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How 'accessible' is open data? Analysis of context-related information and users' comments in open datasets

机译:“访问”是开放数据如何?上下文相关的信息和用户的评论在开放的数据集

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Purpose - This paper aims to examine the nature and sufficiency of descriptive information included in open datasets and the nature of comments and questions users write in relation to specific datasets. Open datasets are provided to facilitate civic engagement and government transparency. However, making the data available does not guarantee usage. This paper examined the nature of context-related information provided together with the datasets and identified the challenges users encounter while using the resources. Design/methodology/approach - The authors extracted descriptive text provided together with (often at the top of) datasets (N = 216) and the nature of questions and comments users post in relation to the dataset. They then segmented text descriptions and user comments into "idea units" and applied open-coding with constant comparison method This allowed them to come up with thematic issues that descriptions focus on and the challenges users encounter. Findings - Results of the analysis revealed that context-related descriptions are limited and normative. Users are expected to figure out how to use the data. Analysis of user comments/questions revealed four areas of challenge they encounter: organization and accessibility of the data, clarity and completeness, usefulness and accuracy and language (spelling and grammar). Data providers can do more to address these issues. Research limitations/implications - The purpose of the study is to understand the nature of open data provision and suggest ways of making open data more accessible to "non expert users". As such, it is not focused on generalizing about open data provision in various countries as such provision may be different based on jurisdiction. Practical implications - The study provides insight about ways of organizing open dataset that the resource can be accessible by the general public. It also provides suggestions about how open data providers could consider users' perspectives including providing continuous support. Originality/value - Research on open data often focuses on technological, policy and political perspectives. Arguably, this is the first study on analysis of context-related information in open-datasets. Datasets do not "speak for themselves" because they require context for analysis and interpretation. Understanding the nature of context-related information in open dataset is original idea.
机译:目的——本文的目的是研究自然和充足的描述性信息包括在公开数据集的性质用户评论和问题写有关特定的数据集。促进公民参与和政府透明度。并不能保证使用。提供上下文相关信息的性质的数据集,确定了用户在使用中遇到的挑战资源。作者提取提供描述性的文本一起的顶部(通常)数据集(N =216)和本质的问题和评论用户发布的数据集。分割文本描述和用户评论为“单位”和应用open-coding这使得他们不断比较方法提出了主题描述的问题关注和用户遇到的挑战。结果-结果的分析显示,是有限的,上下文相关的描述规范。使用数据。评论/显示四个方面的问题他们遇到的挑战:组织和数据的可访问性、清晰完整性、有效性和准确性语言(拼写和语法)。可以做更多的工作来解决这些问题。限制/影响的目的研究是理解开放数据的性质提供和建议的公开数据“非专家用户更容易”。这不是专注于对开放数据泛化提供在不同的国家规定根据管辖可能不同。影响——研究提供了了解组织开放数据资源的方法被公众可以访问。关于开放数据提供建议供应商可以考虑用户的观点包括提供持续的支持。创意/价值——研究经常公开数据关注技术、政策和政治视角。在分析上下文相关的信息open-datasets。“因为他们需要上下文分析和解释。上下文相关的信息开放的性质数据集是最初的想法。

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