PE&RS November 2015 - page 834

November 2015
according to any higher level schema, the overall effect is one
of incoherence and confusion. This issue is exacerbated by
the wildly disparate focus and levels of detail in the different
chapters. One has the impression that authors were given
no instructions beyond a vague request to “write something
about geospatial big data”. The disconnect between different
chapters also results in significant redundancy. For instance,
at least half the authors provide definitions for the three V’s of
big data. This topic could and should have been dealt with in
an introductory chapter and then omitted from the individual
The book includes over one hundred illustrations. However,
the quality of reproduction is so poor that many are unreadable.
Furthermore, it appears clear that the originals for many of
the figures must have been in color, because when printed in
black and white format, one cannot interpret them.
In addition, I noted many typographic and spelling errors. I
find this inexcusable in a technical volume priced at over one
hundred dollars. For example:
• p. 131 - “When these techniques are used together or in
conjunction with big data tacking cognizance...”
• p. 146 - “... although some may be terms of
there dimensionality...”
• p. 181 - “the offturning of selective availability...”
• p. 211 - “The emergence of social media however is pausing
a different type of big data challenge...
• p. 221 - “...submission time (instance when it was
submitted to Twitter by the user)...”
In Chapter 8 (p. 164), the authors discuss a figure that does
not appear to exist. In Chapter 10 (p. 199), a critical acronym
is spelled wrong.
These errata are not complete. I only began recording the
page numbers of errors about halfway through the book, when
I realized that poor editing was a chronic problem. I have also
not called out grammar errors, recognizing that some of the
authors may not be native speakers of English.
Overall, I think it is fair to characterize the production of
this book as careless. It does not meet the standards that I
expect for a scholarly title.
In summary, this book offers a wide variety of interesting
perspectives on the question of big data in geoinformatics.
With some chapters offering three or four pages of references,
it may also serve as a useful starting point for more in-depth
research. However, the book suffers from weak conceptual
coherence and poor editing. Potential purchasers should be
aware of these shortcomings.
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