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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