Related papers: Eprints and the Open Archives Initiative
Open source projects have made incredible progress in producing transparent and widely usable machine learning models and systems, but open source alone will face challenges in fully democratizing access to AI. Unlike software, AI models…
Metadata management plays a critical role in data governance, resource discovery, and decision-making in the data-driven era. While traditional metadata approaches have primarily focused on organization, classification, and resource reuse,…
The Open Databases Integration for Materials Design (OPTIMADE) consortium has designed a universal application programming interface (API) to make materials databases accessible and interoperable. We outline the first stable release of the…
The development of privacy-enhancing technologies has made immense progress in reducing trade-offs between privacy and performance in data exchange and analysis. Similar tools for structured transparency could be useful for AI governance by…
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…
Annotations allow users to associate additional information with existing resources. Using proprietary and closed systems on the Web, users are already able to annotate multimedia resources such as images, audio and video. So far, however,…
Differences between the impacts of Open Access (OA) and non-OA research have been observed over a wide range of citation and altmetric indicators, usually finding an Open Access Advantage (OAA) within specific fields. However, science-wide…
With the rapid evolution of metaverse technologies, numerous metaverse applications have arisen for various purposes and scenarios. This makes interoperability across metaverses becomes one of the fundamental technology enablers in the…
We describe the "Fair Dealing Button," a feature designed for authors who have deposited their papers in an Open Access Institutional Repository but have deposited them as "Closed Access" (meaning only the metadata are visible and…
Smart Services using Industrial Internet of Things (IIoT) applications are on the rise, but still more often than not, traditional industrial protocols are used to interconnect the entities of the resulting systems. These protocols are…
This article describes how technical infrastructure developed by the nonprofit OpenMined enables external scrutiny of AI systems without compromising sensitive information. Independent external scrutiny of AI systems provides crucial…
Metadata, often termed "data about data," is crucial for organizing, understanding, and managing vast omics datasets. It aids in efficient data discovery, integration, and interpretation, enabling users to access, comprehend, and utilize…
Open Information Extraction (OIE) is a structured prediction (SP) task in Natural Language Processing (NLP) that aims to extract structured $n$-ary tuples - usually subject-relation-object triples - from free text. The word embeddings in…
CERN, the European Organization for Nuclear Research, has operated an institutional preprint repository for more than 10 years. The repository contains over 850,000 records of which more than 450,000 are full-text OA preprints, mostly in…
The Internet of Things (IoT) envisions that objects may be connected to the Internet, producing and consuming data in real-time. Today, numerous middleware platforms are available to facilitate the communication with these objects.…
The implementation of policies promoting the adoption of an Open Science culture must be accompanied by indicators that allow monitoring the penetration of such policies and their potential effects on research publishing and sharing…
Over the last decades, the amount of data of all kinds available electronically has increased dramatically. Data are accessible through a range of interfaces including Web browsers, database query languages, application-specific interfaces,…
This paper introduces a no-code, machine-readable documentation framework for open datasets, with a focus on responsible AI (RAI) considerations. The framework aims to improve comprehensibility, and usability of open datasets, facilitating…
Model documentation plays a crucial role in promoting transparency and responsible development of AI systems. With the rise of Generative AI (GenAI), open-source platforms have increasingly become hubs for hosting and distributing these…
Sharing clinical research data is key for increasing the pace of medical discoveries that improve human health. However, concern about study participants' privacy, confidentiality, and safety is a major factor that deters researchers from…