly defined framework which can include the written summary of the rationale and the main underlying principles, detailed editorial guidelines and guidelines for contributors, best-practice recommendations, a clear outline of different roles which experts can have in the project, and requirements for authorship on resulting publications. 2. Flexibility. The framework should be defined in a way that it still allows flexible approaches to the individual projects and the roles that can account for varying levels of commitment and needs of individual researchers. 3. Community aspect. Bringing experts together regularly through in-person conferences or virtual meetings is essential to keep the network going. Participation should be open for everyone who is interested, regardless of career level and there should be different lowthreshold “entry points”. These can be participation in a conference, being invited to contribute to a checklist or seeking out other experts for collaboration. Already active experts can engage and further connect people to the network, thus creating a large and strong community. 4. Credits. Our policy is that each source is referenced and each individual contribution is acknowledged in the data paper and online portal. This aims at increasing the visibility of research results and developing best-practice approaches within the community. 5. Incentives and commitment. People will participate in such networks because they have a strong personal interest to invest their time and energy in a project that is valuable to them and aligns with their own goals. Expert networks need committed people and therefore, there must be strong incentives, for example being part of a widely known and highly visible initiative or co-authoring a key data paper.

Structured Data Storage for Data-Driven Process Optimisation in Bioprinting

Bioprinting is a method to fabricate 3D models that mimic tissue. Future fields of application might be in pharmaceutical or medical context. As the number of applicants might vary between only one patient to manufacturing tissue for high-throughput drug screening, designing a process will necessitate a high degree of flexibility, robustness, as well as comprehensive monitoring. To enable quality by design process optimisation for future application, establishing systematic data storage routines suitable for automated analytical tools is highly desirable as a first step. This manuscript introduces a workflow for process design, documentation within an electronic lab notebook and monitoring to supervise the product quality over time or at different locations. Lab notes, analytical data and corresponding metadata are stored in a systematic hierarchy within the research data infrastructure Kadi4Mat, which allows for continuous, flexible data structuring and access management. To support the experimental and analytical workflow, additional features were implemented to enhance and build upon the functionality provided by Kadi4Mat, including browser-based file previews and a Python tool for the combined filtering and extraction of data. The structured research data management with Kadi4Mat enables retrospective data grouping and usage by process analytical technology tools connecting individual analysis software to machine-readable data exchange formats.

Enhancing the Performance of Android

Abstract: In the present day, with the increasing popularity of the android operating system, applications being built on the Android SDK draw much attention. However, some applications built on android tend to have a cumbersome interface causing inconveniences to users. This can be reduced by eliminating the redundancies during the build of these applications. List view is commonly used in android applications to arrange a list of scrollable items in a sequential order. This consumes a considerable amount of memory and CPU utilization resulting in the degradation of the applications. One proposed solution to this can be the introduction of the RecyclerView. The RecyclerView traditionally replaces the GridView and the ListView which were previously used in android applications. This improvement is achieved by recycling the views which are out of the visibility of the user inturn enhancing both the ListView as well as the GridView. Networking in android was previously a nightmare for developers where they had to retrieve and analyze their own data. Data transfer is performed in Android applications using a Web REST API. Development speed can be enhanced by efficient data analysis by utilizing a library from the entire range of REST client libraries. REST (Representational State Transfer) has become the most commonly used way for creating, publishing, and consuming Web services, exploiting JavaScript Object Notation (JSON) as a data exchange format. The most used libraries for accessing the REST Web APIs today are Android Volley and Retrofit. An android device is hindered by limited power, memory and resources. Several architectures such as MVC(Model-View-Controller), MVP(Model-view-Presenter) and MVVM(ModelView-Viewmodel) are commonly used in the development of android applications. In order to develop applications with efficient CPU utilization, reduced memory usage and a lowered execution time, the most suitable of these architectures is to be utilized

Deep-Learning Based Fault Events Analysis in Power Systems

The identification of fault types and their locations is crucial for power system protection/operation when a fault occurs in the lines. In general, this involves a human-in-the-loop analysis to capture the transient voltage and current signals using a common format for transient data exchange for power systems (COMTRADE) file. Then, protection engineers can identify the fault types and the line locations after the incident. This paper proposes intelligent and novel methods of faulty line and location detection based on convolutional neural networks in the power system. The three-phase fault information contained in the COMTRADE file is converted to an image file and extracted adaptively by the proposed CNN, which is trained by a large number of images under various kinds of fault conditions and factors. A 500 kV power system is simulated to generate different types of electromagnetic fault transients. The test results show that the proposed CNN-based analyzer can classify the fault types and locations under various conditions and reduce the fault analysis efforts.

SpaRSE-BIM: Classification of IFC-based geometry via sparse convolutional neural networks

Information exchange between Building Information Modeling (BIM) tools is challenging, since many applications use their own native data formats. The Industry Foundation Classes (IFC) schema, an open data exchange format for BIM, does not capture the full semantic meaning needed for direct use by different BIM tools and can be prone to information loss due to reduction, simplification, translation and interpretation of the data. Current practice often treats the imported model as a reference and requires a user to remodel the building using the respective application’s native elements. Many BIM object properties are defined by its classification. Inconsistencies in the mapping between native BIM elements and IFC, e.g. due to unsupported export functionality or manual error, can lead to problems when using the model in a downstream application. Recent works demonstrate that neural networks offer a promising possibility to alleviate this issue via classification of the objects contained in a BIM model and suggesting those corrections to the user. However, the computational overhead of these deep learning models, either due to necessary pre-processing of the data or runtime performance of the model, makes it difficult for them to be used in plug-ins or middleware for BIM tools. This work proposes SpaRSE-BIM, a neural network model based on sparse convolutions for the classification of IFC-based geometry and semantic enrichment of BIM models. Experiments are performed on two IFC entity classification benchmark datasets. The results demonstrate that SpaRSE-BIM is significantly more efficient at inference time compared to previous approaches, while maintaining state-of-the-art accuracy. Further experiments explore the applicability of IFC entity classification datasets to the domain of Scan-to-BIM. It can be shown that the feature space of SpaRSE-BIM learns to discern objects in a semantically meaningful way, even in cases where fine-grained subtype information for IFC objects is not available during training.