Editing Office

There's an imbalance in research practice. The training to become a researcher comprises nine parts technical knowledge and one part everything else. But the career of being a researcher requires nine parts publication and one part everything else. That imbalance is set right by our approach. We employ a collaborative editing methodology that develops great authors while they themselves are authoring great papers.

Dr. Daniel Shea, Textician

Motivation for Our Editing
University training too often leaves doctoral researchers unprepared to use text for research purposes. This next generation of researchers command technical expertise but are sorely underprepared to make it known through text. Here, the supervision model largely redresses that imbalance by having all sides collaborate on the same projects for everyone's professional advancement. However, the model still relies heavily on individual talent and supplementary training interventions like workshops. Consequently, junior researchers will compensate using such aids as GenAI, but when that use goes unguided, it'll harm not help a researcher's publishing outcomes.

Methodology of Our Editing

We extend the proven benefits of doctoral supervision and introduce a new collaborator to the model. Our textician — an editing linguist — is a non-author who nonetheless contributes like an author. The textician adds linguistic expertise to publications while also enhancing the publishing experience for every author on the team. Therefore, by introducing a wholly new role in the general process of publishing research, our methodology overcomes the inherent limitations of workshop-based training. Our editing methodology crosses the artificial but longstanding divide between advanced publications training and actual publishing of the research.

sheaDaniel Shea / KIT
Contact

Dr. Daniel Shea
Textician

shea does-not-exist.kit edu

scherzerRabea Strauch, KIT
Contact

Dr. Philipp Scherzer
Management

scherzer does-not-exist.kit edu

Edited Publications

Publications More Info
Fuchß et al (ICSE 2025) LiSSA: Toward Generic Traceability Link Recovery through Retrieval-Augmented Generation Link
Hamarneh et al (HSCC 2025) Trigger-Based Discretization of Hybrid Games for Autonomous Cyber-Physical Systems Link
König et al (ICMM 2025) Towards Dynamic Views on Heterogenous Models: The NeoJoin View Definition Language Link
Mazkatli et al (AuSE 2025) Continuous Integration of Architectural Performance Models with Parametric Dependencies: The CIPM Approach Link
Minhas et al (ICMM 2025) Towards a Unified Model-Based Engineering Framework: Integrating UML Profiles into EMF Link
Pascual et al (MoDEVVa 2025) Towards Examining the Complexity of Consistency TBA
Reiche et al (TSE 2025) Detecting Information Flow Security Vulnerabilities by Analysis Coupling Link
Völk et al (CIRP Design 2025) Structuring Inconsistency Situations in Engineering of Cyber-Physical Systems: A Description Template Proposal TBA
Weber et al (ECMFA 2025) Enhancing Production Workflows by Leveraging BPMN to Model Inconsistencies: An Experience Report Link