Geoscience Reference
In-Depth Information
PROJ.4
(2)
(3)(4)
(5)
GEOS
TerraLib 5.0
GDAL
(1)
OGR
Web
services
...
DBMS
Files
Existing
libraries
PostGIS, oracle
spatial, SQLite
etc...
WMS, WFS,
WCS, etc..
Shapefile, KML,
geotiff, etc...
FIGURE 14.7
Envisioned developments in TerraLib 5: (1) support to different kinds of data sources;
(2) extensive use of existing libraries; (3) more modular, simpler and more easily extensible architecture;
(4) OGC compliant (SFS-SQL, OGC Web Service, etc.); and (5) represent and query spatio-temporal data.
Naturally, other forms of communication, such as IRC (Internet Relay Chat) chats in OSGeo,* or
blogs by Barry Rowlingson
†
and Daniel Nüst
‡
are interesting and less serious - more encouraging -
in tone; being able to include graphics in wiki pages, web fora and blogs is often very helpful. Being
able to search these resources and mailing list archives remains important and may not be easy to
achieve. So one challenge is to attempt to sustain community memory, to try to avoid too many
repeat solutions being offered to questions that have been resolved.
Whether memory of past achievements and insights is a future prospect or not is, of course, a
rather paradoxical issue. I would argue that very much of what GC has been doing over the past
decades has been to compute on, and develop computational techniques for handling, problems
that were proposed in earlier years, when analysis of even small data sets was exhausting (Bivand
2009). In that sense, memory is not unimportant, because we may make progress when we confront
the insights and propositions of the past with regard to research problems, algorithms or tools with
fresh opportunities offered by advances in data gathering and computational technologies, both in
hardware and in software. In this context, the growing importance of open-source software is also
a return to one of the ways in which research was done when spatial analysis and spatial statistics
were first established.
REFERENCES
Altman, M. (2011). BARD: Better automated redistricting. R package version 1.24, http://CRAN.R-project.
org/src/contrib/Archive/BARD/BARD_1.24.tar.gz.
Altman, M. and McDonald, M. P. (2011). BARD: Better automated redistricting.
Journal of Statistical Software
,
42(4):1-28.
Batcheller, J. and Reitsma, F. (2010). Implementing feature level semantics for spatial data discovery:
Supporting the reuse of legacy data using open source components.
Computers, Environment and Urban
Systems
, 34(4):333-344.
Beaudette, D. and Roudier, P. (2011). aqp: Algorithms for quantitative pedology. R package version 0.99-5,
http://CRAN.R-project.org/package=aqp.
Bentley, J., Knuth, D. E., and McIlroy, M. D. (1986). Programming pearls: A literate program.
Communications
of the ACM
, 29(6):471-483.
*
http://wiki.osgeo.org/wiki/IRC.
†
http://geospaced.blogspot.com/.
‡
http://www.nordholmen.net/sos4r/.
