Category Archives: R & D

Corresponds to my Staying Marketable theme

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.


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



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.

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



Learning SPARQL

As my quest for understanding Semantic Web technology continues, I am using several resources for the learning process.  This post is dedicated to the hard copy book entitled “Learning SPARQL” authored by Bob DuCharme, and published by O’Reilly.  At the time of this initial writing, I am only 2 chapters into the book, so stay tuned for updates as I progress through through the pages for additional feedback on this book’s content.  So far, I am very happy with the information presented as it is giving a good big picture view of RDF and using SPARQL as a tool to retrieve information from RDF-structured data.  I am initiating this post early in my reading because it already refers to many good online resources that I wish to capture at this time for reference as I continue through the book.

Online resources:


OSLC Primer

The newest BIG topic on my R&D radar is related to the Semantic Web.  As I am still new to figuring out best practices for using this WordPress website as my central repository and reference place, this content will start as a post and may later become a static page.  This post is also likely to evolve in the days, weeks, and possibly months ahead.  Maybe it needs to be a series.  I just don’t know yet.

Today I came across the acronym OSLC – Open Services for Lifecycle Collaboration.  In previewing this topic it became apparent that it needs to get on my active radar screen real soon, hence this blog post.  As part of my R&D efforts into the Semantic Web, I am looking at storage of Linked Data via RDF, RDFS, and OWL, as well as the applications to work with data stored using these structures.  It appears OSLC might be an overarching theme under which our Semantic Web development progress should occur.  Maybe not, but it is prudent at this juncture to not lose site of this initiative in case compliance with standards mandated by OSLC become best practices for Semantically-enabled applications.  We want to be at the forefront of the effort, not trying to catch up later.

With that said, here are some links to online content I have found:

  • OSLC Primer – a starting point for understanding the initiative
  • OSLC Main page – easy enough to get to once in the above link
  • Eclipse Lyo – impact TBD – however our development will use Eclipse
  • EA Cloud has full support for OSLC – whatever that means right now

.Stay tuned.  More I am sure to follow.