Related papers: Identifying and extracting Data Access Statements …
The rapid integration of generative AI into scientific research has exposed a critical gap in academic disclosure practice. Existing frameworks for reporting AI contributions are uniformly output-oriented -- they document what AI produced,…
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…
This contribution will show how Access play a strong role in the creation and structuring of DARIAH, a European Digital Research Infrastructure in Arts and Humanities.To achieve this goal, this contribution will develop the concept of…
As research and industry moves towards large-scale models capable of numerous downstream tasks, the complexity of understanding multi-modal datasets that give nuance to models rapidly increases. A clear and thorough understanding of a…
Metadata extraction is essential for cataloging and preserving datasets, enabling effective research discovery and reproducibility, especially given the current exponential growth in scientific research. While Masader (Alyafeai et al.,2021)…
In the past decade, deep learning (DL) has achieved unprecedented success in numerous fields including computer vision, natural language processing, and healthcare. In particular, DL is experiencing an increasing development in applications…
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 number of scientific articles has grown rapidly over the years and there are no signs that this growth will slow down in the near future. Because of this, it becomes increasingly difficult to keep up with the latest developments in a…
The availability of large data sets is providing an impetus for driving current artificial intelligent developments. There are, however, challenges for developing solutions with small data sets due to practical and cost-effective deployment…
Over the past decade, the Table Union Search (TUS) task has aimed to identify unionable tables within data lakes to improve data integration and discovery. While numerous solutions and approaches have been introduced, they primarily rely on…
Over the past two decades, every scholarly publisher has migrated at least the mechanical aspects of their journal publishing so that they utilize digital means. The academy was comfortable with that for a while, but publishers are under…
This report provides practical guidance to teams designing or developing AI-enabled systems for how to promote trustworthiness during the data curation phase of development. In this report, the authors first define data, the data curation…
The use of AI tools in research is becoming routine, alongside growing consensus that such use should be transparently disclosed. However, AI disclosure statements remain rare and inconsistent, with policies offering limited guidance and…
Nowadays, a large amount of user privacy-sensitive data is outsourced to the cloud server in ciphertext, which is provided by the data owners and can be accessed by authorized data users. When accessing data, the user should be assigned…
This paper proposes OCR++, an open-source framework designed for a variety of information extraction tasks from scholarly articles including metadata (title, author names, affiliation and e-mail), structure (section headings and body text,…
Domain-specific named entity recognition (NER) on Computer Science (CS) scholarly articles is an information extraction task that is arguably more challenging for the various annotation aims that can beset the task and has been less studied…
To meet the standards of the Open Science movement, the FAIR Principles emphasize the importance of making scientific data Findable, Accessible, Interoperable, and Reusable. Yet, creating a repository that adheres to these principles…
We aim to renew interest in a particular multi-document summarization (MDS) task which we call AgreeSum: agreement-oriented multi-document summarization. Given a cluster of articles, the goal is to provide abstractive summaries that…
Standardizing and incentivizing the use of digital object identifiers (DOIs) to aggregate and identify both data analyzed and data generated by a research project will advance the field of astronomy to match best practices in other research…
An essential part of research and scientific communication is researchers' ability to reproduce the results of others. While there have been increasing standards for authors to make data and code available, many of these files are hard to…