Discussion on Quality Model and Evaluation Methodology for WMS

Development and Design of an Insight Dashboard Using the Laravel Framework

The increasing demand for data-driven governance in higher education requires institutions to develop effective systems for managing, analyzing, and presenting academic information to support strategic decision-making. Conventional manual data management processes often create challenges related to data accuracy, accessibility, reporting efficiency, and institutional quality assurance. This research aims to develop an Insight Dashboard using the Laravel framework to support academic performance monitoring and improve data-based decision-making at the Quality Assurance Institute (LPM) of ITENAS Bandung. The research employed the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology, consisting of business understanding, data understanding, data preparation, modeling, evaluation, and deployment stages. The developed system integrates academic data processing and interactive visualization features to display key performance indicators, including research productivity trends, publication outputs, citation performance, indexed journal distribution, and academic unit comparisons. The results indicate that the dashboard successfully transforms institutional academic data into meaningful insights through dynamic filtering, automated calculations, and visualization components. The system presents important performance indicators, such as total publications, citation impact, publication quality levels, and research output trends, enabling stakeholders to conduct more accurate evaluations and formulate evidence-based strategies. In conclusion, the Insight Dashboard provides an effective solution for strengthening higher education quality management by facilitating continuous monitoring, improving information accessibility, and supporting sustainable data-driven institutional development. Future research may expand the system by incorporating predictive analytics and additional academic performance indicators.

Towards the Development of a Metadata-driven Usability Awareness Prototype for Interoperable GIS Operation Design

Abstract. The effective functioning of Geographic Information Systems (GIS) relies on three essential components: right data, right operations, and right results. Although challenges associated with data discovery and acquisition have lessened over time, concerns regarding data fitness for intended use and usability assessment remain prevalent. Traditionally, reliance was placed on users’ expertise in understanding the data, executing operations, and professionally interpreting outcomes. However, this conventional methodology is inadequate for managing the extensive range of unfamiliar resources currently available. From a usability perspective, this study introduces an intelligent framework based on standardized metadata design, formalized knowledge from data producers, and automated awareness mechanisms embedded within software systems. The framework aims to effectively facilitate interaction between resource providers and users concerning data usability, thereby improving the resource-sharing environment. It utilizes international standards ISO 19115 and ISO 19157 to select metadata elements relevant to usability, encompassing multiple dimensions such as the universe of discourse, qualitative and quantitative quality, and usability scenarios. This standardized metadata is rigorously analyzed in the context of the intended purposes of GIS data and operation, with a focus on incorporating usability interpretation into the design of operations. When dealing with heterogeneous data sources, this approach supports users in developing accurate comprehension and avoiding misuse, ultimately promoting interoperability and enhancing reusability.

Characterizing the Landscape of Open-Source Satellite Software

This work presents the first characterization study of open-source satellite software, examining its ecosystem and development practices, revealing a highly heterogeneous and task-specialized ecosystem with 66 programming languages and diverse implementation strategies.

An Integrated Product Service System Framework for On-Site Digital Human Guide Systems

On-site digital human guide systems, which integrate intelligent interactive technologies with guidance, interpretation, and information services, are emerging as an important form of intelligent on-site service. However, existing knowledge remains largely fragmented across technological configurations, interaction modalities, application contexts, and user experience objectives, lacking an integrated cross-dimensional analytical perspective that explains how these systems create and deliver value. To address this gap, this paper aims to adopt a Product–Service Systems (PSS) perspective to systematically examine the development of on-site digital human guide systems. Specifically, it explores their product–service configurations, service delivery modes and user participation, and artificial intelligence (AI) capability integration pathways, while identifying the value creation opportunities and challenges associated with system development and continuous optimization. The PSS paradigm offers such an integrative lens, which has gained renewed relevance as the Fourth Industrial Revolution (Industry 4.0) accelerates the servitization and digital transformation of traditional services. This paper conducts a scoping review employing content analysis based on a structured cross-database search across Google Scholar, Scopus, and Web of Science, supplemented by snowball sampling, covering 40 studies, including 34 deployed projects. The findings reveal that: (1) on-site digital human guide systems can be categorized into four product–service configurations: fixed terminal (stationary dialogue); mobile terminal (location-aware guidance); Head-Mounted Display/Mixed Reality (immersive experience); and robot (full-process mobile service). The selection of these configurations is shaped by spatial characteristics, target user group, and institutional operational conditions; (2) a user behavior taxonomy of nine active and five passive types was developed, demonstrating that user participation patterns are jointly shaped by control allocation in service delivery and the social behavior design of digital humans, with users showing a preference for controllable and interruptible engagement; (3) AI integration has evolved from rule-and-script-driven approaches to modular AI integration, and subsequently to large language model (LLM)/Retrieval-Augmented Generation (RAG)-driven architectures, with corresponding design implications proposed; and (4) challenges were classified into four major categories and 26 subcategories across three digital transformation stages. The contribution of this paper lies in the development of an integrated PSS analytical framework for on-site digital human guide systems, spanning product, service, and AI integration layers. The framework provides a multi-layer analytical lens for understanding system configurations, user participation, technological evolution, and implementation challenges, while offering structured guidance for configuration and service selection, system design, and continuous optimization across diverse deployment contexts. These findings provide practical implications for researchers and practitioners seeking to design, deploy, and optimize on-site digital human guide systems across diverse service environments.

Electronic Research

Geospatial Technology as Integrated Decision Infrastructure: Applications, Persistent Challenges and Future Directions

It is argued that future progress depends less on incremental accuracy gains than on reproducible multi-source workflows, explicit uncertainty, trustworthy and explainable geospatial artificial intelligence, privacy-preserving governance, interoperable standards and evaluation in the institutions that ultimately use the evidence.