Related papers: A Comprehensive Approach to Ensuring Quality in Sp…

Scientists increasingly recognize the importance of providing rich, standards-adherent metadata to describe their experimental results. Despite the availability of sophisticated tools to assist in the process of data annotation,…

Advances in technology and computing hardware are enabling scientists from all areas of science to produce massive amounts of data using large-scale simulations or observational facilities. In this era of data deluge, effective coordination…

Thanks to their flexibility and capability to perform different tasks and organize data in the best form and format, spreadsheets are widely used in different organizations and by different end users. Many business organizations rely on…

Thanks to the enormous flexibility they provide, spreadsheets are considered a priceless blessing by many end-users. Many spreadsheets, however, contain errors which can lead to severe consequences in some cases. To manage these risks,…

High-quality datasets are fundamental to training and evaluating machine learning models, yet their creation-especially with accurate human annotations-remains a significant challenge. Many dataset paper submissions lack originality,…

Data warehousing is continuously gaining importance as organizations are realizing the benefits of decision oriented data bases. However, the stumbling block to this rapid development is data quality issues at various stages of data…

The widespread adoption of big data has ushered in a new era of data-driven decision-making, transforming numerous industries and sectors. However, the efficacy of these decisions hinges on the quality of the underlying data. Poor data…

Spreadsheets are powerful tools which play a business-critical role in many organizations. However, many bad decisions taken due to faulty spreadsheets show that these tools need serious quality assurance. Furthermore, while collaboration…

Metadata are critical in epidemiological and public health research. However, a lack of biomedical metadata quality frameworks and limited awareness of the implications of poor quality metadata renders data analyses problematic. In this…

Spreadsheets are widely used in industry, because they are flexible and easy to use. Sometimes they are even used for business-critical applications. It is however difficult for spreadsheet users to correctly assess the quality of…

Spreadsheets are widely used in industry, even for critical business processes. This implies the need for proper risk assessment in spreadsheets to evaluate the reliability and validity of the spreadsheet's outcome. As related research has…

The use of spreadsheets is widespread. Be it in business, finance, engineering or other areas, spreadsheets are created for their flexibility and ease to quickly model a problem. Very often they evolve from simple prototypes to…

We consider the challenge of creating guidelines to evaluate the quality of a spreadsheet model. We suggest four principles. First, state the domain-the spreadsheets to which the guidelines apply. Second, distinguish between the process by…

Data quality describes the degree to which data meet specific requirements and are fit for use by humans and/or downstream tasks (e.g., artificial intelligence). Data quality can be assessed across multiple high-level concepts called…

In this paper, we introduce a scientific format for text-based data files, which facilitates storing and communicating tabular data sets. The so-called Full-Metadata Format builds on the widely used INI-standard and is based on four…

A huge amount of data is everyday managed in large organizations in many critical business sectors with the support of spreadsheet applications. The process of elaborating spreadsheet data is often performed in a distributed, collaborative…

The spreadsheet application is among the most widely used computing tools in modern society. It provides excellent usability and usefulness, and it easily enables a non-programmer to perform programming-like tasks in a visual tabular "pen…

High-quality data is key to interpretable and trustworthy data analytics and the basis for meaningful data-driven decisions. In practical scenarios, data quality is typically associated with data preprocessing, profiling, and cleansing for…

This paper proposes a template for documenting datasets that have been collected from online platforms for research purposes. The template should help to critically reflect on data quality and increase transparency in research fields that…

Over the years, many subjective and objective quality assessment datasets have been created and made available to the research community. However, there is no standard process for documenting the various aspects of the dataset, such as…