Results 301 to 310 of about 29,969,840 (342)
Some of the next articles are maybe not open access.
Beyond Accuracy: What Data Quality Means to Data Consumers
Journal of Management Information Systems, 1996Poor data quality (DQ) can have substantial social and economic impacts. Although firms are improving data quality with practical approaches and tools, their improvement efforts tend to focus narrowly on accuracy.
Richard Y. Wang, D. Strong
semanticscholar +1 more source
Overview and Importance of Data Quality for Machine Learning Tasks
Knowledge Discovery and Data Mining, 2020It is well understood from literature that the performance of a machine learning (ML) model is upper bounded by the quality of the data. While researchers and practitioners have focused on improving the quality of models (such as neural architecture ...
Abhinav Jain +9 more
semanticscholar +1 more source
An MTurk Crisis? Shifts in Data Quality and the Impact on Study Results
Social Psychology and Personality Science, 2019Amazon’s Mechanical Turk (MTurk) is arguably one of the most important research tools of the past decade. The ability to rapidly collect large amounts of high-quality human subjects data has advanced multiple fields, including personality and social ...
M. Chmielewski, Sarah C. Kucker
semanticscholar +1 more source
Social-minded Measures of Data Quality
ACM Journal of Data and Information Quality, 2020For decades, research in data-driven algorithmic systems has focused on improving efficiency (making data access faster and lighter) and effectiveness (providing relevant results to users).
E. Pitoura
semanticscholar +1 more source
Nursing Management, 2010
The Healthcare Quality Improvement Partnership has produced a guide covering all aspects of data collection, from what data quality means and how to improve it, to how to ensure that the purpose or objective ofclinical audits clearly identifies the nature of the data needed.
openaire +2 more sources
The Healthcare Quality Improvement Partnership has produced a guide covering all aspects of data collection, from what data quality means and how to improve it, to how to ensure that the purpose or objective ofclinical audits clearly identifies the nature of the data needed.
openaire +2 more sources
2000
Several different kinds of problems arise when parish records are used. First, the data include only the Christian population, and the population development of the Christians might be quite different from the other part of the society. During the 1930s the proportion of the Christian population of the whole population was already about 40 per cent in ...
Harri Siiskonen, Veijo Notkola
openaire +2 more sources
Several different kinds of problems arise when parish records are used. First, the data include only the Christian population, and the population development of the Christians might be quite different from the other part of the society. During the 1930s the proportion of the Christian population of the whole population was already about 40 per cent in ...
Harri Siiskonen, Veijo Notkola
openaire +2 more sources
Dynamic data maintenance for quality data, quality research
International Journal of Information Management, 2012Abstract Just like any other scientific research field, the value of data quality is undisputed in the field of transportation. From policy planning to performance evaluation, from model development to impact studies, good quality data is essential to generate ideas and clear-cut solutions to be implemented by transportation professionals and ...
Dilruba Ozmen-Ertekin, Kaan Ozbay
openaire +2 more sources
Automating Large-Scale Data Quality Verification
Proceedings of the VLDB Endowment, 2018Modern companies and institutions rely on data to guide every single business process and decision. Missing or incorrect information seriously compromises any decision process downstream.
Sebastian Schelter +5 more
semanticscholar +1 more source
Communications of the ACM, 2002 How good is a company's data quality? Answering this question requires usable data quality metrics. Currently, most data quality measures are developed on an ad hoc basis to solve specific problems [6, 8], and fundamental principles necessary for developing usable metrics in practice are lacking.
Leo L. Pipino +2 more
openaire +1 more source
2019
We are living in a world of information abundance, surplus, and access. We have technologies to acquire any type of information but we still face the challenge of extracting the underlying valuable knowledge. Data analyses and mining processes may be severely impaired whenever data are corrupted by noise, ambiguity and distortions.
Oliveira, Alexandra +4 more
openaire +3 more sources
We are living in a world of information abundance, surplus, and access. We have technologies to acquire any type of information but we still face the challenge of extracting the underlying valuable knowledge. Data analyses and mining processes may be severely impaired whenever data are corrupted by noise, ambiguity and distortions.
Oliveira, Alexandra +4 more
openaire +3 more sources