Related papers: Unfolding Data Quality Dimensions in Practice: A S…
Data quality and data cleaning are context dependent activities. Starting from this observation, in previous work a context model for the assessment of the quality of a database instance was proposed. In that framework, the context takes…
The study, based on a documental classic analysis, presents conceptual and methodological guidelines concerning the design of methodologies that help to measure the quality of information that is managed in organizations. It is described…
This document gives a set of recommendations to build and manipulate the datasets used to develop and/or validate machine learning models such as deep neural networks. This document is one of the 3 documents defined in [1] to ensure the…
A number of visual quality measures have been introduced in visual analytics literature in order to automatically select the best views of high dimensional data from a large number of candidate data projections. These methods generally…
This report discusses the issues of data quality in biobanks. It presents the state-of-the-art in data quality: the definition of data quality, the dimensions of data quality, and the quality management system for achieving or describing…
This paper provides a detailed survey of synthetic data techniques. We first discuss the expected goals of using synthetic data in data augmentation, which can be divided into four parts: 1) Improving Diversity, 2) Data Balancing, 3)…
Service quality possesses the vital prominence in usability of innovative products and services. As technological innovation has made the life synchronized and effective, Internet of Things (IoT) is matter of discussion everywhere. From…
Artificial Intelligence (AI) applications critically depend on data. Poor quality data produces inaccurate and ineffective AI models that may lead to incorrect or unsafe use. Evaluation of data readiness is a crucial step in improving the…
The composition of web services is a promising approach enabling flexible and loose integration of business applications. Numerous approaches related to web services composition have been developed usually following three main phases: the…
There is an implicit assumption in software testing that more diverse and varied test data is needed for effective testing and to achieve different types and levels of coverage. Generic approaches based on information theory to measure and…
Background: Test-case quality has always been one of the major concerns in software testing. To improve test-case quality, it is important to better understand how practitioners perceive the quality of test-cases. Objective: Motivated by…
Data profiling is an essential process in modern data-driven industries. One of its critical components is the discovery and validation of complex statistics, including functional dependencies, data constraints, association rules, and…
Quality managers, change agents and researchers are often troubled in defining and demonstrating the level of success achieved in software process improvement (SPI) initiatives. So far, there exist only few frameworks for identifying the…
In today's digital age, information systems (IS) are indispensable tools for organizations of all sizes. The quality of these systems, encompassing system, information, and service dimensions, significantly impacts organizational…
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…
Datasets serve as crucial training resources and model performance trackers. However, existing datasets have exposed a plethora of problems, inducing biased models and unreliable evaluation results. In this paper, we propose a…
Recent work has demonstrated the viability of using crowdsourcing as a tool for evaluating the truthfulness of public statements. Under certain conditions such as: (1) having a balanced set of workers with different backgrounds and…
Cloud computing has become increasingly popular. Many options of cloud deployments are available. Testing cloud performance would enable us to choose a cloud deployment based on the requirements. In this paper, we present an innovative…
In materials sciences, a large amount of research data is generated through a broad spectrum of different experiments. As of today, experimental research data including meta-data in materials science is often stored decentralized by the…
Data integration is the process of collecting data from different data sources and providing user with unified view of answers that meet his requirements. The quality of query answers can be improved by identifying the quality of data…