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Many research questions can be answered quickly and efficiently using data already collected for previous research. This practice is called secondary data analysis (SDA), and has gained popularity due to lower costs and improved research…
In recent years, numerous domain adaptive strategies have been proposed to help deep learning models overcome the challenges posed by domain shift. However, even unsupervised domain adaptive strategies still require a large amount of target…
According to the FAIR (findability, accessibility, interoperability, and reusability) principles, scientific data should always be stored with machine-readable descriptive metadata. Existing solutions to store data with metadata, such as…
We highlight here several solutions developed to make high-level Cherenkov data FAIR: Findable, Accessible, Interoperable and Reusable. The first three FAIR principles may be ensured by properly indexing the data and using community…
Many recent caching systems aim to improve miss ratios, but there is no good sense among practitioners of how much further miss ratios can be improved. In other words, should the systems community continue working on this problem?…
The notion of a Fast Moving Object (FMO), i.e. an object that moves over a distance exceeding its size within the exposure time, is introduced. FMOs may, and typically do, rotate with high angular speed. FMOs are very common in sports…
Advances in lightweight neural networks have revolutionized computer vision in a broad range of IoT applications, encompassing remote monitoring and process automation. However, the detection of small objects, which is crucial for many of…
Unequivocally, a single man in possession of a strong password is not enough to solve the issue of security. Studies indicate that passwords have been subjected to various attacks, regardless of the applied protection mechanisms due to the…
Recently the International Virtual Observatory Alliance (IVOA) released a standard to structure provenance metadata, and several implementations are in development in order to capture, store, access and visualize the provenance of astronomy…
Over the past few years, the YOLO series of models has emerged as one of the dominant methodologies in the realm of object detection. Many studies have advanced these baseline models by modifying their architectures, enhancing data quality,…
A large number of services for research data management strive to adhere to the FAIR guiding principles for scientific data management and stewardship. To evaluate these services and to indicate possible improvements, use-case-centric…
The principles of data spaces for sovereign data exchange across trusted organizations have so far mainly been adopted in business-to-business settings, and recently scaled to cloud environments. Meanwhile, research organizations have…
The availability of open data and of tools to create visualizations on top of these open datasets have led to an ever-growing amount of geovisualizations on the Web. There is thus an increasing need for techniques to make geovisualizations…
It is essential for the advancement of science that scientists and researchers share, reuse and reproduce workflows and protocols used by others. The FAIR principles are a set of guidelines that aim to maximize the value and usefulness of…
In an era dominated by information technology, the critical discipline of data management remains undervalued compared to the innovations it enables, such as artificial intelligence and social media. The ambiguity surrounding what…
Fast Identity Online 2 (FIDO2), a modern authentication protocol, is gaining popularity as a default strong authentication mechanism. It has been recognized as a leading candidate to overcome limitations (e.g., it is phishing resistant) of…
The ability to find data is central to the FAIR principles underlying research data stewardship. As with the ability to reuse data, efforts to ensure and enhance findability have historically focused on discoverability of data by other…
Recent years have seen the rapid development of fairness-aware machine learning in mitigating unfairness or discrimination in decision-making in a wide range of applications. However, much less attention has been paid to the fairness-aware…
Research methods and procedures are core aspects of the research process. Metadata focused on these components is critical to supporting the FAIR principles, particularly reproducibility. The research reported on in this paper presents a…
Federated Domain Adaptation (FDA) is a federated learning (FL) approach that improves model performance at the target client by collaborating with source clients while preserving data privacy. FDA faces two primary challenges: domain shifts…