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As data is increasingly acknowledged as a highly valuable asset, much effort has been put into investigating inter-organisational data sharing, aiming at utilising the value of formerly unused data. Moreover, most researchers agree, that…
In this paper, we delve into the critical aspect of dataset quality assessment in machine learning classification tasks. Leveraging a variety of nine distinct datasets, each crafted for classification tasks with varying complexity levels,…
Data cooperatives with fiduciary obligations to members provide a promising direction for the empowerment of individuals through their own personal data. A data cooperative can manage, curate and protect access to the personal data of…
Automated, data-driven quality management systems, which facilitate the transformation of data into useable information, are desired to enhance decision-making processes. Integration of accurate, reliable, and straightforward approaches…
Organizations across all sectors are increasingly undergoing deep transformation and restructuring towards data-driven operations. The central role of data highlights the need for reliable and clean data. Unreliable, erroneous, and…
The NIS2 directive requires EU Member States to ensure a consistently high level of cybersecurity by setting risk-management measures for essential and important entities. Evaluations are necessary to assess whether the required security…
The quality of the data in a dataset can have a substantial impact on the performance of a machine learning model that is trained and/or evaluated using the dataset. Effective dataset management, including tasks such as data cleanup,…
Declarative data quality has been an active research topic. The fundamental principle behind a declarative approach to data quality is the use of declarative statements to realize data quality primitives on top of any relational data…
Many software developments projects fail due to quality problems. Software testing enables the creation of high quality software products. Since it is a cumbersome and expensive task, and often hard to manage, both its technical background…
Data Warehouse provides storage for huge amounts of historical data from heterogeneous operational sources in the form of multidimensional views, thus supplying sensitive and useful information which help decision-makers to improve the…
In the digital age, the amount of data produced is growing exponentially. Governments and institutions can no longer rely on old methods for storing data and passing on the knowledge to future generations. Digital data preservation is a…
Digital repositories, either digital preservation systems or archival systems, periodically check the integrity of stored objects to assure users of their correctness. To do so, prior solutions calculate integrity metadata and require the…
In this paper we have focused a variety of techniques, approaches and different areas of the research which are helpful and marked as the important field of data mining Technologies. As we are aware that many Multinational companies and…
Survival of IT industries depends much upon the development of high quality and customer satisfied software products. Quality however can be viewed from various perspectives such as deployment of the products within estimated resources,…
Efficiency has been a pivotal aspect of the software industry since its inception, as a system that serves the end-user fast, and the service provider cost-efficiently benefits all parties. A database management system (DBMS) is an integral…
The open source software (OSS) assessment has become important given the increased adoption of OSS in commercial product development. Researchers proposed many OSS assessment models. However, little is known about the industrial relevance…
What if the main data protection vulnerability is risk management? Data Protection merges three disciplines: data protection law, information security, and risk management. Nonetheless, very little research has been made on the field of…
Within data-driven artificial intelligence (AI) systems for industrial applications, ensuring the reliability of the incoming data streams is an integral part of trustworthy decision-making. An approach to assess data validity is data…
The increase reliance on information systems has created unprecedented challenges for organizations to protect their critical information from different security threats that have direct consequences on the corporate liability, loss of…
Today it is crucial for organizations to pay even greater attention on quality management as the importance of this function in achieving ultimate business objectives is increasingly becoming clearer. Importance of the Quality Management…