Recap: Don’t Shrink – Rethink

Excellent considerations for taking BPM automation to the mobile device:

5 Summary points at the end of the article should be on the table when eliciting requirements:

So in summary, my experience for optimizing the mobile “happy path” can be captured in 5 key points:
1)  Don’t shrink, rethink: While there is no magic number, users should instantly recognize that each touch or swipe takes them closer to their end goal. Look for unnecessary layers and remove them; see if tables, forms and buttons can be simplified.
2)  Incorporate navigational cues: Have you included a button that links to the start screen? Do your labels make sense – or do they scream ‘marketese’? Can you reduce call-to-action labels to three, two, or even one per step?
3)  Maximize native functions: Image and signature capture are both simple yet highly effective ways to streamline processes that are simply out of bounds for PC users.
4)  Incorporate apps: They’re quick, easy, and can cut development time in half. In our expenses claim example, adding a calendar, currency converter and mileage calculator are no-brainers.
5)  Get your (data) in order: A delighted customer doesn’t see any disruption when completing a transaction. So whether you’re linking with ECM (for documents), ERP (to update transactions) or CRM (for customer interactions) it’s essential that every link takes place as cleanly and efficiently as possible. Data virtualization and / or replication can link up all the necessary data in the loosest of couplings, making processes changes easy and flexible without the ‘hard coded’ bonds of the past.
In conclusion: redesigning processes from a mobile perspective is a skilled job requiring thought, time and vision. But by thinking about processes from the perspective of the mobile users that we all are, we will ultimately be on the right road.


So far this blog site has been really focused on content and links to resources related to Semantic Web technologies.  But with a main site theme designation being GIS, it is important to make sure I am providing a fair share of content related to this topic as well

Of particular interest is GIS development for mobile and web applications.  Today I ran across a reminder of OpenLayers, so I went to check out the OpenLayers web site.  It is up to version 3.2 and appears to be going string.  Therefore I will publish this post as a reference to this resource, and use it as reminder to keep developing content in mobile and web GIS realm.

OpenLayers main page


Today I ran across the first installment of a tutorial for developing mobile applications using PhoneGap.  The whole notion of the single codebase to create applications that will deploy across the major mobile platforms is of great interest to me, and PhoneGap is a development environment that promotes this capability.  Therefore I will provide the link here for my own reminder and access, which will also make it available for anyone else who is interested.

An Introduction to PhoneGap

Conceptual Heaven

Today I discovered a website that appears to be excellent resource for learning more about the application of SBVR to one’s Model Driven Architecture (MDA) development lifecycle.  There are free resources and a link to purchase the blog author’s book about the subject.  I have not read the book, but would expect it to contain a more layman-like explanation of the SBVR topic over the documents published by OMG.  The OMG publications are the de facto standard, but sometimes hard to digest, especially when new to a particular subject, so I am hoping this book will be a good primer leading to use of the OMG documentation for later reference.

Conceptual Heaven website

OMG SBVR landing page

Machine Learning Mastery

While browsing some resources made available by the Blacksburg Data Science Meetup Group, I came across this website entitled ‘Machine Learning Mastery’.  Since I have to get back to work soon, I haven’t had a chance to dive deep into its contents, but it appears to have a wealth of excellent material related to this subject.  Since Deep Learning appears to be a sub-topic to Machine Learning, I’ll tag this one as Machine Learning.

Link to: Machine Learning Mastery


Neural Networks and Deep Learning

While researching Semantic Web topics, I have started coming across references to the field of Deep Learning.  It appears to have morphed from earlier work in Neural Networks into a more evolved science.  I have heard that many folks are turned off by talk of Semantic Web technology because they presume it is very related to failed work in the Neural Networks field.  However, the two have different objectives, and even if they were closely related, it appears Deep Learning has taken the (presumably failed) work in Neural Nets in a new direction with productive promise.  Time will tell, but it appears to be something that should be put on one’s radar screen as it involves graph analysis as does Semantic Web technology, therefore the two might be complementary technologies in future applications.

Here is a link to a free online book bearing the title of this blog post.  I have yet to read its full contents, but my initial scan of its contents excited me to the point of writing this post so that I’ll have a quick reference link for my own use, and promote its availability for others on the Internet who might have a similar interest.

Neural Networks and Deep Learning, by Michael Neilsen, Dec 2014

Link to my own Deep Learning resources page




As a GIS geek with a keen interest in the Open Source movement, today’s discovery of LocationTech is worth writing about.  Thanks to the Eclipse Newsletter December 2014 issue, I have discovered yet another area of technology that should be high on my radar screen.

Here is a link to the main website for LocationTech under which several development projects exist.


Also noted in the newsletter is an article that predicts the huge growth potential of Open Source GIS implementation opportunities in the Utility space by the end of the decade, especially by small and medium operators.  This seems like a good opportunity to provide implementation services for someone or their company who have experience with these platforms.


Bayesian Statistics for Hackers

In conjunction with my ongoing learning about implementing technologies related to the Semantic Web is the topic of Bayesian statistical analysis.  The big picture idea is to use semantically stored, ontologically structured  data feeding Bayesian networks for statistical analysis in all kinds of risk assessment use cases.   The topic of Bayesian statistics is fairly math intensive, and for someone who has been out of hard core math and statistics for a couple decades, the re-training is coming along slowly.  Today I came across the following resource that appears to have a learning objective that aligns with my current learning needs on the topic.  I have yet to delve into the depths of this site’s contents, but will make this post, these initial comments, and a link to the site as a placeholder for my own future reference, and to provide a useful link in case someone else with in a similar situation might someday read these words.

Probabilistic Programming and Bayesian Methods for Hackers

Update 12/18/2014:

I have barely started reading through the contents of the site and have already come across a fascinating find:


This is the learning environment used by the contents of the book.

GIS on the Semantic Web

This blog is new, and so is my study of the Semantic Web and its related technologies.  However my study of GIS is not new at all.  In fact my keen interest in GIS goes back about 30 years now, and is the core technology around which my career has focused.

So as I have been adding content to this blog whose name features the acronym ‘GIS’, all of it has been related to pure Semantic Web research without a geospatial component.  In the unlikely event that someone happened across this blog, they would have to wonder about the disconnect between the blog name and its content.

Well finally it occurred to me how the two could and should be  researched and recorded in these pages, and that is: how can GIS be integrated with Semantic Web technology?   I will start with some ‘why’ questions to determine whether there is any benefit whatsoever to mix, or integrate, the two technologies.  I guess the first place to start is to determine what benefit is there to using Semantic data stores, with or without a geospatial content, over traditional RDBMS.

In any event, the reason for this particular post is to link back to another blog post I came across that reports the state of testing geospatial RDF stores.  I found it enlightening to see that many efforts are underway to integrate these two technologies, but at the same time got me thinking about several of the questions that I have just posed about justifying a purpose for doing so.  I think it is a good start for a path to pursue in answering these questions, and if it is clear that a benefit is realized by representing geospatial data in a semantic web context, on how to proceed.

Here is a link to the blog post, which in turn appears to have further links to this topic.

Geospatial RDF stores: where do we stand?

Updated later on 12/15/14

Note: The referenced blog post has an excellent white paper available for download.  In the white paper the following initiatives are mentioned and repeated here because they appear to have important future implications.

OGC Working Groups that are working on aspects of the GeoSPARQL standard are:

  • GeoSemantics Domain Working Group (DGW), and
  • GeoSPARQL Standard Working Group (SWG)

ISO 19125 and ISO 19107 are also standards that have been established by OGC for spatial feature representation.

Free Semantic Web Book!

While reviewing the list of resources for Learning SPARQL, from the book’s website, I came across a link to a book entitled: “Linked Data: Evolving the Web into a Global Data Space“, by Tom Heath and Christian Bizer.  Although this book is available for purchase in PDF and hard-copy formats, there is also a free HTML version available online.  I have not read the entire content of this resource, but did skim the Table of Contents and it appears to cover the breadth of Semantic Web topics related to Linked Data including RDF, OWL, and SKOS.  Free is good, and upon initial review it appears the site content at the following link is good, too.

Linked Data: Evolving the Web into a Global Data Space