Yes. For example, the “gender” property
values could be M, F, L, G, B, T, and I saw an
article the other day about a
man who was born with two penises. Then again,
there are hermaphrodites
born occasionally.
It’s very
difficult to fully
understand the entire context around even
relatively simple properties that
most people don’t bother to think about.
-Rich
Sincerely,
Rich Cooper
EnglishLogicKernel.com
Rich AT
EnglishLogicKernel DOT com
9 4 9 \ 5 2 5 -
5 7 1 2
Kingsley,
Rich:
I’d
suggest
adding something in the definition of data that
addresses the issue of scope
and frames of reference that are usually
implicit in the representation of
data. The inclusion of the term “big data” in
the glossary and
the discussion of boundaries and open-ness
underscores this point. Data is
about something or a portion of something and
not everything, i.e., it has
scope – unfortunately not usually explicitly
defined. It also has one or
more frames of reference in which it is
represented, such as character sets,
numbering systems, units of measure, naming
conventions and namespaces,
physical/spatial environmental assumptions,
socio-political norms/perspectives,
etc., as well as the notion of language already
cited in the definition. For
example, what are the correct, allowable, values
for data elements such as sex,
gender, sexual orientation, or political
affiliation? I realize this forum
doesn’t care much for the notion of context and
its scope, but most data
I have run across in my career in information
systems carries with it all sorts
of context and scope assumptions, and
interpreting the data properly for
whatever purposes someone might have requires an
understanding to those
context/scope assumptions and how they might
relate (or not) to the
corresponding assumptions appropriate to the
purposes of those
seeking/accessing/viewing the data in question.
Linked
data provides
links for one such set of scope/context
assumptions, determined by the link
creator. But data can be linked in a
multiplicity of ways for a multiplicity of
purposes – following multiple ontologies and
related operational or
institutional domains and their respective scope
and underlying perspectives,
frames of reference, and purposes for
representing/amassing data in the first
place.
Hans
On 1/4/14 12:50
PM, Rich Cooper wrote:
Dear
Kingsley,
The
definition you
offered for “big data”:
“Data that's disparately
located, varied in structure,
voluminous, and rapidly changing.”
doesn’t
fit what
most uses of that word seem to imply.
Businesses maintain big data
history files which they mine for discovering
knowledge. But normally,
that big data is stored in a data center on
the local area network (not on the
internet per se) to protect it from outside
eyes. Your definition
emphasizes the internet, domains on it having
lots of data which can be
linked. Most big data is not really linked –
it comes from SQL and
NoSQL databases that were captured in the
business.
I am not
insinuating that "Big Data" is
linked, quite the contrary. My claim is that
"Big Data" is a term
that refers to:
“Data
that's
disparately located, varied in structure,
voluminous, and rapidly changing.”
For
example, many store
chains keep records of how customers visit
retail aisles, how much time they
spend at each section, and what they finally buy
before leaving. The
stores may forward the data to HQ over the
internet, but it is protected by
encryption, VPNs, etc to keep it from prying
eyes. After it reaches HQ,
it is stored and mined.
So
my suggestion is to
differentiate “Linked Big Data” from the usual
“Big
Data”. That way, you can distinguish which kind
is being
described.
Yes, which is why I treat "Big Data" as a term
that's distinct from
"Linked Data", "Linked Open Data", and the
"Linked
Open Data Cloud" in this document.
--
Happy New Year,
Kingsley Idehen
Founder & CEO
OpenLink Software
Company Web: http://www.openlinksw.com
Personal Weblog: http://www.openlinksw.com/blog/~kidehen
Twitter Profile: https://twitter.com/kidehen
Google+ Profile: https://plus.google.com/+KingsleyIdehen/about
LinkedIn Profile: http://www.linkedin.com/in/kidehen
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