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A key feature of collaboration in science and software development is to have a {\em log} of what and how is being done - for private use and reuse and for sharing selected parts with collaborators, which most often today are distributed…
The integration of large language models (LLMs) with external tools has significantly expanded the capabilities of AI agents. However, as the diversity of both LLMs and tools increases, selecting the optimal model-tool combination becomes a…
Researchers in the field of materials science, chemistry, and computational physics are regularly posed with the challenge of managing large and heterogeneous data spaces. The amount of data increases in lockstep with computational…
This paper presents a modern and scalable framework for analyzing Detector Control System (DCS) data from the ATLAS experiment at CERN. The DCS data, stored in an Oracle database via the WinCC OA system, is optimized for transactional…
The Center for Expanded Data Annotation and Retrieval (CEDAR) aims to revolutionize the way that metadata describing scientific experiments are authored. The software we have developed--the CEDAR Workbench--is a suite of Web-based tools and…
The ATLAS EventIndex system comprises the catalogue of all events collected, processed or generated by the ATLAS experiment at the CERN LHC accelerator, and all associated software tools to collect, store and query this information. ATLAS…
Monitoring of the large-scale data processing of the ATLAS experiment includes monitoring of production and user analysis jobs. The Experiment Dashboard provides a common job monitoring solution, which is shared by ATLAS and CMS…
Large language models have become proficient at generating functional code, but ensuring the output truly matches the programmer's intent remains difficult. Testing improves trust, yet for safety-critical applications, formal verification…
In this paper, we summarize our effort to create and utilize a simple framework to coordinate computational analytics tasks with the help of a workflow system. Our design is based on a minimalistic approach while at the same time allowing…
With the advantages that cloud computing offers in terms of platform as a service, software as a service, and infrastructure as a service, data engineers and data scientists are able to leverage cloud computing for their ETL/ELT (extract,…
Large scientific institutions, such as the Space Telescope Science Institute, track the usage of their facilities to understand the needs of the research community. Astrophysicists incorporate facility usage data into their scientific…
The rapid acceleration of scientific publishing has created substantial challenges for researchers attempting to discover, contextualize, and interpret relevant literature. Traditional keyword-based search systems provide limited semantic…
The exponential increase in academic publications has made it increasingly difficult for researchers to remain up to date and systematically synthesize knowledge scattered across vast and fragmented research domains. Literature reviews,…
Health informatics research is characterized by diverse data modalities, rapid knowledge expansion, and the need to integrate insights across biomedical science, data analytics, and clinical practice. These characteristics make it…
Scientific workflows are powerful tools for management of scalable experiments, often composed of complex tasks running on distributed resources. Existing cyberinfrastructure provides components that can be utilized within repeatable…
Critical goals of scientific computing are to increase scientific rigor, reproducibility, and transparency while keeping up with ever-increasing computational demands. This work presents an integrated framework well-suited for data…
AI-driven autoformalization of mathematics is advancing rapidly. However, the type checker of a proof assistant guarantees only the logical correctness of proofs; it does not verify whether propositions and definitions faithfully capture…
Automated, secure software development is an important task of digitalization, which is solved with the DevSecOps approach. An important part of the DevSecOps approach is continuous risk assessment, which is necessary to identify and…
We introduce _transparent documents_, interactive web-based scholarly articles which allow readers to explore the relationship to the underlying data by hovering over fragments of text, and present an LLM-based tool for authoring…
Cloud platforms allow users to execute tasks directly from their web browser and are a key enabling technology not only for commerce but also for computational science. Research software is often developed by scientists with limited…