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Why Open Government Data? The Case of a Swedish Municipality

Journal of Data and Information Science 2021年第1期6卷 120-138页

作者： koraljka golub Arwid Lund Linnaeus University 35195 VäxjöSweden Södertörn University 14189 HuddingeStockholmSweden

Purpose: The purpose of this exploratory study is to provide modern local governments with potential use cases for their open data, in order to help inform related future policies and decision-making. The concrete context was that of the Vaxjo municipality located in southeastern ***/methodology/approach: The methodology was two-fold: 1) a survey of potential end users(n=151) from a local university;and, 2) analysis of survey results using a theoretical model regarding local strategies for implementing open government ***: Most datasets predicted to be useful were on: sustainability and environment;preschool and school;municipality and politics. The use context given is primarily research and development, informing policies and decision making;but also education, informing personal choices, informing citizens and creating services based on open data. Not the least, the need for educating target user groups on data literacy emerged. A tentative pattern comprising a technical perspective on open data and a social perspective on open government was identified. Research limitations: In line with available funding, the nature of the study was exploratory and implemented as an anonymous web-based survey of employees and students at the local university. Further research involving(qualitative) surveys with all stakeholders would allow for creating a more complete picture of the matter. Practical implications: The study determines potential use cases and use contexts for open government data, in order to help inform related future policies and ***/value: Modern local governments, and especially in Sweden, are faced with a challenge of how to make their data open, how to learn about which types of data will be most relevant for their end users and what will be different societal purposes. The paper contributes to knowledge that modern local governments can resort to when it comes to attitudes of local citizens to open government da

关键词： Open data E-government Open government

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Automatic Classification of Swedish Metadata Using Dewey Decimal Classification:A Comparison of Approaches

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Journal of Data and Information Science 2020年第1期5卷 18-38页

作者： koraljka golub Johan Hagelback Anders Ardo Department of Cultural Sciences Faculty of Arts and HumanitiesLinnaeus UniversityVaxjoSweden Department of Computer Science and Media Technology Faculty of TechnologyLinnaeus UniversityKalmarSweden Department of Electrical and Information Technology Lund UniversityLundSweden

Purpose:With more and more digital collections of various information resources becoming available,also increasing is the challenge of assigning subject index terms and classes from quality knowledge organization *** the ultimate purpose is to understand the value of automatically produced Dewey Decimal Classification(DDC)classes for Swedish digital collections,the paper aims to evaluate the performance of six machine learning algorithms as well as a string-matching algorithm based on characteristics of ***/methodology/approach:State-of-the-art machine learning algorithms require at least 1,000 training examples per *** complete data set at the time of research involved 143,838 records which had to be reduced to top three hierarchical levels of DDC in order to provide sufficient training data(totaling 802 classes in the training and testing sample,out of 14,413 classes at all levels).Findings:Evaluation shows that Support Vector Machine with linear kernel outperforms other machine learning algorithms as well as the string-matching algorithm on average;the string-matching algorithm outperforms machine learning for specific classes when characteristics of DDC are most suitable for the *** embeddings combined with different types of neural networks(simple linear network,standard neural network,1 D convolutional neural network,and recurrent neural network)produced worse results than Support Vector Machine,but reach close results,with the benefit of a smaller representation *** of features in machine learning shows that using keywords or combining titles and keywords gives better results than using only titles as *** only marginally improves the *** stop-words reduced accuracy in most cases,while removing less frequent words increased it *** greatest impact is produced by the number of training examples:81.90%accuracy on the training set is achieved when at least 1,000 records per class are available

关键词： LIBRIS Dewey Decimal Classification Automatic classification Machine learning Support Vector Machine Multinomial Naive Bayes Simple linear network Standard neural network 1D convolutional neural network Recurrent neural network Word embeddings String matching

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iSchool中的数字人文

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数字人文研究 2021年第3期1卷 93-112页

作者：约翰·A.沃尔什彼得·J.科布韦恩·德·弗雷默里科拉伊卡·戈卢布基赫·汉弗莱金贞贤约瑟夫·基普朗特刘英享西蒙·马奥尼吴三均克里斯·阿伦·苏拉特德·安德伍德王晓光陈怡(译) 美国印第安纳大学勒迪学院香港大学教育学院人类通讯、发展与信息科学学术组(CDIS) 香港大学人文学院韩国西江大学媒体艺术科学院瑞典林奈大学信息研究所联合国粮食及农业组织美国北得克萨斯州大学信息学院肯尼亚莫伊大学信息科学学院挪威奥斯陆城市大学图书情报档案系北京师范大学珠海分校数字出版与数字人文研究中心韩国成均馆大学图书馆与信息科学系美国普瑞特艺术学院信息学院美国伊利诺伊大学厄巴纳-香槟分校信息科学学院武汉大学信息管理学院、数字人文研究中心中国人民大学信息资源管理学院

作为交叉领域而广为人知的数字人文,正形式多样地呈现于iSchool的教学和研究活动中.在专门负责探索数字人文课程体系的iSchools组织委员会工作的基础上,当前的发现来自于一系列探讨iSchool(经常与其他部门和学科合作)的数字人文教学、... 详细信息

作为交叉领域而广为人知的数字人文,正形式多样地呈现于iSchool的教学和研究活动中.在专门负责探索数字人文课程体系的iSchools组织委员会工作的基础上,当前的发现来自于一系列探讨iSchool(经常与其他部门和学科合作)的数字人文教学、教育和研究之各方面的相关探讨.首先基于对iSchool项目的调研和一项对数字人文课程的在线调查,考察了iSchool中丰富多样的数字人文教育模式;通过分析各课程大纲与描述,详细探究了数字人文课程设置及体系.随后简要介绍了与iSchool合作进行数字人文研究项目或提供数字人文教育的学科部门.接着,通过分析相关职位的招聘广告探讨了数字人文职业.最后,围绕开展一项新的数字人文项目,就运营和行政层面上的挑战与机遇提供了一些观察.作为结果,最终呈现的是一份关于iSchool中数字人文发展现状的概览,可为设计与发展新的数字人文项目、学位和相关举措提供有益参考.

关键词：数字人文 iSchool 教育培养课程设置合作学科职业生涯

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