Digital Library of Gesellschaft für Informatik e.V.
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Beyond Big Data — The Ocient Hyperscale Data Warehouse
No full textThe Ocient Hyperscale Data Warehouse is a massively parallel processing (MPP) system designed to efficiently store and analyze petabyte-scale datasets. Ocient utilizes a compute-adjacent storage architecture (CASA), where storage and compute resources are co-located to minimize data movement, thus enhancing query performance. We present the system architecture and dive deeper into data storage in segments, which do not only store columnar table data but also index information. This design, combined with parallel query processing, allows for high throughput and low-latency execution. Beyond that, the paper highlights OcientGeo – deeply integrated data types for geospatial analytics – as well as OcientML – a machine learning integration for running analytics and model training directly inside the database system. These features expand the system’s utility across diverse industries and applications
Requirements Classification for Traceability Link Recovery
No full textThe paper assesses the potential of requirements classification approaches to identify parts of requirements that are irrelevant for automated traceability link recovery between requirements and code. We were able to show that automatic identification of parts of requirements that do not describe functional aspects can significantly improve the recovery performance and that the parts can be identified with an F1-score of 84 %
CommunityMirrors – Semi-Public Information Radiators for Knowledge Workers
No full textOur daily work in the information society relies on creating, editing and collecting different information objects. Without additional presentation mechanisms these activities of particular knowledge workers remain hidden in the underlying IT sys-tems. The resulting lack of awareness can lead to inefficient coordination as well as to the duplication of work in the worst case. Information Radiators are large displays providing context-specific pieces of information in a semi-public setting where people can see it while working or passing-by. They have a long history originating from simple printed posters for agile project management and software development, over interactive versions on large touch displays in the early 2000s to complex situated sociotechnically integrated multi-user multi-device interaction spaces for knowledge workers in recent years. By augmenting the physical working environment with pe-ripherally recognizable digital content Interactive Information Radiators (IIRs) can simplify information sharing "out-of-the-box", foster awareness and socialization, create serendipity and enhance collaboration. In this report we present Communi-tyMirrors as one potential solution to this problem. CommunityMirrors are an exam-ple for information radiators and discussed in detail within this work. We describe the start of the project and elaborate on the work done in the past 20+ years covering different phases from first experiments to setting up a long-term deployment and providing support for evaluation in this deployment
Workflow for Creating and Sealing a Research Data Management Container (RDMC)
No full textThis paper describes the process of creating a Research Data Management Container (RDMC) from NFDIxCS . The RDMC encapsulates data, software components, and its context, allowing it to be published as a standalone artifact or alongside a paper/publication. Based on user stories, a workflow was developed to create and seal the RDMC. During the creation of the RDMC, a manifest file is provided to describe the architecture and relevant metadata of the container, and security information to be included in the sealing process. Two different approaches are proposed for sealing the RDMC. The development of the RDMC is still in its early stages, as it is paving the way for further research in the management of Research Data and Software
Analyse und Bewältigung von Herausforderungen im Software-Prototyping: Eine Untersuchung der Schlüsseldimensionen zur Unterstützung der Digitalen Transformation
No full textSoftware-Prototyping von Informationssystemen ermöglicht die frühzeitige Entwicklung von Demonstratoren zur schnellen Integration von Nutzerfeedback, das für die digitale Transformation und organisatorische Veränderungen entscheidend ist. Trotz zahlreicher Vorteile treten bei der Anwendung der Methode Herausforderungen auf, welche sich auch auf die Integration und Verwaltung von Enterprise Systems auswirken. Die Identifizierung von diesen Herausforderungen beim Software-Prototyping ist grundlegend, um Misserfolge bei der Entwicklung innovativer Prototypen zu vermeiden. Mit diesem Beitrag werden fünf Schlüsseldimensionen – Technologie, Organisation, Datenmanagement, Entwicklungsprozess und Benutzererfahrung – durch die Analyse von 39 identifizierten Herausforderungen in 13 Kategorien untersucht. Darüber hinaus zeigen die Ergebnisse, dass in dem achtstufigen Software-Prototyping-Prozess die Phase des User Interface Prototyping die häufigsten Probleme aufweist. Ziel ist es, mögliche Probleme zu identifizieren und zu kategorisieren sowie Handlungsempfehlungen daraus abzuleiten, um ein Bewusstsein für solche zu schaffen, damit Strategien zur digitalen Transformation besser umgesetzt werden können. Software prototyping in information systems enables the early development of prototypes for the rapid integration of user feedback which is crucial for digital transformation and organisational changes. Despite numerous advantages, issues arise when using the method—also affecting the integration and management of enterprise systems. Identifying issues in software prototyping is important to prevent failures in the development of innovative prototypes. This study examines five key dimensions—technology, organisation, data management, development process and user experience—by analysing 39 identified issues in 13 categories. Furthermore, findings show that in the eight-stage software prototyping process, the user interface prototyping phase has the most frequent issues. This research aims to identify and categorise possible issues as well as to derive recommendations for action to clarify these and create awareness of such for better digital transformation strategies
Microlearning als nachhaltige Lernmethode zum Erwerb digitaler Kompetenzen an den Fachschulen für Landwirtschaft
No full textIn der modernen Landwirtschaft nimmt die Digitalisierung eine zunehmend zentrale Rolle ein. Um Betriebsleitende in die Lage zu versetzen, fundierte Entscheidungen auf Basis großer Datenmengen aus Maschinen, Sensoren und Satelliten oder Drohnen zu treffen, benötigen Studierende der Fachschulen für Landwirtschaft verstärkt Kompetenzen aus anderen Domänen. Allerdings werden diese in den meisten Lehrplänen bisher unzureichend berücksichtigt. Statt als Kernkompetenz der landwirtschaftlichen Fortbildung werden digitale Fähigkeiten oft nur als ergänzende Inhalte vermittelt, abhängig von der individuellen Qualifikation der Lehrkräfte. Diese Lücke hat signifikante Auswirkungen auf die Qualität der beruflichen Weiterbildung und die digitale Transformationsfähigkeit der Betriebe
Benchmarking the RDF and Property Graph Model in the Temporal Dimension — A Case Study with Finbench
No full textTemporal graph data is highly relevant for capturing the evolving nature of various domains, including financial transactions, social network interactions, supply chain logistics, disease outbreak modeling, and dynamic transportation systems. In this work, we benchmark the performance of temporal data representations in the property graph model (PGM) and RDF model using the FinBench transaction workload. Our contributions are twofold. First, we adapt the FinBench data generator to produce RDF datasets in two formats: (1) the RDF-Reification representation and (2) the RDF-Star extension. Second, we provide queries for three new databases: Memgraph (PGM) and two RDF databases, Virtuoso and GraphDB, with only the latter offering RDF-Star support. Our findings highlight key challenges in representing FinBench data in RDF, like missing functions of the SPARQL language in addressing certain query requirements. These insights provide valuable guidance for query writing and optimizing RDF-based representations for temporal graph workloads
Aufruf zur Einreichung: Deutscher Preis für Software-Qualität 2025
No full textAufruf zur Einreichung: Deutscher Preis für Software-Qualität 202