A day in the life of a petro-data manager - Part I - Shorthand

[Update: a simpler workflow that uses  for-fee & for-free software is posted here]

After intoducing the process to extract, transform & load  (ETL) www.boem.gov well data into a www.ppdm.org database, here is the short version expanded over on my sister blog.

Web Maps on Steroids, Part II

I showed a couple of months ago ways to post mega-datasets online without choking the system. This month OSGeoUK gave me the opportunity to present the same on PostGIS Day 2014, as postGIS was the backbone of two of these examples on GIScloud and GeoCloud2. Thanks to OSGeoUK and British Computer Society for hosting this.

A day in the life of a petro-data manager - intro

[Update: Talend made the early version complex, so simpler one was posted later]

Have you ever been given plain text geodata and wondered how to database and map it? And has this happened to you lately with tens of thousands of lines of data? Well help is at hand! Here is an ETL  workflow (extract, transform, load) useful to any data manager in or out of petroleum using free tools:

Big data and maps reloaded

Social media really work! +Vicky Gallardo posted on Google+ that the map is not the territory, with a wonderful big data map by Ben Allen of Denton TX (near where I used to live). That prompted a post by the same title on my companion map blog. The distinction between data and maps has long kept me up at night (see my blog tagline), and many others to judging by exhibits and media only in London (near where I live now).

Web maps on steroids

The last 6 blog posts over the last 3 months chronicled the use of dynamic maps using time attribute - years for historic ship tracks and wind data from same 150-350 yrs ago - not to animate maps but to filter them by decade and manage data fetches on ArcGIS Online. A parallel series of posts showed mega data sets on Amazon Web Services, as Mapcentia assured me postGIS handled giga datasets...

On joining and merging historic multi-lingual geodata

Earlier posts chronicled the history even the beauty of historic shipping and climate data from CLIWOC. British, Dutch, French and Spanish maritime agencies transferred paper logs to digital records. In doing so look-up tables allowed to convert multi-lingual records into quantifiable attributes. Something odd (to me) happened in the process of mapping these: over 1/4M records doubled to almost 1/2M when look-ups were joined and then wind and direction tables merged to create maps symbolised by wind force and orientation.

The happenstance art of maps

I showed recently how CLIWOC weather data from ships captains logs dating 1662 to 1885 totalled almost 1/2M points. It started with a 1/4M ships tracks, and combining look-up tables from four maritime agencies they yield numeric wind force and direction...

Dynamic maps final (for now)

[Update1: longhand version posted on my map catalog blog
Update 2: companion Slideshare delves into technical issues]

This is the end installment of progressing from static to dynamic maps online. A few lessons learned along the way on posting a quarter million point dataset, which ballooned to almost half a million after links & joins...

Lessons from 'static to dynamic maps'

Last month related the stumbling blocks in posting too much data on arcgis.com - time animation pushed the limits of stock web service even when limits are set above 250K points - and other services don't offer animation as yet.

From static to dynamic maps, continued

Last month I reported on posting on arcgis.com some time-stamped, time-slider or time-aware maps - I showed my WhereIsAndrew map - I also mentioned how time-sliders are a great way to roll-up diverse datasets that are time dependent. CLIWOC Captain's ships logs was the other example cited, and I proceeded to post it as a service from ArcMap on arcgis.com.