Related papers: The OAI Data-Provider Registration and Validation …

Numerous institutions and organizations need not only to preserve the material and publications they produce, but also have as their task (although it would be desirable it was an obligation) to publish, disseminate and make publicly…

The PASTEUR4OA project analyses what makes an Open Access (OA) policy effective. The total number of institutional or funder OA policies worldwide is now 663 (March 2015), over half of them mandatory. ROARMAP, the policy registry, has been…

In reaction to growing concerns about the potential harms of artificial intelligence (AI), societies have begun to demand more transparency about how AI models and systems are created and used. To address these concerns, several efforts…

OAuth protocols have been widely adopted to simplify user authentication and service authorization for third-party applications. However, little effort has been devoted to automatically checking the security of the libraries that service…

Knowing more about the data used to build AI systems is critical for allowing different stakeholders to play their part in ensuring responsible and appropriate deployment and use. Meanwhile, a 2023 report shows that data transparency lags…

Purpose: As surgery increasingly integrates advanced imaging, algorithms, and robotics to automate complex tasks, human judgment of system correctness remains a vital safeguard for patient safety. A critical example is 2D/3D registration,…

With generative AI becoming widespread, the existence of AI-based programming assistants for developers is no surprise. Developers increasingly use them for their work, including generating code to fulfil the data protection requirements…

The Virtual Observatory Registry is a distributed directory of information systems and other resources relevant to astronomy. To make it useful, facilities to query that directory must be provided to humans and machines alike. This article…

Recent years have seen fast growth in the number of policies mandating Open Access (OA) to research outputs. We conduct a large-scale analysis of over 800 thousand papers from repositories around the world published over a period of 5 years…

What makes safety claims about general purpose AI systems such as large language models trustworthy? We show that rather than the capabilities of security tools such as alignment and red teaming procedures, it is security practices based on…

Reliable and trustworthy evaluation of algorithms is a challenging process. Firstly, each algorithm has its strengths and weaknesses, and the selection of test instances can significantly influence the assessment process. Secondly, the…

Artificial intelligence (AI) has been advancing at a fast pace and it is now poised for deployment in a wide range of applications, such as autonomous systems, medical diagnosis and natural language processing. Early adoption of AI…

Document redaction in public authorities faces critical challenges as traditional manual approaches struggle to balance growing transparency demands with increasingly stringent data protection requirements. This study investigates the…

Registries provide a mechanism with which VO applications can discover and select resources--e.g. data and services--that are relevant for a particular scientific problem. This specification defines the interfaces that support interactions…

The education technology (EdTech) landscape is expanding rapidly in higher education institutes (HEIs). This growth brings enormous complexity. Protecting the extensive data collected by these tools is crucial for HEIs as data breaches and…

This study aims to analyze the vital role played by the Digital Object Identifier (DOI) in enhancing the credibility and reliability of scientific research in the digital age. Through an analytical study of DOI usage data derived from…

AI services are known to have unstable behavior when subjected to changes in data, models or users. Such behaviors, whether triggered by omission or commission, lead to trust issues when AI works with humans. The current approach of…

Instances of Artificial Intelligence (AI) systems failing to deliver consistent, satisfactory performance are legion. We investigate why AI failures occur. We address only a narrow subset of the broader field of AI Safety. We focus on AI…

The rapid entry of machine learning approaches in our daily activities and high-stakes domains demands transparency and scrutiny of their fairness and reliability. To help gauge machine learning models' robustness, research typically…

The proliferation of the Open Archive Initiative Protocol for Metadata Harvesting (OAI-PMH) has resulted in the creation of a large number of service providers, all harvesting from either data providers or aggregators. If data were…