Related papers: Demystifying Funding: Reconstructing a Unified Dat…
Despite the success of PubMed and other search engines in managing the massive volume of biomedical literature and the retrieval of individual publications, grant-related data remains scattered and relatively inaccessible. This is…
Datasets explicitly linking publications to funding at project level are the basis of evaluative bibliometric analysis of funding programmes. Analysis of the impact of the EU funding programmes has been often frustrated by the lack of data…
Funding acknowledgments in scholarly publications provide large-scale trace data on organizations that support scientific research. We present a dataset for linking global science funding organizations to research publications by…
Grant recommendation systems remain one of the least explored areas within academic recommender systems, and existing proposals are typically tied to specific funding agencies or disciplinary domains. This paper presents an…
This report introduces the Grant Maturity Index (GMI), a novel evaluative framework designed to assess the maturity and operational effectiveness of Web3 grant programs. As Web3 continues to develop, the decentralized nature of these…
Research software is crucial in the research process and the growth of Open Science underscores the importance of accessing research artifacts, like data and code, raising traceability challenges among outputs. While it is a clear principle…
The rapid expansion of blockchain and digital asset ecosystems has intensified the challenge of translating academic research into deployable systems and regulatory frameworks. While advances in cryptography, consensus, digital assets, and…
Linking research results to grants is an essential prerequisite for an effective monitoring and evaluation of funding programs. For the EU research funding programs, there are multiple datasets linking scholarly publications to the…
This article contributes to the development of methods for analysing research funding systems by exploring the robustness and comparability of emerging approaches to generate funding landscapes useful for policy making. We use a novel…
Academic Clinical Trial Units frequently face fragmented statistical workflows, leading to duplicated effort, limited collaboration, and inconsistent analytical practices. To address these challenges within an oncology Clinical Trial Unit,…
Reproducibility remains a central challenge in machine learning (ML), especially in collaborative eScience projects where teams iterate over data, features, and models. Current ML workflows are often dynamic yet fragmented, relying on…
Many research groups aspire to make data and code FAIR and reproducible, yet struggle because the data and code life cycles are disconnected, executable environments are often missing from published work, and technical skill requirements…
Knowledge-based dialogue systems with internet retrieval have recently attracted considerable attention from researchers. The dialogue systems overcome a major limitation of traditional knowledge dialogue systems, where the timeliness of…
Understanding the broad impact of science and science funding is critical to ensuring that science investments and policies align with societal needs. Existing research links science funding to the output of scientific publications but…
Scientific data governance should prioritize maximizing the utility of data throughout the research lifecycle. Research software systems that enable analysis reproducibility inform data governance policies and assist administrators in…
The circular economy has the potential to increase resource efficiency and minimize waste through the 4R framework of reducing, reusing, recycling, and recovering. Blockchain technology is currently considered a valuable aid in the…
This article provides a comprehensive systematic literature review of academic studies, industrial applications, and real-world deployments from 2018 to 2025, providing a practical guide and detailed overview of modern Retrieval-Augmented…
Research and industry are rapidly advancing the innovation and adoption of foundation model-based systems, yet the tools for managing these models have not kept pace. Understanding the provenance and lineage of models is critical for…
We present an overview of the recently funded "Merging Science and Cyberinfrastructure Pathways: The Whole Tale" project (NSF award #1541450). Our approach has two nested goals: 1) deliver an environment that enables researchers to create a…
Data mining techniques can transform massive amounts of unstructured data into quantitative data that quickly reveal insights, trends, and patterns behind the original data. In this paper, a data mining model is applied to analyse the 2019…