Research On Quality Assessment And Quality Improvement For Open Government Data In China

Open Government Data is the outcome of economic and social development to a certain stage in the era of big data.It has risen to the height of national strategy and created rich value and benefits in political,economic,social and cultural aspects.Opening government data is not just as simple as opening the data,but to revitalize the stock data and optimize the incremental data,improve the economic and social availability,determine the rationality of decision-making and the accurate application of data.Data sharing is moving towards data availability.At present,Open Government Data in China shows trends of a steady increase in total data,increased support for policies and regulations,a gradual improvement in the construction of data platforms.There are more than 100 local governments have launched open data platforms with more than 70,000 open datasets,an increase of nearly eight times in two years.However,the level of data quality is uneven.The problems are gradually becoming more prominent,and there is a lack of scientific data quality assessment.standards and systems.To solve the above problems,the main contents of this paper are as follows:(1)Analysis of data quality assessment frameworks at home and abroad.Analyze and study the five quality assessment frameworks represented by Open Data Barometers abroad and the domestic Open Forest Index.Focused on the analysis of the specific quality dimensions and metrics in the framework to provide a basis for the data quality assessment framework of this paper.(2)Construct a data quality assessment framework.From the perspective of data quality,investigated the quality problems existing in the open data platform of local governments in China,then established a framework for assessing the Open Government Data quality in China with 8 quality dimensions.Quantitative assessment examples have been given of datasets and portal sites in five pilot areas in China.(3)Develop a data quality ontology.Based on the seven-step method,established a data quality ontology model,which was applied to the assessment results of the five pilot sites,and a unified example description of the data quality was introduced.Ontology reasoning is used to query and reason about the assessment results,to achieve the reuse and sharing of assessment results semantically.(4)Propose a data quality improvement mechanism and improvement methods.On the basis of the data governance framework,a quality improvement mechanism including system assurance,data processing,data quality control and assessment feedback is proposed.Based on the quality assessment framework and data quality ontology,applying data cleaning and ontology reasoning of two quality improvement methods for verification.(5)Quality assessment and improvement of COVID-19 datasets.The survey found that 13 local government platforms have opened a total of 113 COVID-19 datasets in China.The data.quality assessment framework constructed in this.paper is used to assess the data,data cleaning and ontology reasoning are used to improve data quality.Meanwhile,provide the suggestions for COVID-19 data quality improvement.The purpose of this paper is to improve the quality of Open Government Data in China,and to provide a certain reference for the development of data quality of local and national Open Government Data platforms.