Improving data quality of smartphone‐based activity–travel survey: A framework for data post‐processing

2021 ◽  
Author(s):  
Yaxuan Zhang ◽  
Ying Song ◽  
Yingling Fan
Keyword(s):  
Data Quality ◽  
Post Processing ◽  
Travel Survey

Designing Information Product (IP) Maps On the Process of Data Processing and Academic Information

2017 ◽  
Vol 4 (1) ◽  
pp. 25-31 ◽  
Author(s):  
Diana Effendi
Keyword(s):  
Data Quality ◽  
Data Management ◽  
Information Management ◽  
Information Quality ◽  
Quality Data ◽  
Management Approach ◽  
Quality Of Data ◽  
Information Product ◽  
Academic Activities

Information Product Approach (IP Approach) is an information management approach. It can be used to manage product information and data quality analysis. IP-Map can be used by organizations to facilitate the management of knowledge in collecting, storing, maintaining, and using the data in an organized. The  process of data management of academic activities in X University has not yet used the IP approach. X University has not given attention to the management of information quality of its. During this time X University just concern to system applications used to support the automation of data management in the process of academic activities. IP-Map that made in this paper can be used as a basis for analyzing the quality of data and information. By the IP-MAP, X University is expected to know which parts of the process that need improvement in the quality of data and information management.   Index term: IP Approach, IP-Map, information quality, data quality. REFERENCES[1] H. Zhu, S. Madnick, Y. Lee, and R. Wang, “Data and Information Quality Research: Its Evolution and Future,” Working Paper, MIT, USA, 2012.[2] Lee, Yang W; at al, Journey To Data Quality, MIT Press: Cambridge, 2006.[3] L. Al-Hakim, Information Quality Management: Theory and Applications. Idea Group Inc (IGI), 2007.[4] “Access : A semiotic information quality framework: development and comparative analysis : Journal ofInformation Technology.” [Online]. Available: http://www.palgravejournals.com/jit/journal/v20/n2/full/2000038a.html. [Accessed: 18-Sep-2015].[5] Effendi, Diana, Pengukuran Dan Perbaikan Kualitas Data Dan Informasi Di Perguruan Tinggi MenggunakanCALDEA Dan EVAMECAL (Studi Kasus X University), Proceeding Seminar Nasional RESASTEK, 2012, pp.TIG.1-TI-G.6.

scholarly journals Response Behavior and Quality of Survey Data: Comparing Elderly Respondents in Institutions and Private Households

2021 ◽  
pp. 004912412199553
Author(s):  
Jan-Lucas Schanze
Keyword(s):  
Data Quality ◽  
The Elderly ◽  
Response Behavior ◽  
Quality Of Data ◽  
Social Surveys ◽  
Private Households ◽  
Confounding Variables ◽  
Health Related ◽  
Survey Interviews

An increasing age of respondents and cognitive impairment are usual suspects for increasing difficulties in survey interviews and a decreasing data quality. This is why survey researchers tend to label residents in retirement and nursing homes as hard-to-interview and exclude them from most social surveys. In this article, I examine to what extent this label is justified and whether quality of data collected among residents in institutions for the elderly really differs from data collected within private households. For this purpose, I analyze the response behavior and quality indicators in three waves of Survey of Health, Ageing and Retirement in Europe. To control for confounding variables, I use propensity score matching to identify respondents in private households who share similar characteristics with institutionalized residents. My results confirm that most indicators of response behavior and data quality are worse in institutions compared to private households. However, when controlling for sociodemographic and health-related variables, differences get very small. These results suggest the importance of health for the data quality irrespective of the housing situation.

scholarly journals Thinking about police data: Analysts’ perceptions of data quality in Canadian policing

2021 ◽  
pp. 0032258X2110214
Author(s):  
Christopher D O’Connor ◽  
John Ng ◽  
Dallas Hill ◽  
Tyler Frederick
Keyword(s):  
Big Data ◽  
Data Collection ◽  
Data Quality ◽  
Research Culture ◽  
Police Services ◽  
Police Data ◽  
Data Collection And Analysis ◽  
Quality Issues

Policing is increasingly being shaped by data collection and analysis. However, we still know little about the quality of the data police services acquire and utilize. Drawing on a survey of analysts from across Canada, this article examines several data collection, analysis, and quality issues. We argue that as we move towards an era of big data policing it is imperative that police services pay more attention to the quality of the data they collect. We conclude by discussing the implications of ignoring data quality issues and the need to develop a more robust research culture in policing.

Effect of post‐processing treatments on the quality of three‐dimensional printed rice starch constructs

2021 ◽  
Author(s):  
Radhika Theagarajan ◽  
Shubham Nimbkar ◽  
Jeyan Arthur Moses ◽  
Chinnaswamy Anandharamakrishnan
Keyword(s):  
Three Dimensional ◽  
Rice Starch ◽  
Post Processing

Research on the Validation Method of Product Data Quality

2014 ◽  
Vol 989-994 ◽  
pp. 1631-1634
Author(s):  
Ping Wang ◽  
Bin Wang
Keyword(s):  
Data Quality ◽  
High Efficiency ◽  
Engineering Analysis ◽  
Validation Process ◽  
Software Environment ◽  
Product Data ◽  
Validation Method ◽  
Source Data ◽  
Cnc Programming

Product data is the source data of product lifecycle in manufacturing enterprise. The quality of product data largely determines the effect of the application of Engineering analysis, simulation assembly and CNC programming work and so on. In order to solve the problems of the existing product data quality, such as validation custom trival, lack of high efficiency and flexibility, etc. The validation method of product data quality (PDQ) based on class was proposed in NX software environment, the representation of validation rules classes of product data quality, validation rules customization and implementation of validation process were introduced in detail in this study. Finally, an application case was employed to verify the practicability and effectiveness of the proposed method.

Finding Approximate Shape Regularities for Reverse Engineering

2001 ◽  
Vol 1 (4) ◽  
pp. 282-290 ◽  
Author(s):  
F. C. Langbein ◽  
B. I. Mills ◽  
A. D. Marshall ◽  
R. R. Martin
Keyword(s):  
Reverse Engineering ◽  
Small Groups ◽  
Input Data ◽  
Boundary Representation ◽  
Range Data ◽  
Engineering Systems ◽  
Post Processing ◽  
Processing Step ◽  
3D Range Data

Current reverse engineering systems can generate boundary representation (B-rep) models from 3D range data. Such models suffer from inaccuracies caused by noise in the input data and algorithms. The quality of reverse engineered geometric models can be improved by finding candidate shape regularities in such a model, and constraining the model to meet a suitable subset of them, in a post-processing step called beautification. This paper discusses algorithms to detect such approximate regularities in terms of similarities between feature objects describing properties of faces, edges and vertices, and small groups of these elements in a B-rep model with only planar, spherical, cylindrical, conical and toroidal faces. For each group of similar feature objects they also seek special feature objects which may represent the group, e.g. an integer value which approximates the radius of similar cylinders. Experiments show that the regularities found by the algorithms include the desired regularities as well as spurious regularities, which can be limited by an appropriate choice of tolerances.

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