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What do we mean by “effective” access to data ? (Part II)

In my last post, I described the possibility of a systematic approach to data validation. A key feature of such an approach must be it’s availability to all who are responsible for data – and of special importance, its capacity to support efficient and timely use by creators or managers of data. Bill Michener (UNM), leader of one of the currently funded DataNet projects has published a chart describing the problem of “information entropy” [SEE: WK Michener “Meta-information concepts for ecological data management,” Ecological Informatics 1 (2006): 4 ] Within recent memory, I have heard an ecologist say that were it not possible to generate minimally necessary metadata “in 8 minutes,” he would not do it. Leaving aside — for now — the possibility of applying sticks and/or carrots (i.e. law and regulations, norms and incentives), it seems clear that a goal of applications development should be simplicity and ease of use.

[ Within the realm of ecology, a good set of guidelines to making data effectively available was recently published – these guidelines are well worth reviewing and make specific reference to the importance of using “scripted” statistical applications (i.e. applications that generate records of the full sequence of transformations performed on any given data) this recommendation complements the broader notion — mentioned in my last post — of using work flow mechanisms like Kepler to document the full process and context of a scientific investigation. SEE “Emerging Technologies: Some Simple Guidelines for Effective Data Management” Bulletin of the Ecological Society of America, April 2009, 205-214. http://www.nceas.ucsb.edu/files/computing/EffectiveDataMgmt.pdf ]

As a sidebar, it is worth noting that virtually all data are “dynamic” in the sense that they may be and are extended, revised, reduced etc. For purposes of publication – or for purposes of consistent citation and coherent argument in public discourse – it is essential that the referent instance of data or “version” of a data set be exactly specified and preserved. (This is analogous to the practice of “time-stamping” the citation of a Wikipedia article…)

Lest we be distracted by the brightest lights of technology, we should acknowledge that we now have available to us, on our desktops, powerful visualization tools. The development of Geographic Information Systems (GIS) has made it possible to present any and all forms of geo-referenced data as maps. Digital imaging and animation tools give us tremendous expressive power – which can greatly increase the persuasive, polemical effects of any data. (For just two instances among many possible, have a look at presentations at the TED meetings [SEE: http://www.ted.com/ ] or have a look Many Eyes [SEE: http://manyeyes.alphaworks.ibm.com/manyeyes/ ] .) But, these tools notwithstanding, there is always a fundamental obligation to provide for full , rigorous and public validation of data. That is, data must be fit for confident use.


Unanticipated uses of resources are one of the most interesting aspects of resource sharing on the Web. (At the American Museum of Natural History, we made a major investment in developing a comprehensive presentation of the American Museum Congo Expedition (1909-1915) – our site included 3-D presentation of stereopticon slides and one of the first documented uses of the site was by a teacher in Amarillo, Texas who was teaching Joseph Conrad – we received a picture of her entire class wearing our 3-D glasses.) It seems highly unlikely to me that we can anticipate or even should try to anticipate all such uses.

In the early 1980’s, I taught Boolean searching to students at the University of Washington and I routinely advised against attempts to be overly precise in search formulation – my advice was – and is – to allow the user to be the last term in the search argument.

An important corollary to this concept is the notion that metadata creation is a process not an event – and by “process” I mean an iterative, learning process. Clearly some minimally adequate set of descriptive metadata is essential for discovery of data but our applications must also support continuing development of metadata. Social, collaborative tools are ideal for this purpose. (I will not pursue this point here but I believe that a combination of open social tagging and tagging by “qualified” users — perhaps using applications that can invoke well-formed ontologies – holds pour best hope for comprehensive metadata development.)

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