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In a decentralized household energy system consisting of various devices such as washing machines, heat pumps, and solar panels, understanding the electric energy consumption and production data at the granularity of the device helps…
Reproducing experiments is an important instrument to validate previous work and build upon existing approaches. It has been tackled numerous times in different areas of science. In this paper, we introduce an empirical replicability study…
Rapid growth of documents, web pages, and other types of text content is a huge challenge for the modern content management systems. One of the problems in the areas of information storage and retrieval is the lacking of semantic data.…
Robot behavior is often validated through simulation-based testing, yet the replicability of such campaigns depends critically on transparent documentation of how tests are configured, executed, and post-processed. We argue that data…
The vision of the Semantic Web is becoming a reality with billions of RDF triples being distributed over multiple queryable end-points (e.g. Linked Data). Although there has been a body of work on RDF triples persistent storage, it seems…
Microbiology research has access to a very large amount of public information on the habitats of microorganisms. Many areas of microbiology research uses this information, primarily in biodiversity studies. However the habitat information…
Recent reproducibility case studies have raised concerns showing that much of the deposited research has not been reproducible. One of their conclusions was that the way data repositories store research data and code cannot fully facilitate…
Accountability is widely understood as a goal for well governed computer systems, and is a sought-after value in many governance contexts. But how can it be achieved? Recent work on standards for governable artificial intelligence systems…
Data centers have significant energy needs, both embodied and operational, affecting sustainability adversely. The current techniques and tools for collecting, aggregating, and reporting verifiable sustainability data are vulnerable to…
The trend toward open science increases the pressure on authors to provide access to the source code and data they used to compute the results reported in their scientific papers. Since sharing materials reproducibly is challenging, several…
Reproducibility should be a cornerstone of science as it enables validation and reuse. In recent years, the scientific community and the general public became increasingly aware of the reproducibility crisis, i.e. the wide-spread inability…
Although reproducibility is a core tenet of the scientific method, it remains challenging to reproduce many results. Surprisingly, this also holds true for computational results in domains such as systems biology where there have been…
In recent years, the importance of well-documented metadata has been discussed increasingly in many research fields. Making all metadata generated during scientific research available in a findable, accessible, interoperable, and reusable…
How many times have you tried to re-implement a past CAV tool paper, and failed? Reliably reproducing published scientific discoveries has been acknowledged as a barrier to scientific progress for some time but there remains only a small…
We study linear-time temporal logics interpreted over data words with multiple attributes. We restrict the atomic formulas to equalities of attribute values in successive positions and to repetitions of attribute values in the future or…
Motivation: The rapid growth of biological data has intensified the need for transparent, reproducible, and well-documented computational workflows. The ability to clearly connect the steps of a workflow in the code with their description…
In engineering projects involving various parts from global suppliers, one common task is to determine which parts are best suited for the project requirements. Information about specific parts' characteristics is published in so called…
Computational reproducibility is central to scientific credibility, yet verifying published results at scale remains costly. We develop an AI-assisted workflow for automated full-paper replication -- retrieving materials, reconstructing…
The ever-increasing amount of data in biomedical research, and in cancer research in particular, needs to be managed to support efficient data access, exchange and integration. Existing software infrastructures, such caGrid, support access…
Across the natural and life sciences, images have become a primary measurement modality, yet the dominant analytic paradigm remains semantics-first. Structure is recovered by predicting or enforcing domain-specific labels. This paradigm…