Data Quality Matrix

2020 ◽  
pp. 373-383
Author(s):  
Prameela Singu ◽  
Rayees Farooq
Keyword(s):  
Systematic Review ◽  
Data Quality ◽  
Survey Research ◽  
Review Of Literature ◽  
Quality Of Data ◽  
Research Outcomes ◽  
The Matrix ◽  
Survey Results ◽  
Quality Dimensions

The objective of the study is to develop a data quality matrix, which can be used to measure the quality of data and response rate from respondents. The study is exploratory in nature, which applied the systematic review of literature extracted from different database. The study found that all the quadrants of the matrix (e.g., active, risky, and non-functional and deferential) have importance depending upon the nature of the study. The study further suggests that risky situation can be improved through enhancing the quality of data collected. The proposed matrix is very helpful in understanding the quantity and quality dimensions of the data in survey research. It helps to interpret survey results to fit between data representativeness and desired research outcomes.

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.

Quality of Patient-Reported Outcome Studies Utilizing the BREAST-Q: A Systematic Review

2021 ◽  
Author(s):  
Lior Har-Shai ◽  
Sar-El Ofek ◽  
Addy Brandstetter ◽  
Keren H Cohen ◽  
Tamir Shay ◽  
...  
Keyword(s):  
Systematic Review ◽  
Plastic Surgery ◽  
Survey Research ◽  
Breast Surgery ◽  
Sample Size Calculation ◽  
Patient Reported Outcome ◽  
Validated Questionnaire ◽  
Patient Reported ◽  
Current Guidance

Abstract Background Patient-reported outcome (PRO) studies are essential the assessment of surgical procedures in plastic surgery. An accepted and validated questionnaire is the Breast-Q. Objectives This study aims to assess the quality of PRO studies in plastic surgery utilizing the Breast-Q questionnaire. Methods This study included two steps: (1) A systematic review of 23 key-criteria assessing the quality of survey-research in studies utilizing the Breast-Q which were published between 2015-2018; (2) Review of current guidance for survey-research in journals related to Plastic Surgery and Breast Surgery which were included in the systematic review. Results 79 studies were included in the systematic review. Many key-criteria were poorly reported: 51.9% of the studies did not provide a defined response rate and almost 90% did not provide a method for analysis of non-response error. 67.1% lacked a description of the sample's representativeness of the population of interest, and 82.3% did not present a sample size calculation. 11.4% of papers failed to describe the data analyzing methods; in 27.8% the data analysis which was presented could not allow replication of the results. Of the 16 journals in Plastic Surgery and Breast Surgery that their "Instruction to Authors" were reviewed, 15 (93.7%) did not provide any guidance for survey reporting. Conclusions The majority of key criteria are under-reported by authors publishing their survey-research in peer-reviewed journals in the fields of plastic and breast surgery. There is an urgent need for constructing a well-developed reporting guideline for survey-research in plastic surgery and particularly in breast surgery.

Integrating Experimental and Analytic Approaches to Improve Data Quality in Genome-wide RNAi Screens

2008 ◽  
Vol 13 (5) ◽  
pp. 378-389 ◽  
Author(s):  
Xiaohua Douglas Zhang ◽  
Amy S. Espeseth ◽  
Eric N. Johnson ◽  
Jayne Chin ◽  
Adam Gates ◽  
...  
Keyword(s):  
Data Quality ◽  
High Throughput Screening ◽  
Daily Practice ◽  
Systematic Errors ◽  
Quality Of Data ◽  
Improve Data Quality ◽  
Research Journal ◽  
Genome Wide ◽  
Assess Data Quality

RNA interference (RNAi) not only plays an important role in drug discovery but can also be developed directly into drugs. RNAi high-throughput screening (HTS) biotechnology allows us to conduct genome-wide RNAi research. A central challenge in genome-wide RNAi research is to integrate both experimental and computational approaches to obtain high quality RNAi HTS assays. Based on our daily practice in RNAi HTS experiments, we propose the implementation of 3 experimental and analytic processes to improve the quality of data from RNAi HTS biotechnology: (1) select effective biological controls; (2) adopt appropriate plate designs to display and/or adjust for systematic errors of measurement; and (3) use effective analytic metrics to assess data quality. The applications in 5 real RNAi HTS experiments demonstrate the effectiveness of integrating these processes to improve data quality. Due to the effectiveness in improving data quality in RNAi HTS experiments, the methods and guidelines contained in the 3 experimental and analytic processes are likely to have broad utility in genome-wide RNAi research. ( Journal of Biomolecular Screening 2008:378-389)

Peningkatan Kualitas Data Bidang Tanah di Kantor Pertanahan Kota Administrasi Jakarta Selatan

Tunas Agraria ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 168-174
Author(s):  
Maslusatun Mawadah
Keyword(s):  
Quality Improvement ◽  
Data Quality ◽  
Research Method ◽  
The South ◽  
Quality Of Data ◽  
Regional Division ◽  
Land Administration ◽  
Problems And Solutions ◽  
Descriptive Approach

The South Jakarta Administrative City Land Office is one of the cities targeted to be a city with complete land administration in 2020. The current condition of land parcel data demands an update, namely improving the quality of data from KW1 to KW6 towards KW1 valid. The purpose of this study is to determine the condition of land data quality in South Jakarta, the implementation of data quality improvement, as well as problems and solutions in implementing data quality improvement. The research method used is qualitative with a descriptive approach. The results showed that the condition of the data quality after the implementation of the improvement, namely KW1 increased from 86.45% to 87.01%. The roles of man, material, machine, and method have been fulfilled and the implementation of data quality improvement is not in accordance with the 2019 Complete City Guidelines in terms of territorial boundary inventory, and there are still obstacles in the implementation of improving the quality of land parcel data, namely the absence of buku tanah, surat ukur, and gambar ukur at the land office, the existence of regional division, the boundaries of the sub district are not yet certain, and the existence of land parcels that have been separated from mapping without being noticed by the office administrator.

Data Quality Associated with Big Data Processing: A Survey

2021 ◽  
Vol 23 (06) ◽  
pp. 1011-1018
Author(s):  
Aishrith P Rao ◽  
◽  
Raghavendra J C ◽  
Dr. Sowmyarani C N ◽  
Dr. Padmashree T ◽  
...  
Keyword(s):  
Big Data ◽  
Data Quality ◽  
Data Gathering ◽  
Cost Effective ◽  
Data Repository ◽  
Critical Approach ◽  
Critical Aspect ◽  
Quality Of Data ◽  
Data Group

With the advancement of technology and the large volume of data produced, processed, and stored, it is becoming increasingly important to maintain the quality of data in a cost-effective and productive manner. The most important aspects of Big Data (BD) are storage, processing, privacy, and analytics. The Big Data group has identified quality as a critical aspect of its maturity. Nonetheless, it is a critical approach that should be adopted early in the lifecycle and gradually extended to other primary processes. Companies are very reliant and drive profits from the huge amounts of data they collect. When its consistency deteriorates, the ramifications are uncertain and may result in completely undesirable conclusions. In the sense of BD, determining data quality is difficult, but it is essential that we uphold the data quality before we can proceed with any analytics. We investigate data quality during the stages of data gathering, preprocessing, data repository, and evaluation/analysis of BD processing in this paper. The related solutions are also suggested based on the elaboration and review of the proposed problems.

scholarly journals Systematic Review with Meta-Analysis: Endoscopic and Surgical Resection for Ampullary Lesions

2020 ◽  
Vol 9 (11) ◽  
pp. 3622
Author(s):  
Christian Heise ◽  
Einas Abou Ali ◽  
Dirk Hasenclever ◽  
Francesco Auriemma ◽  
Aiste Gulla ◽  
...  
Keyword(s):  
Systematic Review ◽  
Meta Analysis ◽  
Significant Risk ◽  
Significant Heterogeneity ◽  
Incomplete Resection ◽  
Quality Of Data ◽  
Surgical Interventions ◽  
Random Effects Models ◽  
Fixed And Random Effects

Ampullary lesions (ALs) can be treated by endoscopic (EA) or surgical ampullectomy (SA) or pancreaticoduodenectomy (PD). However, EA carries significant risk of incomplete resection while surgical interventions can lead to substantial morbidity. We performed a systematic review and meta-analysis for R0, adverse-events (AEs) and recurrence between EA, SA and PD. Electronic databases were searched from 1990 to 2018. Outcomes were calculated as pooled means using fixed and random-effects models and the Freeman-Tukey-Double-Arcsine-Proportion-model. We identified 59 independent studies. The pooled R0 rate was 76.6% (71.8–81.4%, I2 = 91.38%) for EA, 96.4% (93.6–99.2%, I2 = 37.8%) for SA and 98.9% (98.0–99.7%, I2 = 0%) for PD. AEs were 24.7% (19.8–29.6%, I2 = 86.4%), 28.3% (19.0–37.7%, I2 = 76.8%) and 44.7% (37.9–51.4%, I2 = 0%), respectively. Recurrences were registered in 13.0% (10.2–15.6%, I2 = 91.3%), 9.4% (4.8–14%, I2 = 57.3%) and 14.2% (9.5–18.9%, I2 = 0%). Differences between proportions were significant in R0 for EA compared to SA (p = 0.007) and PD (p = 0.022). AEs were statistically different only between EA and PD (p = 0.049) and recurrence showed no significance for EA/SA or EA/PD. Our data indicate an increased rate of complete resection in surgical interventions accompanied with a higher risk of complications. However, studies showed various sources of bias, limited quality of data and a significant heterogeneity, particularly in EA studies.

scholarly journals Quality of Open Research Data: Values, Convergences and Governance

Information ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 175 ◽  
Author(s):  
Tibor Koltay
Keyword(s):  
Big Data ◽  
Data Quality ◽  
Academic Research ◽  
Research Data ◽  
Data Governance ◽  
Quality Of Data ◽  
Open Research ◽  
Research Environments

This paper focuses on the characteristics of research data quality, and aims to cover the most important issues related to it, giving particular attention to its attributes and to data governance. The corporate word’s considerable interest in the quality of data is obvious in several thoughts and issues reported in business-related publications, even if there are apparent differences between values and approaches to data in corporate and in academic (research) environments. The paper also takes into consideration that addressing data quality would be unimaginable without considering big data.

Evaluating the Data Quality of a National Sample of Young Sexual and Gender Minorities Recruited Using Social Media: The Influence of Different Design Formats

2020 ◽  
pp. 089443932092824 ◽  
Author(s):  
Michael J. Stern ◽  
Erin Fordyce ◽  
Rachel Carpenter ◽  
Melissa Heim Viox ◽  
Stuart Michaels ◽  
...  
Keyword(s):  
Social Media ◽  
Data Quality ◽  
National Sample ◽  
Quality Data ◽  
Quality Of Data ◽  
Gender Minorities ◽  
Population Recruitment ◽  
Youth Population ◽  
And Gender

Social media recruitment is no longer an uncharted avenue for survey research. The results thus far provide evidence of an engaging means of recruiting hard-to-reach populations. Questions remain, however, regarding whether the data collected using this method of recruitment produce quality data. This article assesses one aspect that may influence the quality of data gathered through nonprobability sampling using social media advertisements for a hard-to-reach sexual and gender minority youth population: recruitment design formats. The data come from the Survey of Today’s Adolescent Relationships and Transitions, which used a variety of forms of advertisements as survey recruitment tools on Facebook, Instagram, and Snapchat. Results demonstrate that design decisions such as the format of the advertisement (e.g., video or static) and the use of eligibility language on the advertisements impact the quality of the data as measured by break-off rates and the use of nonsubstantive responses. Additionally, the type of device used affected the measures of data quality.

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