Datum, Data, Big Data, Big Text

Datum v. Data:

The word data is the plural of datum. To Put it even more starkly: Data is Plural. It signifies the availability of more than one datum -- or "data points" -- as are to be found in a scattergram, for example, where each "point" or dot represents one count in, or  "member" of, a sample or population. But even when referring to lots of data (or gathered or observed "datum" points), the word data has become, even among the savviest of analysts and 'reporters' (who are not necessarily the best linguists or the most cautious custodians of grammar), singularly singular in its day-to-day use (read this). Thus, for example, when economic or stock market statistics point in a discernible direction, we still 'hear' pundits almost invariably remark that "...the data tells us that..." or "shows that...". But they are, it seems, instinctively too reticent to remark that "...the statistics tells us...". Statistics always tell and show. So why is data so clumsily used? Why is this increasingly ever-present meme apparently so irredeemably lost?

Contributors and Editors at Wikipedia have grappled with this meme, and generally take the view that it is just fine to treat data as a singular -- "a mass noun". But they are clearly cognizant of its etymology and the attendant weight of grammar -- and thus implicitly acknowledge or fear that the notion of data as acceptably singular will sound to those who disagree as less Solomonic and more a deference or concession to the gallery (of casual users of the term).

READ: Data viewed as "a mass noun"

Here's what Tayler Krupa (2012) said about the proper use of datum and data:

"As noted in the sixth edition of the [APA Style] Publication Manual (p. 79), the plural form of some nouns of foreign origin—particularly those that end in the letter a—may appear to be singular and can cause authors to select a verb that does not agree in number with the noun. This is certainly the case with the word data. As shown in the Publication Manual (p. 96), the word datum is singular, and the word data is plural. Plural nouns take plural verbs, so data should be followed by a plural verb. To help clear up any confusion regarding the proper use of these terms, I list examples of datum and data being used correctly below..."


From Data to Big Data:

No one says Big Statistics. No one ever did, perhaps (correct me, s'il vous plait). But everyone, carried away by a certain current (a certain currency) of consciousness, says Big Data -- including yours truly. That's where we're headed after we're done with plain and simple data. Yes? Yet how cloudy and 'unreachable' is it where we must increasingly strive to safely keep it?

My mom's quite alert to the challenge; to the hilarity and boundless promise of clouds, up in the heavens, as hiding places for paperwork and suchlike -- against prying eyes and stealthy hands.

Do national statistics constitute big data -- or is that the preserve of tech giants of the world?

READ: "Kenya GDP Annual Growth Rate| 2004-2017|..."


Body Text:

Verbal language is so expansive it can only be "spoke", or more precisely "texted", within specific (con)texts. As with the spoken word, so too with such messages as the body involuntarily broadcasts or consciously emits within/across engaged (or communicating) "circles" or "parties" or contacts. As a term, then, "body language" is a monumental and "thoughtless" misnomer. All that we have are body texts extended or bounded by certain structures of intuitive or culturally (or experientially) mediated meaning. We have a plenitude of body texts -- but at best only illusions of body language. Body texts are the building-blocks of "big text" -- a term fairly recently chanced upon by yours truly thanks to inventive SONY Corp.


From Body Text to Big Text?

Is a mass of logically challenged argumentation on a WhatsApp wall, or a Trumped-up Twitter feed, characteristically Big Text? Is Big Text by definition more broadly cast and (or) other than Body Text? Not necessarily. And yet SONY, seemingly cogitating on a tangent, implies (indeed claims) that its mass-appeal World Cup images on huge TV screens represent Big Text as an 'evolutionary' phenomenon in the memetic sphere. Perhaps so, after all. In which case, so do (in more subtle ways) their precedents: the Pyramids of Giza, Mona Lisa, Guernica, The Last Supper, Black Panther (The Movie), the Wildebeest Migration -- and The Elusive/Living Black Panther. Just examples, these --  which are no substitute for robust classifications, for sure. But in fluid or rapidly changing contexts they do help point the way to deeper (re)cognition and greater clarity.



Updated: February 14, 2019

CSO 302 Qualitative Research Methods, Final Examination Papers, 21 December 2004 to 11 January 2014

To skip the text below and go straight to the examination papers, click here 

As is to be expected, the past papers included in the set I am providing in this blog post reflect the subject-matter of qualitative research methods taught under course code CSO 302 -- a third-year course at the University of Nairobi. The course underscores the contribution of qualitative methods to knowledge-generation, and to the deeper understanding of the social forces operating in 21st century society. 

We can trace the origins of qualitative methods back to the deep, millennia-long, past of human existence -- the ontological/ existential/proto-naturalistic past -- which preceded even the first stage in Auguste Comte's Law of Three Stages; that is, the "theological stage." Similarly, of course, we can trace the very roots of the natural (and social) sciences as we have come to know them back to that same past.

There is clearly a determination in the course to distinguish between methods of data collection and methods of data analysis, and to go for detail. And even though (a) similar methods often appear under a variety names; and, (b) similar names are or seem to be used, on occasion, interchangeably for both data collection and data analysis, you are challenged to spot the random disguises (under a), and to both extricate 'analysis' from 'collection' and articulate the paired differences (under b). 

All this puts a high premium on conceptual clarity and empirical example. Designing an efficient taxonomy of methods, which should proceed from such clarity and example(s), remains an ever-present challenge, which you are challenged to overcome any imaginative way you can, without 'brutally' violating Bateson's (1987: 284-287) classification principles embodied in his theory of logical types. 


Read More >>> Past Papers

Reminder: To access the CSO 302 examination papers, click here 

Thick Description ~ CSO 302

"... : if you want to understand what a science is, you should look in the first instance not at its theories or its findings, and certainly not at what its apologists say about it; you should look at what the practitioners of it do.

In anthropology, or anyway social anthropology, what the practioners (sic) do is ethnography. And it is in understanding what ethnography is, or more exactly what doing ethnography is, that a start can be made toward grasping what anthropological analysis amounts to as a form of knowledge. This, it must immediately be said, is not a matter of methods. From one point of view, that of the textbook, doing ethnography is establishing rapport, selecting informants, transcribing texts, taking genealogies, mapping fields, keeping a diary, and so on. But it is not these things, techniques and received procedures, that define the enterprise.

What defines it is the kind of intellectual effort it is: an elaborate venture in, to borrow a notion from Gilbert Ryle, "thick description." ~ Clifford Geertz (1973: 5-6) [Quote from his book, The Interpretation of Cultures. New York: Basic Books]

Gilbert Ryle's concept of thick description, as popularized in the disciplines of anthropology and sociology by Clifford Geertz (see, also, this article), refers to the successive addition of layer upon layer of detail to a phenomenon or process or event being described -- building up from 'literal' (or simple or lay) to 'thin' (or journalistic) to thick (or 'deep' or scholarly) description -- such that, true to the second law of dialectics, the quantum (quantity) of descriptions progressively transforms into a qualitative synthesis of the 'totality' of aspects of the phenomenon in question. It is like adding pixels and mega-pixels, one measured 'spread' after another, to a picture until one achieves the highest possible level of clarity, or picture quality.

Thick description is widely accepted as a major qualitative data analysis method or technique. However, I have preferred to use the concept synthesis in the above definition, as it more satisfactorily captures what for me is the core purpose of thick description. There is debate, however, concerning the relative merits of analysis and synthesis in pushing the boundaries of knowledge.

Analysis, an anchor concept in both quantitative and qualitative research, which is used routinely and unquestioningly by nearly all scientists (natural and social), does not seem to be quite apt here. B.N Ghosh (1985: 23), for example, has suggested that “analysis plays a more important role than synthesis” during “the initial stages of a science”; but “as the science becomes more and more progressive, synthesis plays a more and more important role. But in every science both the methods are used simultaneously.” He (1985: 24) adds that:

“A science aims at not only arriving at the truth but also at expounding the truth. A synthetic method is necessarily expository because it puts together the elements of a phenomenon in a systematic manner. In synthesis, exposition is possible because the entire elements are completely known and, as such, they can easily be arranged in an orderly way. The discovery of truth, however, is made possible by the method of analysis.”

I think that the aim and effect of thick description is to expound in 'full' the details, the 'totality', of the object of description. However, the end-product of thick description cannot be touted as a "complete" exposition of that which is (to be or has been) described; and I suspect that thick description was never intended for such a purpose.

NOTE: For more on thick description read:
1.This article by Joseph Ponterotto
2. Fei-Wen Liu's article

PS: Quote at the top added on September 11, 2015