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

机译：开放数据的“可访问性”如何？在开放数据集中分析上下文相关信息和用户评论

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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-本文旨在研究开放数据集中包含的描述性信息的性质和充分性，以及用户针对特定数据集撰写的评论和问题的性质。提供了开放数据集，以促进公民参与和政府透明度。但是，使数据可用并不能保证使用。本文研究了与数据集一起提供的上下文相关信息的性质，并确定了用户在使用资源时遇到的挑战。设计/方法/方法-作者提取了与数据集一起提供的描述性文本（通常位于数据集的顶部（N = 216））以及用户针对数据集发布的问题和评论的性质。然后，他们将文本描述和用户注释细分为“理想单元”，并使用恒定比较方法进行开放式编码。这使他们能够提出描述所关注的主题问题以及用户遇到的挑战。调查结果-分析结果表明，与上下文相关的描述是有限且规范的。希望用户弄清楚如何使用数据。对用户评论/问题的分析揭示了他们遇到的四个挑战：数据的组织和可访问性，清晰性和完整性，有用性和准确性以及语言（拼写和语法）。数据提供者可以做更多的工作来解决这些问题。研究的局限性/含义-该研究的目的是了解开放数据提供的性质，并提出使“非专家用户”更容易访问开放数据的方法。因此，它不着重于在各个国家对开放数据提供进行概括，因为这种提供可能会因管辖权而异。实际意义-该研究提供了有关组织开放数据集的方式的见解，使公众可以访问该资源。它还提供有关开放数据提供者如何考虑用户观点的建议，包括提供持续支持。创意/价值-对开放数据的研究通常侧重于技术，政策和政治观点。可以说，这是对开放数据集中与上下文相关的信息进行分析的第一项研究。数据集不“自言自语”，因为它们需要上下文进行分析和解释。理解开放数据集中与上下文相关的信息的本质是最初的想法。

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