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Re: Converting a variety of data formats, containingvarious ki
- From: Stephen D Green <stephengreenubl@gmail.com>
- To: "Costello, Roger L." <costello@mitre.org>
- Date: Tue, 4 Oct 2016 18:06:37 +0100
Slowness of reasoners, etc, makes me incredulous and the format is very verbose.
On Tuesday, 4 October 2016, Costello, Roger L. <costello@mitre.org> wrote:
Hi Folks,
Scenario: You are tasked to build a system that will receive data from a variety of sources. The data arrives in different formats (e.g., CSV, binary, tab-delimited, JSON, XML). The data sources
provide different kinds of data (e.g., one source provides book data, another source provides weather data, another source provides gardening data). The data will be converted to a common intermediary form and then from the intermediary form, placed into a
data store.
Recently I heard this statement:
Converting data that is in various formats and contains various kinds
of data, into a common intermediate form is hard (computationally
expensive). RDF is the only data model the enables such conversions
to be done in a way that is computationally tractable. Therefore, we
must use RDF. And, as a corollary, we must use a triple store to store
the RDF data.
Do you agree with that statement? If you do, can you provide evidence that RDF is the only data model that supports such conversions in a computationally tractable manner?
If you do not agree with that statement, can you provide evidence on why the statement is false?
/Roger
--
---- Stephen D Green
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