A classification of data quality assessment and improvement methods

Data quality (DQ) assessment and improvement in larger information systems would often not be feasible without using suitable “DQ methods”, which are algorithms that can be automatically executed by computer systems to detect and/or correct problems in datasets. Currently, these methods are already essential, and they will be of even greater importance as the quantity of data in organisational systems grows. This paper provides a review of existing methods for both DQ assessment and improvement and classifies them according to the DQ problem and problem context. Six gaps have been identified in the classification, where no current DQ methods exist, and these show where new methods are required as a guide for future research and DQ tool development.This is the accepted manuscript. It's currently embargoed pending publication by Inderscience

Ready Educators Quality Improvement Pilot: Linking Program Improvement to Child Outcomes

This report is an evaluation of the first year of the Ready Educators Quality Improvement Pilot (REQIP), part of Thrive in 5's city-wide Ready Educators strategy. The pilot provided technical assistance and support to early education and care programs in centers and family child care homes that serve children from birth to age five. The REQIP theory of change posits that, to meet the goal of improved child outcomes, programs need to build "sustainable independent capacity to operationalize a continuous quality improvement process (CQI)." As the Pilot was envisioned, CQI involved the development of a Program Improvement Plan (PIP) through an assessment based on child-level and program data and with support from a Quality Improvement Partner (QIP). The PIP would then serve as the basis for technical assistance to meet the goals of the PIP, followed by a re-assessment using program and childlevel data. This CQI process would be sustained over time, in an ongoing continuous loop. In July 2013, after a competitive RFP process and with funding from the Barr Foundation, Thrive in 5 selected Wellesley Centers for Women to serve as the QIP

Data Accuracy and Completeness of Monthly Midwifery Returns Indicators of Ejisu Juaben Health Directorate of Ghana

The broad range of activities contained in the provision of Primary Health Care (PHC) places a burden on providers to make optimal use of limited resources to achieve maximal health benefit to the population served. All too often, ad hoc decisions and personal preferences guide PHC resource allocations, making accountability for results impossible. Problems constraining Routine Health Information System (RHIS) performance in low-income countries include: poor data quality; limited use of available information; weaknesses in how data are analyzed and poor RHIS management practices. This study sought to investigate these constraints. A non-experimental before and after study involving bassline assessment of data accuracy and completeness, application of innovative strategies such as mentoring and coaching of Health Information Officers in data quality improvement process. Coincidentally, the intervention improved both data accuracy and completeness performance significantly among the participating facilities. The outstanding performance may be attributed to management's new orientation and growing interest towards quality data. Engaging frontline staff in data quality improvement work and provision of regular feedback leads to improvement in data accuracy and completeness. This has implications for decision-making and resource allocation, especially in low-income countries, where the routine health information management system relies heavily on paper work

Synchrophasors: Multilevel Assessment and Data Quality Improvement for Enhanced System Reliability

. This study presents a comprehensive framework for testing and evaluation of Phasor Measurement Units (PMUs) and synchrophasor systems under normal power system operating conditions, as well as during disturbances such as faults and transients. The proposed framework suggests a performance assessment to be conducted in three steps: (a) type testing: conducted in the synchrophasor calibration laboratory according to accepted industrial standards; (b) application testing: conducted to evaluate the performance of the PMUs under faults, transients, and other disturbances in power systems; (c) end-to-end system testing: conducted to assess the risk and quantify the impact of measurement errors on the applications of interest. The suggested calibration toolset (type testing) enables performance characterization of different design alternatives in a standalone PMU (e.g., length of phasor estimation windows, filtering windows, reporting rates, etc.). In conjunction with the standard performance requirements, this work defines new metrics for PMU performance evaluations under any static and dynamic conditions that may unfold in the grid. The new metrics offer a more realistic understanding of the overall PMU performance and help users choose the appropriate device/settings for the target applications. Furthermore, the proposed probabilistic techniques quantify the PMU accuracy to various test performance thresholds specified by corresponding IEEE standards, rather than having only the pass/fail test outcome, as well as the probability of specific failures to meet the standard requirements defined in terms of the phasor, frequency, and rate of change of frequency accuracy. Application testing analysis encompasses PMU performance evaluation under faults and other prevailing conditions, and offers a realistic assessment of the PMU measurement errors in real-world field scenarios and reveals additional performance characteristics that are crucial for the overall application evaluation. End-to-end system tests quantify the impact of synchrophasor estimation errors and their propagation from the PMU towards the end-use applications and evaluate the associated risk. In this work, extensive experimental results demonstrate the advantages of the proposed framework and its applicability is verified through two synchrophasor applications, namely: Fault Location and Modal Analysis. Finally, a data-driven technique (Principal Component Pursuit) is proposed for the correction and completion of the synchrophasor data blocks, and its application and effectiveness is validated in modal analyzes

Improvement of Borehole Seismic Data Quality Control and Assessment by Statistical Approach

Borehole seismic data quality control is currently done by visual inspection; it increases acquisition time and ultimately leads to lost revenue for the client. In 2010 sixty wells had VSP surveys with the rig time losses US$6.6M. A proposed Quality Control Assurance Technology uses statistics for credibility of analysed information. The QCAT approaches are designed to be independent of personnel expertise, enable the client to manage risk and make decisions based on empirical evidence

Linked Data Quality Assessment: A Survey

Data is of high quality if it is fit for its intended use in operations, decision-making, and planning. There is a colossal amount of linked data available on the web. However, it is difficult to understand how well the linked data fits into the modeling tasks due to the defects present in the data. Faults emerged in the linked data, spreading far and wide, affecting all the services designed for it. Addressing linked data quality deficiencies requires identifying quality problems, quality assessment, and the refinement of data to improve its quality. This study aims to identify existing end-to-end frameworks for quality assessment and improvement of data quality. One important finding is that most of the work deals with only one aspect rather than a combined approach. Another finding is that most of the framework aims at solving problems related to DBpedia. Therefore, a standard scalable system is required that integrates the identification of quality issues, the evaluation, and the improvement of the linked data quality. This survey contributes to understanding the state of the art of data quality evaluation and data quality improvement. A solution based on ontology is also proposed to build an end-to-end system that analyzes quality violations\u27 root causes

Enhancing Transition for Students with Disabilities Across New York State: State Performance Plan #13 and the New York State Transition Quality Indicators

This policy brief describes the relationship between state reporting requirements under the Individuals with Disabilities Education Act of 2004 and New York State\u27s process for continuous quality improvement, utilizing TransQUAL Online. The federal government established State Performance Plan Indicator #13 (SPP 13) so that states would report the percentage of students with Individualized Education Programs whose goals and transition services reasonably enable the student to meet measurable post-secondary goals. In New York State, Transition Quality Indicators (TQI) were established to help school districts collaboratively assess their current transition-related practices. TransQUAL Online is a password-protected organizational assessment tool that integrates the TQI with planning and reflection tools and resources, supporting a continuous improvement approach. The author identifies a process by which a school district planning team can infuse SPP 13 data into the TransQUAL collaborative process, bringing this mandated review into a broader context. Tables are included that directly link Transition Quality Indicators to elements of the SPP 13 measurement tool

IMPROVEMENT MANAGEMENT OF TEACHER RESOURCE AMONG VOCATIONAL HIGH SCHOOL BASED ON INTERNATIONAL STANDARD SCHOOL INVEST (INDONESIA VOCATIONAL EDUCATION STRENGTHENING) IN YOGYAKARTA

ABSTRACT This education research aimed to: (1) find an overview of resource about teacher’s resource improvement management in vocational high school based on international INVEST in Yogyakarta, (2) find the effectiveness for the implementation of quality improvement resource teacher program at vocational high school based on international standard INVEST in Yogyakarta and (3) to know the constraints that experienced by vocational high school based on international standard INVEST in Yogyakarta in the implementation of improvement quality for teacher’s resource program. This education is an evaluation study (Evaluation Research), which was done through a case study on two vocational schools in Yogyakarta; they are SMKN 2 Yogyakarta and SMKN 2 Depok Sleman. Data collection methods were done by observation, questionnaires and unstructured interviews. Analysis techniques of data were used to adjust the data’s type obtained, and quantitative data were analyzed by using the descriptive statistical techniques, while qualitative data were analyzed by qualitative descriptive analysis. These results indicate that outlines an overview of resource’s management to improve the teacher’s quality at vocational high school based on international standard INVEST includes the several stages/processes such as: crawl (recruitment), filtering (selection), the placement/assignment, assessment/ evaluation of teacher’s performance, and teachers career’s development. From the five stages of the process, there is one of the most dominant/prominent and effective enough to be implemented by the school teacher is a career development process. This process aims to improve the graduate teacher’s quality in order to obtain the appropriate competence. Problems were encountered in the recruitment and selection process, among others, totaly has done by the municipal government and district government, while the problems were encountered in the placement process, evaluation and career development is generally caused by lack of school’s budget, also the technical and non technical constraints. Keywords: Quality Management, Resource Teacher, Vocational High School Based On International Standard INVES

A framework for assessing and improving quality of data from visual evaluation of asset conditions

Investments in transportation infrastructure assets are among the largest investments made by governmental agencies. Besides requiring a large investment for design and construction, transportation infrastructure also requires a significant amount of resources and effort for performing maintenance and/or rehabilitation activities. Along with other considerations, data on asset conditions are used to make decisions regarding the timing of maintenance activities, the type of treatment, and the resources employed. Some parameters under assessment, however, are evaluated through visual — or manual — assessments performed by evaluators on the site due to a lack of reliable, inexpensive automated methods to collect the data. While manual assessments for surface distresses are widely used, they still have the stigma that the results are based on subjective judgments by the individual evaluators. This thesis describes the Data Quality Assessment & Improvement Framework that has been developed to measure, and to improve, the performance of multiple pavement evaluators. This framework is based on a Continuous Quality Improvement cyclic process, where the main components include: a) assessment of the consistency over time — performed using linear regression analysis, b) assessment of the agreement between evaluators — performed using inter-rater agreement analysis, and c) management practices performed to improve the results shown by the assessments. When the Data Quality Assessment & Improvement Framework is applied to actual pavement distress data collected manually by different evaluators, the results show that it is an effective method for quickly identifying and solving data collection issues. The benefit of this framework is that the analyses employed provide performance data during the data collection process, thus minimizing the risk of subjectivity. The Data Quality Assessment & Improvement Framework can be used as part of an asset management program, or in any engineering program where the data collected are subjected to the judgment of the individuals performing the evaluation

Impact of published clinical outcomes data: case study in NHS hospital trusts

Objective To examine the impact of the publication of clinical outcomes data on NHS Trusts in Scotland to inform the development of similar schemes elsewhere. Design Case studies including semistructured interviews and a review of background statistics. Setting Eight Scottish NHS acute trusts. Participants 48 trust staff comprising chief executives, medical directors, stroke consultants, breast cancer consultants, nurse managers, and junior doctors. Main outcome measures Staff views on the benefits and drawbacks of clinical outcome indicators provided by the clinical resource and audit group (CRAG) and perceptions of the impact of these data on clinical practice and continuous improvement of quality. Results The CRAG indicators had a low profile in the trusts and were rarely cited as informing internal quality improvement or used externally to identify best practice. The indicators were mainly used to support applications for further funding and service development. The poor effect was attributable to a lack of professional belief in the indicators, arising from perceived problems around quality of data and time lag between collection and presentation of data; limited dissemination; weak incentives to take action; a predilection for process rather than outcome indicators; and a belief that informal information is often more useful than quantitative data in the assessment of clinical performance. Conclusions Those responsible for developing clinical indicator programmes should develop robust datasets. They should also encourage a working environment and incentives such that these data are used to improve continuously