{"title":"开放政府计划对数据质量的系统性影响:以纽约州食品保护计划领域为例","authors":"M. Najafabadi, Felippe Cronemberger","doi":"10.1108/tg-11-2021-0194","DOIUrl":null,"url":null,"abstract":"\nPurpose\nThis paper aims to explore the open government data initiative in the Food Protection program area within the New York State’s Department of Health to assess the impacts of opening data in terms of data quality and public value. An ecosystem lens is used to explore the dynamics of actors and their interactions, the processes involved in the program and the consequences such interplay brought forth to data quality.\n\n\nDesign/methodology/approach\nThe data were collected through 15 semistructured interviews with multiple stakeholders from different sectors, such as county officials, administrators and technicians, food sanitarians, data journalists and restaurant owners. At the analysis stage, the ecosystem perspective helped to capture the big picture of the open data actor interrelationships within this community regarding the food service inspections datasets.\n\n\nFindings\nPrior research suggests that open data initiatives enhance data quality. However, this study shows how opening data can adversely affect the quality of data. Results are explained by competing dynamics and conflicting interests among open data actors, undermining the expected public value from open data initiatives.\n\n\nResearch limitations/implications\nThe findings are in contrast with the mainstream open data literature and helps open data scholars to anticipate some currently unexpected results of open data initiatives. Limitations include potential biases associated to interpretation of interview data and that the results are based on a single case study.\n\n\nPractical implications\nThis study makes governments and policymakers alert about the possibility of similar open data byproducts and unwanted outcomes and helps them to design more effective open data policies, hence gaining higher economic advantage while lowering costs of open data initiatives.\n\n\nOriginality/value\nDetailed open data and open data case studies through the ecosystem perspective are still scarce and can enrich discussions about open data policy design and refinement in the public sector. The data used for this research are not used in any prior papers, and to the best of the authors’ knowledge, this is the first study to identify such adverse effects of data quality that have been reported.\n","PeriodicalId":51696,"journal":{"name":"Transforming Government- People Process and Policy","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2022-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Systemic effects of an open government program on data quality: the case of the New York State’s Food Protection program area\",\"authors\":\"M. Najafabadi, Felippe Cronemberger\",\"doi\":\"10.1108/tg-11-2021-0194\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nPurpose\\nThis paper aims to explore the open government data initiative in the Food Protection program area within the New York State’s Department of Health to assess the impacts of opening data in terms of data quality and public value. An ecosystem lens is used to explore the dynamics of actors and their interactions, the processes involved in the program and the consequences such interplay brought forth to data quality.\\n\\n\\nDesign/methodology/approach\\nThe data were collected through 15 semistructured interviews with multiple stakeholders from different sectors, such as county officials, administrators and technicians, food sanitarians, data journalists and restaurant owners. At the analysis stage, the ecosystem perspective helped to capture the big picture of the open data actor interrelationships within this community regarding the food service inspections datasets.\\n\\n\\nFindings\\nPrior research suggests that open data initiatives enhance data quality. However, this study shows how opening data can adversely affect the quality of data. Results are explained by competing dynamics and conflicting interests among open data actors, undermining the expected public value from open data initiatives.\\n\\n\\nResearch limitations/implications\\nThe findings are in contrast with the mainstream open data literature and helps open data scholars to anticipate some currently unexpected results of open data initiatives. Limitations include potential biases associated to interpretation of interview data and that the results are based on a single case study.\\n\\n\\nPractical implications\\nThis study makes governments and policymakers alert about the possibility of similar open data byproducts and unwanted outcomes and helps them to design more effective open data policies, hence gaining higher economic advantage while lowering costs of open data initiatives.\\n\\n\\nOriginality/value\\nDetailed open data and open data case studies through the ecosystem perspective are still scarce and can enrich discussions about open data policy design and refinement in the public sector. The data used for this research are not used in any prior papers, and to the best of the authors’ knowledge, this is the first study to identify such adverse effects of data quality that have been reported.\\n\",\"PeriodicalId\":51696,\"journal\":{\"name\":\"Transforming Government- People Process and Policy\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2022-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transforming Government- People Process and Policy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1108/tg-11-2021-0194\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"INFORMATION SCIENCE & LIBRARY SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transforming Government- People Process and Policy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/tg-11-2021-0194","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
Systemic effects of an open government program on data quality: the case of the New York State’s Food Protection program area
Purpose
This paper aims to explore the open government data initiative in the Food Protection program area within the New York State’s Department of Health to assess the impacts of opening data in terms of data quality and public value. An ecosystem lens is used to explore the dynamics of actors and their interactions, the processes involved in the program and the consequences such interplay brought forth to data quality.
Design/methodology/approach
The data were collected through 15 semistructured interviews with multiple stakeholders from different sectors, such as county officials, administrators and technicians, food sanitarians, data journalists and restaurant owners. At the analysis stage, the ecosystem perspective helped to capture the big picture of the open data actor interrelationships within this community regarding the food service inspections datasets.
Findings
Prior research suggests that open data initiatives enhance data quality. However, this study shows how opening data can adversely affect the quality of data. Results are explained by competing dynamics and conflicting interests among open data actors, undermining the expected public value from open data initiatives.
Research limitations/implications
The findings are in contrast with the mainstream open data literature and helps open data scholars to anticipate some currently unexpected results of open data initiatives. Limitations include potential biases associated to interpretation of interview data and that the results are based on a single case study.
Practical implications
This study makes governments and policymakers alert about the possibility of similar open data byproducts and unwanted outcomes and helps them to design more effective open data policies, hence gaining higher economic advantage while lowering costs of open data initiatives.
Originality/value
Detailed open data and open data case studies through the ecosystem perspective are still scarce and can enrich discussions about open data policy design and refinement in the public sector. The data used for this research are not used in any prior papers, and to the best of the authors’ knowledge, this is the first study to identify such adverse effects of data quality that have been reported.