{"title":"优化开放政府:数据共享的经济学视角","authors":"Todd Sanderson, A. Reeson, P. Box","doi":"10.1145/3326365.3326383","DOIUrl":null,"url":null,"abstract":"Data has value helping individuals, businesses and government make decisions. Sharing government data can, therefore, enhance its value, providing privacy is safeguarded. Open government data can also enhance equity by reducing the information advantage that large businesses increasingly have over smaller competitors and customers. However, there are costs associated with open data. It must be curated and disseminated. Protecting individual privacy may require aggregation or transformation. There are also different ways of sharing data. At its crudest, this may take the form of providing files, in whatever form, on a website. More usefully and at greater cost, sharing data may take the form of machine-readable APIs. Data services also help users draw insights from data, for example by identifying patterns or trends or highlighting the most salient information. These different sharing models incur different costs to government and users. More accessible data with associated services generally increase the potential benefits to users but will come at some cost to government. From an economic perspective, it will be more efficient if this is done once by the government. However, given the limited budget resources of governments it is worth considering how the process of opening government data could be optimized. The objective of this research is to provide a framework to assist decision-makers responsible for open data. A data prioritization index could assess the trade-offs between the costs and benefits of making particular datasets open. The benefits depend on the extent to which data are likely to be used by citizens, or to enhance competition among firms. The costs include the ICT infrastructure requirements and privacy safeguards needed to make the data open. Ultimately the value of open data will grow as artificial intelligence lowers the cost of drawing insights from it. Open data could also reduce the extent to which a small number of large companies are able to profit from monopolizing their data holdings.","PeriodicalId":178287,"journal":{"name":"Proceedings of the 12th International Conference on Theory and Practice of Electronic Governance","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Optimizing Open Government: an economic perspective on data sharing\",\"authors\":\"Todd Sanderson, A. Reeson, P. Box\",\"doi\":\"10.1145/3326365.3326383\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Data has value helping individuals, businesses and government make decisions. Sharing government data can, therefore, enhance its value, providing privacy is safeguarded. Open government data can also enhance equity by reducing the information advantage that large businesses increasingly have over smaller competitors and customers. However, there are costs associated with open data. It must be curated and disseminated. Protecting individual privacy may require aggregation or transformation. There are also different ways of sharing data. At its crudest, this may take the form of providing files, in whatever form, on a website. More usefully and at greater cost, sharing data may take the form of machine-readable APIs. Data services also help users draw insights from data, for example by identifying patterns or trends or highlighting the most salient information. These different sharing models incur different costs to government and users. More accessible data with associated services generally increase the potential benefits to users but will come at some cost to government. From an economic perspective, it will be more efficient if this is done once by the government. However, given the limited budget resources of governments it is worth considering how the process of opening government data could be optimized. The objective of this research is to provide a framework to assist decision-makers responsible for open data. A data prioritization index could assess the trade-offs between the costs and benefits of making particular datasets open. The benefits depend on the extent to which data are likely to be used by citizens, or to enhance competition among firms. The costs include the ICT infrastructure requirements and privacy safeguards needed to make the data open. Ultimately the value of open data will grow as artificial intelligence lowers the cost of drawing insights from it. Open data could also reduce the extent to which a small number of large companies are able to profit from monopolizing their data holdings.\",\"PeriodicalId\":178287,\"journal\":{\"name\":\"Proceedings of the 12th International Conference on Theory and Practice of Electronic Governance\",\"volume\":\"72 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 12th International Conference on Theory and Practice of Electronic Governance\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3326365.3326383\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 12th International Conference on Theory and Practice of Electronic Governance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3326365.3326383","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimizing Open Government: an economic perspective on data sharing
Data has value helping individuals, businesses and government make decisions. Sharing government data can, therefore, enhance its value, providing privacy is safeguarded. Open government data can also enhance equity by reducing the information advantage that large businesses increasingly have over smaller competitors and customers. However, there are costs associated with open data. It must be curated and disseminated. Protecting individual privacy may require aggregation or transformation. There are also different ways of sharing data. At its crudest, this may take the form of providing files, in whatever form, on a website. More usefully and at greater cost, sharing data may take the form of machine-readable APIs. Data services also help users draw insights from data, for example by identifying patterns or trends or highlighting the most salient information. These different sharing models incur different costs to government and users. More accessible data with associated services generally increase the potential benefits to users but will come at some cost to government. From an economic perspective, it will be more efficient if this is done once by the government. However, given the limited budget resources of governments it is worth considering how the process of opening government data could be optimized. The objective of this research is to provide a framework to assist decision-makers responsible for open data. A data prioritization index could assess the trade-offs between the costs and benefits of making particular datasets open. The benefits depend on the extent to which data are likely to be used by citizens, or to enhance competition among firms. The costs include the ICT infrastructure requirements and privacy safeguards needed to make the data open. Ultimately the value of open data will grow as artificial intelligence lowers the cost of drawing insights from it. Open data could also reduce the extent to which a small number of large companies are able to profit from monopolizing their data holdings.