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The Web of Data: Creating Machine-Accessible Information - ReadWriteWeb

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The Web of Data: Creating Machine-Accessible Information - ReadWriteWeb
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The Web of Data: Creating Machine-Accessible Information

In the coming years, we will see a revolution in the ability of machines to access, process, and apply information. This revolution will emerge from three distinct areas of activity connected to the Semantic Web: the Web of Data, the Web of Services, and the Web of Identity providers. These webs aim to make semantic knowledge of data accessible, semantic services available and connectable, and semantic knowledge of individuals processable, respectively. In this post, we will look at the first of these Webs (of Data) and see how making information accessible to machines will transform how we find information.

The amount of information and services available is growing exponentially. Every day, it is getting harder to find the information we are actually looking for. Still, we have to learn how to tell machines what we want. Why can't a machine understand which website, recent tweet, Flickr photo, Facebook message, or restaurant we are currently looking for?

Because it can't. It does not understand. It has no access to most sources. It lacks the semantic understanding and common sense to build bridges between information.

It is critical that machines gain a new level of understanding. Instead of statistically computing how well a search term matches a document, a machine must literally be able to understand. Therefore, knowledge bases are needed to look things up. Examples of these knowledge bases include:

an encyclopedia containing knowledge to look up the semantic meaning and context of a particular term (e.g. to understand that Berlin is a city, how many people live there, and where it is),

Yellow Pages or a service pool to query often-changing and more complex information (e.g. a route from Berlin to Porto by car, or the current temperature of Porto in Celsius),

...

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http://www.readwriteweb.com/archives/web_of_data_machine_accessible_information.php

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    • Andrew Waywood
      7 months ago


      I have only recently joined twine. It is fantastic for staying abreast of issues. I figure this post is a good anchor for a few general points. It is some way off in the future before machines will be intelligent. I take the functional definition of intelligence to be the ability to have insights. Bits of information coalescing into new know-how. Know-how is a practice and not a thing, or to frame in the terms of "creating machine accessible information". knowledge is information in use and something that takes insight to be applied.
      There is a point before "intelligent machines" that is worth aiming for, machines as amplifiers and social coordinators of human insight (really quite an important goal given the deleterious effect specialization is likely to have on future rates of innovation). When the article sets the goal as "a machine must literally be able to understand" it is simply an empty anthem unless we understand understanding, and at the moment we don't.
      I am really encouraged by growing acceptance of ontologies (and hence implicitly Directed Acyclic Graphs) in these debates and efforts. This is the locus of the issue: can we construct ontologies that cover all of human activity (TBL's GGG), even if we could how could we process them, and even if we could how would we define the relevance to the concrete and myriad human purposes that constitute our social lives.

      My current interests lie in the direction of the algorithms and methods required to build and process bottom up local ontologies. It seems to me that a pragmatic rather than semantic approach to these information to knowledge problems can be solved by re conceiving metadata in terms of a late binding process between content and user context.
      My main comment on this article "web as data" is that it leaves out human purposes and misconstrues the internal relations between data and the external relationships to the problems of people in the world. We ain't going to build "common sense" into computers but we can have computing facilitate the development of the future "common sense".
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First Posted By

Nova Spivack

First Comment By

Andrew Waywood

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