Related papers: A Comprehensive Approach to Ensuring Quality in Sp…
As Large Language Models (LLMs) become integral to scientific workflows, concerns over the confidentiality and ethical handling of confidential data have emerged. This paper explores data exposure risks through LLM-powered scientific tools,…
Knowledge about data completeness is essentially in data-supported decision making. In this thesis we present a framework for metadata-based assessment of database completeness. We discuss how to express information about data completeness…
Data is a precious resource in today's society, and is generated at an unprecedented and constantly growing pace. The need to store, analyze, and make data promptly available to a multitude of users introduces formidable challenges in…
This article evaluates the quality of data collection in individual-level desktop information tracking used in the social sciences and shows that the existing approaches face sampling issues, validity issues due to the lack of content-level…
High-quality, "rich" metadata are essential for making research data findable, interoperable, and reusable. The Center for Expanded Data Annotation and Retrieval (CEDAR) has long addressed this need by providing tools to design…
The scientific literature is growing faster than ever. Finding an expert in a particular scientific domain has never been as hard as today because of the increasing amount of publications and because of the ever growing diversity of…
Data is of high quality if it is fit for its intended use. The quality of data is influenced by the underlying data model and its quality. One major quality problem is the heterogeneity of data as quality aspects such as understandability…
To aid the development of spreadsheet debugging tools, a knowledge of end-users natural behaviour within the Excel environment would be advantageous. This paper details the design and application of a novel data acquisition tool, which can…
While automated experiments and high-throughput methods are becoming more mainstream in the age of data, empowering individual researchers to capture, collate, and contextualize their data faster and more reproducibly still remains a…
This paper presents a framework for assessing data and metadata quality within Open Data portals. Although a few benchmark frameworks already exist for this purpose, they are not yet detailed enough in both breadth and depth to make valid…
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 rapid expansion of scholarly publications across diverse disciplines has made it increasingly difficult to systematically evaluate how research contributes to the United Nations Sustainable Development Goals (SDGs). Domain…
Usability is a key quality attribute of successful software systems. Unfortunately, there is no common understanding of the factors influencing usability and their interrelations. Hence, the lack of a comprehensive basis for designing,…
Incorporating metadata in Large Language Models (LLMs) pretraining has recently emerged as a promising approach to accelerate training. However prior work highlighted only one useful signal-URLs, leaving open the question of whether other…
In High Energy Physics (HEP), analysis metadata comes in many forms -- from theoretical cross-sections, to calibration corrections, to details about file processing. Correctly applying metadata is a crucial and often time-consuming step in…
Currently, there are many difficulties regarding the interoperability of medical data and related population data sources. These complications get in the way of the generation of high-quality data sets at city, region and national levels.…
Data management tasks require access to metadata, which is increasingly tracked by databases called data catalogs. Current catalogs are too dependent on users' understanding of data, leading to difficulties in large organizations of users…
Data intensive research requires the support of appropriate datasets. However, it is often time-consuming to discover usable datasets matching a specific research topic. We formulate the dataset discovery problem on an attributed…
Research data are often released upon journal publication to enable result verification and reproducibility. For that reason, research dissemination infrastructures typically support diverse datasets coming from numerous disciplines, from…
Data quality is vital for user experience in products reliant on data. As solutions for data quality problems, researchers have developed various taxonomies for different types of issues. However, although some of the existing taxonomies…