Digital Library of Gesellschaft für Informatik e.V.
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A Use Case and Method for Migrating a Low Code Business Information System to a Custom Three Tier Application
No full textNon-trained software engineers are able to rapidly develop productive software applications using low code platforms. Those platforms offer ease of use, compared to classical software development and operation environments. However, when software needs to be heavily customized, the advantage of standardization is replaced by the complexity of customizing. In this paper, we present an industry use case and our method for transforming a low code information system into a custom three-tier architecture
Semantic technologies for interdisciplinary research: A case study on improving data synthesis and integration in the biodiversity domain
No full textIn biodiversity research, synthesizing data from different sources is frequently needed as a prerequisite to answering important questions. Performing this synthesis and integrating one's own research data remains a tedious process requiring significant human effort. Often, the results of these efforts are not easily reusable for other questions. Knowledge graphs have been proposed in the literature as an approach to alleviate this problem, in part through their inherent adherence to the FAIR data principles, but have gained little traction in biodiversity research practice so far due to significant challenges in knowledge graph construction and usage by non-domain experts. Our contribution showcases an approach and tools needed for knowledge graph creation, management, and usage implemented in the context of PlantHub and the former iKNOW project. We present a knowledge graph combining plant trait sources within the PlantHub project (planthub.idiv.de) including preprocessed data from TRY, a plant trait database, with citizen science occurrence data from naturgucker.de and add taxonomic and additional information from multiple sources (e.g. Wikidata, GBIF, OpenElevation,...). We present the workflow needed to create such a graph and show different options for its management using features from Ontotext Refine for data cleaning, API \& URL fetching, RDF mapping and export, and Ontotext GraphDB for hosting, querying, and visualization. To simplify usage of this graph, we showcase a query builder interface that allows users to construct SPARQL queries without needing any prior domain knowledge. We motivate our work and its application in the biodiversity research domain and contribute to bridging the gap towards using semantic technologies in this field of research
Security awareness versus secure behaviour: A bibliometric study of the state of research on human factors in IT Security
No full textThis bibliometric analysis examines the evolving role of human behavior and IT practices in shaping cybersecurity research and strategies. By leveraging VOSviewer, we analyse a comprehensive dataset of Scopus articles to explore key themes, keyword co-occurrence, and the intersection between human vulnerabilities and technological solutions. Our findings reveal a persistent gap in addressing the human factor, with keywords such as 'human error,' 'social engineering,' and 'awareness' frequently emerging as critical vulnerabilities. The analysis also highlights the inadequate integration of human-centric solutions by IT professionals, as evidenced by weak connections between 'employee awareness,' 'cyber hygiene,' and 'cybersecurity culture.' Despite advancements in technology, the study underscores that cybersecurity's effectiveness is often compromised by human behavior, suggesting a need for deeper engagement with user training, organizational culture, and behavioral change. This bibliometric analysis contributes to understanding the critical blind spots in cybersecurity research, offering valuable insights into the overlooked relationship between human behavior and IT practices in safeguarding digital infrastructures
Poster: Dynamic Write-Mode Fragmentation for Non-Volatile Memory Simulation
No full textDisruptive memory technology development leads to a wide landscape of novel memory properties. Specifically, with the possibility to utilize multiple write modes for the tradeoff of energy consumption and retention time, the system software and applications can optimize the energy consumption of the memory while ensuring guarantees for memory retention. Deriving online and offline strategies for such optimization requires precise simulation of memory write modes across the memory area. This paper enables the simulation of such write-mode fragmentation for the NVMain2.0 simulator in a static and dynamic configuration fashion
ODDA: Ontology-Driven Data Acquisition
No full textOntologies are powerful tools for structuring and formalizing knowledge and enabling interoperability. They play a crucial in research data management by making data machine-interpretable and facilitating the integration of diverse datasets from various researchers. Ideally, the integrated datasets contribute to global use cases aimed at inferring new knowledge. To achieve this, it is essential that researchers align the data collected for their local use cases with existing domain ontologies. However, the data needs for local use cases might not readily fit into these domain ontologies without further adaptation. As a consequence, researchers often refrain from reusing the ontologies and collect their local data on an ad hoc basis using improvised schemas. We surveyed current approaches to ontology-based data acquisition, revealing that while some methods exist for generating forms from ontologies, there are currently no significant approaches that enable researchers to customize these ontologies to fit their individual needs. To address this gap, we developed a prototype aimed at exploring the challenges of adapting ontologies for specific use cases. Our form-based approach empowers researchers to reuse ontologies without requiring substantial expertise in ontology engineering. This prototype allows researchers to define ontology-based data collection forms tailored to their specific needs, ultimately generating ontology-compliant knowledge graphs from the collected data
Auswirkungen von KI, Rechenzentren und Halbleitern auf Wasserverfügbarkeit und -Qualität
No full textExperiences with Combining Proactive with Retroactive Feature Traces
No full textReverse engineering feature traces is crucial to systematically support organized reuse in evolving highly configurable software systems. A feature represents a user-visible characteristic of the software which allows for its configuration and may be mapped onto almost all artifacts in a software system. Consequently, variable parts can optionally be included or excluded from variants of the software system. Methods to build feature traces, which establish a mapping between features and software artifacts, range from purely manual to fully automated techniques. Feature traces can be built proactively during development or retroactively recovered mainly based on heuristics. In a published study, we examined how minimal seeds of proactive traces can increase the accuracy of a retroactive feature tracing method. In this article, we summarize the key findings and outline actions and research directions following up on the published experiment
BPM Research is Finally Maturing (Right?)
No full textThe Business Process Management (BPM) field is characterized by its interdisciplinary nature and small close-knit community. While these aspects foster collaboration and intellectual diversity, they also pose challenges related to visibility and positioning within the broader academic landscape. This opinion piece, accompanying an EMISA 2025 keynote, reflects on recent developments that are helping to strengthen and future-proof BPM research. It highlights three promising directions: (1) initiatives that connect BPM to other research communities and break disciplinary silos, (2) growing attention to sound and transparent research methodology, and (3) community-building efforts that foster cohesion and support. By drawing attention to these trends, the article aims to encourage broader engagement and recognize the individuals and initiatives driving positive change
Erfahrungsberichte über die Transformation der Requirements Engineering-Lehre in Zeiten von Künstlicher Intelligenz
No full textDurch Künstliche Intelligenz (KI) und besonders vortrainierte Large Language Modelle (LLM) wird sich das Requirements Engineering zukünftig massiv verändern. Wir berichten hier über Änderungen, die wir an unserer Lehre bereits vorgenommen haben und weiterhin planen, um diesen Veränderungen gerecht zu werden und die Studierenden auf die neue Form des Requirements Engineering und Software Engineering vorzunehmen