Results 21 to 30 of about 24,118,381 (294)

Pattern Functional Dependencies for Data Cleaning [PDF]

, 2020
Patterns (or regex-based expressions) are widely used to constrain the format of a domain (or a column), e.g., a Year column should contain only four digits, and thus a value like “1980-” might be a typo.
Stonebraker, Michael, Sub Data Intensive Systems, Qahtan, A.A.A., Tang, Nan, Cao, Yang; id_orcid, Ouzzani, Mourad, Cao, Yang, Qahtan, Abdulhakim, Data Intensive Systems   +8 more
core   +2 more sources

dataMaid: Your Assistant for Documenting Supervised Data Quality Screening in R

Journal of Statistical Software, 2019
Data cleaning and validation are important steps in any data analysis, as the validity of the conclusions from the analysis hinges on the quality of the input data.
Anne Helby Petersen, Claus Thorn Ekstrøm   +1 more
doaj   +1 more source

Multi-Dimensional Data Preparation: A Process to Support Vulnerability Analysis and Climate Change Adaptation

IEEE Access, 2020
Agriculture is the backbone of a country’s economic system, considering that it not only provides food and raw materials but also employment opportunities for a large percentage of the population.
Ivan Dario Lopez, Apolinar Figueroa, Juan Carlos Corrales   +2 more
doaj   +1 more source

IoT data cleaning techniques: A survey

Intelligent and Converged Networks, 2022
Data cleaning is considered as an effective approach of improving data quality in order to help practitioners and researchers be devoted to downstream analysis and decision-making without worrying about data trustworthiness.
Xiaoou Ding, Hongzhi Wang, Genglong Li, Haoxuan Li, Yingze Li, Yida Liu   +5 more
doaj   +1 more source

A Python-Based Pipeline for Preprocessing LC–MS Data for Untargeted Metabolomics Workflows

Metabolites, 2020
Preprocessing data in a reproducible and robust way is one of the current challenges in untargeted metabolomics workflows. Data curation in liquid chromatography–mass spectrometry (LC–MS) involves the removal of biologically non-relevant features ...
Gabriel Riquelme, Nicolás Zabalegui, Pablo Marchi, Christina M. Jones, María Eugenia Monge   +4 more
doaj   +1 more source

Data Cleaning Framework: An Extensible Approach to Data Cleaning [PDF]

, 2010
The growing dependence of society on enormous quantities of information stored electronically has led to a corresponding rise in errors in this information.
Gu, Randy S.
core  

Comparative Evaluation of Hemodiafiltration, Hemoperfusion, and Standard Hemodialysis on Efficacy, Inflammatory Control, Dialysis Adequacy, and Safety in End‐Stage Renal Disease: A Prospective Observational Study

Therapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Background Chronic micro‐inflammation in patients with end‐stage renal disease (ESRD) is a significant driver of cardiovascular complications and diminished quality of life. While standard hemodialysis (SHD) effectively manages small‐molecule clearance, its ability to remove medium‐to‐large uremic toxins—the primary catalysts of systemic ...
Hongwei Zuo, Weisi Dai, Jie Mao, Mei Ye, Xingshan Lu, Xiaocui Zhang   +5 more
wiley   +1 more source

A framework for data cleaning in data warehouses [PDF]

, 2008
It is a persistent challenge to achieve a high quality of data in data warehouses. Data cleaning is a crucial task for such a challenge. To deal with this challenge, a set of methods and tools has been developed.
Peng, Taoxin
core  

Salmonella lipopolysaccharide‐containing supported lipid bilayers as platforms to study bacteriophage interactions

FEBS Letters, EarlyView.
We present robust protocols for the preparation of supported lipid bilayers (SLBs) incorporating either Salmonella smooth LPS or outer membrane vesicles (OMVs). We use a combination of quartz crystal microbalance with dissipation (QCM‐D) and fluorescence microscopy to both characterize the SLBs of various compositions and to probe their interactions ...
Hudson P. Pace, Alyssa Borges, Charles Arnaud, Tove Karlsson, Nina K. Bröker, Stefanie Barbirz, Marta Bally   +6 more
wiley   +1 more source

Performance and Scalability of Data Cleaning and Preprocessing Tools: A Benchmark on Large Real-World Datasets

Data
Data cleaning remains one of the most time-consuming and critical steps in modern data science, directly influencing the reliability and accuracy of downstream analytics.
Pedro Martins, Filipe Cardoso, Paulo Váz, José Silva, Maryam Abbasi   +4 more
doaj   +1 more source