增加对“广泛数据”网络的访问

J. Hendler
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We are also working with the US government on bringing these techniques to the US Data.gov project.\n In this talk, which I admit includes parts that are far more speculative than practical at this point in time, I will explore how the link spaces among the data provide the underpinnings of potential new applications that will help bring data analytics into our personal lives. By making data more personalized, we may be able to achieve new possibilities in data integration that could provide capabilities by which all of us would be able to more fully interact with the important data that affects us in our everyday lives (such as health and well-being), and not just in our professional careers. I contend that similar techniques could be used to help increase the accessibility of data on the web. Linked-data approaches have been helping to some degree in this arena, but still leave a lot to be desired. 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引用次数: 5

摘要

由于我的手腕有问题,希望是暂时的,我正在用语音识别软件写这篇短文。由于这是我第一次使用这个软件,实际上我对它的工作效果比较满意。我可以写电子邮件,发送twitter和Facebook更新,并使用语音完成许多日常任务。除去一些拼写错误,我甚至可以写出这个文档(尽管将其转换为ACM格式需要帮助)。然而,现在我的生活中有很大一部分涉及到与数据的交互,当涉及到数据交互时,“面向所有人的网络”可能只是一个口号。即使没有可访问性问题,无论您的目标是输入、发现或集成数据,还是尝试理解某些特定数据告诉您的内容,都不是一件容易的事。再加上残疾,问题就变得更糟了。在这个主题演讲中,我将讨论当人们试图使用万维网上可以找到的“广泛数据”时出现的一些问题。“轻量级”语义的现代组合在很大程度上基于早期语义Web研究的迅速成熟的产品,再加上已经脱离传统关系数据库的“大数据”工具,提供了一个探索领域,将研究推向新的和有趣的方向。蒂姆·伯纳斯——李对“现在就开始原始数据”的呼吁得到了许多方面的响应,其他力量,包括透明度和创新的力量,正在创建不受限制的庞大数据存储库。举个例子,世界各国政府一直在以惊人的速度在网络上发布数据集。在过去的一年半里,我的研究小组已经确定并索引了来自世界各地超过70万个开放政府数据集的元数据。在撰写本文时,这包括来自30多个国家和国际组织的16种不同语言的数据集(我们目前预计到本日历年底将有超过100万组数据集)。我们的研究探索了如何从这个庞大的联邦目录空间中创建、索引和搜索元数据。我们还开发了一些工具,帮助用户从这些数据集中创建链接数据,并在可视化和其他演示的开发中使用这些链接数据,从而使数据更易于访问。我们还与美国政府合作,将这些技术引入美国数据网站项目。在这次演讲中,我承认在这个时间点上,我将探索数据之间的链接空间如何为潜在的新应用提供基础,这些应用将有助于将数据分析带入我们的个人生活。通过使数据更加个性化,我们可能能够在数据集成方面实现新的可能性,从而使我们所有人都能够更充分地与影响我们日常生活(如健康和福祉)的重要数据进行交互,而不仅仅是在我们的职业生涯中。我认为类似的技术可以用来帮助增加网络上数据的可访问性。关联数据方法在一定程度上帮助了这个领域,但仍有很多需要改进的地方。简而言之,我将探讨数据网络上发生的一些令人兴奋的事情,但哀叹在提供对数据网络的可扩展访问方面仍然存在的挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Increasing access to the web of "broad data"
Due to a problem with my wrists, hopefully temporary, I am writing this short article using voice recognition software. As this is the first time I've used this software, I'm actually relatively pleased with how well it works. I am able to write e-mails, send twitter and Facebook updates, and do many routine tasks using my voice. Modulo a few typos, I can even write this document (although putting this into ACM format required help). However, a significant portion of my life nowadays involves interacting with data, and when it comes to data interaction, "web for all" may as well just be a slogan. Even without accessibility problems, whether your goal is to enter, discover, or integrate data, or to try to understand what some particular data is telling you, it isn't easy. Add in disability, and the problem is made much worse. In this keynote, I will discuss some of the issues that arise as people try to use the "broad data" that can be found on the World Wide Web. The modern combination of "lightweight" semantics, based to a large degree on the rapidly maturing products of early semantic Web research, coupled with the "big data" tools that have moved away from traditional relational databases, provides an area of exploration that is pushing research in new and interesting directions. Tim Berners--Lee's call for "Raw Data Now" is being heeded in many quarters, and other forces, including those of transparency and innovation, are creating vast repositories of data that are available without restriction. As an example, governments around the world have been posting data sets on the web at a really amazing rate. In the past year and a half, my research group has identified and indexed the metadata for well over 700,000 open government datasets from around the world. This includes, at the time of this writing, datasets from more than thirty countries and international organizations in 16 different languages (we currently anticipate having more than 1 million data sets by the end of this calendar year). Our research has explored how to create, index and search metadata from this immense Federated catalog space. We have also been developing tools for helping users to create linked data from these data sets and to use that link data in the development of visualizations and other presentations that make the data more accessible. We are also working with the US government on bringing these techniques to the US Data.gov project. In this talk, which I admit includes parts that are far more speculative than practical at this point in time, I will explore how the link spaces among the data provide the underpinnings of potential new applications that will help bring data analytics into our personal lives. By making data more personalized, we may be able to achieve new possibilities in data integration that could provide capabilities by which all of us would be able to more fully interact with the important data that affects us in our everyday lives (such as health and well-being), and not just in our professional careers. I contend that similar techniques could be used to help increase the accessibility of data on the web. Linked-data approaches have been helping to some degree in this arena, but still leave a lot to be desired. In short, I will explore some exciting things happening on the web of data, but bemoan the challenges that still remain in providing scalable access to the Web of Data.
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