+1 # everything is data, context makes it meta
On Feb 15, 2012, at 10:29 PM, Simon Spero wrote:
> I have had several theoretical changes of opinion on this question, and
> have come to the considered opinion that there is no principled *essential*
> difference between Metadata and Data. It all depends on the
> context/theory/background assumptions to which the data is being applied.
> The property of Data being meta is entirely use sensitive. The property of
> being information may depend upon the existence of metadata referring to
> the data.
> For example, it is labeling of an antelope in a zoo as "an antelope" that
> turns an ungulate into a document; data measured from this beast gives us
> evidence about what "an antelope" is like.
> The label & number of the beast, as well as the date of capture and other
> provenance, are clearly metadata in this case, and provide the context for
> interpreting the data as information, and for assessing the degree of
> justification we have for treating this information as knowledge. However,
> in other cases, the metadata may serve as data for other studies, with no
> reference to our four legged friend.
> Suppose we are doing a study on the rate of differently labeled specimen
> acquisition in zoos across Europe over the course of the 19th and 20th
> centuries. In this situation, what was metadata has become our primary
> data; *our* metadata relates to the provenance of the descriptions.
> Metadata embedded by a smart sensor package included in the same persuade
> as the data gathered as part of an observation run is essential to the
> interpretation of that data as information. However, it is not the primary
> data itself; it is the context. Radar data from early JSTARS platforms was
> severely downgraded by rain between the platform and the ground; the
> information provided needs context about climate conditions in order to
> determine the actual amount of information obtained when fusing that
> information with other sensor systems. However, the climate readings are
> not part of the radar data itself.
> So, to sum up, it depends; Further Research Is Needed; one man's Meta is
> another man's Poisson.
> On Feb 14, 2012 9:59 AM, "Michael Hopwood" <[log in to unmask]> wrote:
>> Having done research, and now working in a very varied metadata role, I
>> don't quite understand this discussion about data that is or isn't
>> metadata. Scientific data is a great example of structured data, but it's
>> not impossible to distinguish it from metadata purely describing a dataset.
>> However, if you have scientific research data created during the
>> experiments, even if it's "operational", it's clearly part of "the" data.
>> This doesn't mean there can't be metadata describing *that data*. Just
>> because it's not glamorous data doesn't mean it's not essential to the
>> scientific process. Similarly, just being about mundane or procedural
>> things doesn't make data into metadata...!
>> You're absolutely right, the contextual information is certainly part of
>> the experimental outcome in this example; otherwise it would be abstract
>> data such as one might use in a textbook example.
>> Metadata would describe the dataset itself, not the scientific research.
>> There's always a certain ambiguity involved in identifying "the data" as
>> distinct from the metadata, and it's a false dichotomy to suggest metadata
>> is not useful at all for the domain expert. It's contextual, and the
>> definition is always at least partly based on your use case for the data
>> and its description.
>> -----Original Message-----
>> From: Code for Libraries [mailto:[log in to unmask]] On Behalf Of
>> Nate Vack
>> Sent: 14 February 2012 14:45
>> To: [log in to unmask]
>> Subject: Re: [CODE4LIB] Metadata
>> On Tue, Feb 14, 2012 at 1:22 AM, Graham Triggs <[log in to unmask]>
>>> That's an interesting distinction though. Do you need all that data in
>>> order to make sense of the results? You don't [necessarily] need to
>>> know who conducted some research, or when they conducted it in order
>>> to analyse and make sense of the data. In the context of having the
>>> data, this other information becomes irrelevant in terms of
>>> understanding what that data says.
>> It is *essential* to understanding what the data says. Perhaps you find
>> out your sensor was on the fritz during a time period -- you need to be
>> able to know what datasets are suspect. Maybe the blood pressure effect
>> you're looking at is mediated by circadian rhythms, and hence, times of day.
>> Not all of your data is necessary in every analysis, but a bunch of blood
>> pressure measurements in the absence of contextual information is
>> universally useless.
>> The metadata is part of the data.