David S. Read

I am excited to share the news that Blue Slate Solutions has kicked off a formal innovation program, creating a lab environment which will leverage the Cognitive Corporation™ framework and apply it to a suite of processes, tools and techniques.  The lab will use a broad set of enterprise technologies, applying the learning organization concepts implicit in the Cognitive Corporation’s™ feedback loop.

I’ve blogged a couple of times (see references at the end of this blog entry) about the Cognitive Corporation™.  The depiction has changed slightly but the fundamentals of the framework are unchanged.

The focus is to create a learning enterprise, where the learning is built into the system integrations and interactions. Enterprises have been investing in these individual components for several years; however they have not truly been integrating them in a way to promote learning.

By “integrating” I mean allowing the system to understand the meaning of the data being passed between them.  Creating a screen in a workflow (BPM) system that presents data from a database to a user is not “integration” in my opinion.  It is simply passing data around.  This prevents the enterprise ecosystem (all the components) from working together and collectively learning.

I liken such connections to my taking a hand-written note in a foreign language, which I don’t understand, and typing the text into an email for someone who does understand the original language.  Sure, the recipient can read it, but I, representing the workflow tool passing the information from database (note) to screen (email) in this case, have no idea what the data means and cannot possibly participate in learning from it.  Integration requires understanding.  Understanding requires defined and agreed-upon semantics.

This is just one of the Cognitive Corporation™ concepts that we will be exploring in the lab environment.  We will also be looking at the value of these technologies within different horizontal and vertical domains.  Given our expertise in healthcare, finance and insurance, our team is well positioned to use the lab to explore the use of learning BPM in many contexts.

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I had the pleasure of attending the Semantic Technology and Business Conference in Washington, DC last week.  I have a strong interest in semantic technology and its capabilities to enhance the way in which we leverage information systems.  There was a good selection of topics discussed by people with a variety of  backgrounds working in different verticals.

To begin the conference I attended the half day “Ontology 101” presented by Elisa Kendall and Deborah McGuinness.  They indicated that this presentation has been given at each semantic technology conference and the interest is still strong.  The implication being that new people continue to want to understand this art.

Their material was very useful and if you are someone looking to get a grounding in ontologies (what are they?  how do you go about creating them?) I recommend attending this session the next time it is offered.  Both leaders clearly have deep experience and expertise in this field.  Also, the discussion was not tied to a technology (e.g. RDF) so it was applicable regardless of underlying implementation details.

I wrapped up the first day with Richard Ordowich who discussed the process of reverse engineering semantics (meaning) from legacy data.  The goal of such projects being to achieve a data harmonization of information across the enterprise.

A point he stressed was that a business really needs to be ready to start such a journey.  This type of work is very hard and very time consuming.  It requires an enterprise wide discipline.  He suggests that before working with a company on such an initiative one should ask for examples of prior enterprise program success (e.g. something like BPM, SDLC).

Fundamentally, a project that seeks to harmonize the meaning of data across an enterprise requires organization readiness to go beyond project execution.  The enterprise must put effective governance in place to operate and maintain the resulting ontologies, taxonomies and metadata.

The full conference kicked off the following day.  One aspect that jumped out for me was that a lot of the presentations dealt with government-related projects.  This could have been a side-effect of the conference being held in Washington, DC but I think it is more indicative that spending in this technology is more heavily weighted to public rather than private industry.

Being government-centric I found any claims of “value” suspect.  A project can be valuable, or show value, without being cost effective.  Commercial businesses have gone bankrupt even though they delivered value to their customers.  More exposure of positive-ROI commercial projects will be important to help accelerate the adoption of these technologies.

Other than the financial aspect, the presentations were incredibly valuable in terms of presenting lessons learned, best practices and in-depth tool discussions.  I’ll highlight a few of the sessions and key thoughts that I believe will assist as we continue to apply semantic technology to business system challenges.

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I was recently asked about the SPARQL support in Sparql Droid and whether it could serve as a way for other Android applications to execute SPARQL queries against remote data sources.  It could be used in this way but there is a simpler alternative I’d like to discuss here.

On the Android platform it is actually quite easy to execute SPARQL against remote SPARQL endpoints, RDF data and local models.  The heavy lifting is handled by Androjena’s ARQoid, an Android-centric port of HP’s Jena ARQ engine.

Both engines (the original and the port) do a great job of simplifying the execution of SPARQL queries and consumption of the resulting data.  In this post I’ll go through a simple example of using ARQoid.  Note that all the code being shown here is available for download.  This post is based specifically on the queryRemoteSparqlEndpoint() method in the com.monead.androjena.demo.arqoid.SparqlExamples class.

Setup

To begin, some environment setup needs to be done in order to have a properly configured Android project ready to use ARQoid.

First, obtain the ARQoid JAR and its dependencies.  This is easily accomplished using the download page on the ARQoid Wiki and obtaining the latest ARQoid ZIP file.  Unzip the downloaded archive.   Since I’m discussing an Android application I’d expect that you would have created an Android project and that it contains a libs directory where the JAR files should be placed.

Second, add the JAR files to the classpath for your Android project.  I use the ADT plugin for Eclipse to do Android development.  So to add the JARs to my project I choose the Project menu item, select Properties, choose Build Path, select the Libraries tab, click the Add JARs… button, navigate to the libs directory, select the JAR files and click OK on the open dialogs.

Third, setup a minimal Android project.  The default layout, with a small change to its definition will work fine.

Overview

Now we are ready to write the code that uses ARQoid to access some data.  For this first blog entry I’ll focus on a trivial query against a SPARQL endpoint.  There would be some small differences if we wanted to query a local model or a remote data set.  Those will be covered in follow-on entries.

Here is a list of the ARQoid classes we will be using for this initial example:

• com.hp.hpl.jena.query.Query – represents the query being executed
• com.hp.hpl.jena.query.Syntax – represents the query syntaxes supported by ARQoid
• com.hp.hpl.jena.query.QueryFactory – creates a Query instance based on supplied parameters such as the query string and syntax definition
• com.hp.hpl.jena.query.QueryExecution – provides the service to  execute the query
• com.hp.hpl.jena.query.QueryExecutionFactory – creates a QueryExecution instance based on supplied parameters such as a Query instance and SPARQL endpoint URI
• com.hp.hpl.jena.query.ResultSet – represents the returned data and metadata associated with the executed query
• com.hp.hpl.jena.query.QuerySolution – represents one row of data within the ResultSet.

We’ll use these classes to execute a simple SPARQL query that retrieves some data associated with space exploration.  Talis provides an endpoint that we can use to access some interesting space exploration data.  The endpoint is located at http://api.talis.com/stores/space/services/sparql.
The query we will execute is:

SELECT ?dataType ?data
WHERE {
  <http://nasa.dataincubator.org/launch/1961-012> ?dataType ?data.
}

This query will give us a little information about Vostok 1 launched by the USSR in 1961.

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The Cognitive Corporation™ is a framework introduced in an earlier posting.  The framework is meant to outline a set of general capabilities that work together in order to support a growing and thinking organization.  For this post I will drill into one of the least mature of those capabilities in terms of enterprise solution adoption – Learn.

Business rules, decision engines, BPM, complex event processing (CEP), these all invoke images of computers making speedy decisions to the benefit of our businesses.  The infrastructure, technologies and software that provide these solutions (SOA, XML schemas, rule engines, workflow engines, etc.) support the decision automation process.  However, they don’t know what decisions to make.

The BPM-related components we acquire provide the how of decision making (send an email, route a claim, suggest an offer).  Learning, supported by data analytics, provides a powerful path to the what and why of automated decisions (send this email to that person because they are at risk of defecting, route this claim to that underwriter because it looks suspicious, suggest this product to that customer because they appear to be buying these types of items).

I’ll start by outlining the high level journey from data to rules and the cyclic nature of that journey.  Data leads to rules, rules beget responses, responses manifest as more data, new data leads to new rules, and so on.  Therefore, the journey does not end with the definition of a set of processes and rules.  This link between updated data and the determination of new processes and rules is the essence of any learning process, providing a key function for the cognitive corporation.

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Given my role as an enterprise architect, I’ve had the opportunity to work with many different business leaders, each focused on leveraging IT to drive improved efficiencies, lower costs, increase quality, and broaden market share throughout their businesses.  The improvements might involve any subset of data, processes, business rules, infrastructure, software, hardware, etc.  A common thread is that each project seeks to make the corporation smarter through the use of information technology.

As I’ve placed these separate projects into a common context of my own, I’ve concluded that the long term goal of leveraging information technology must be for it to support cognitive processes.  I don’t mean that the computers will think for us, rather that IT solutions must work together to allow a business to learn, corporately.

The individual tools that we utilize each play a part.  However, we tend to utilize them in a manner that focuses on isolated and directed operation rather than incorporating them into an overall learning loop.  In other words, we install tools that we direct without asking them to help us find better directions to give.

Let me start with a definition: similar to thinking beings, a cognitive corporation™ leverages a feedback loop of information and experiences to inform future processes and rules.  Fundamentally, learning is a process and it involves taking known facts and experiences and combining them to create new hypothesis which are tested in order to derive new facts, processes and rules.  Unfortunately, we don’t often leverage our enterprise applications in this way.

We have many tools available to us in the enterprise IT realm.  These include database management systems, business process management environments, rule engines, reporting tools, content management applications, data analytics tools, complex event processing environments, enterprise service buses, and ETL tools.  Individually, these components are used to solve specific, predefined issues with the operation of a business.  However, this is not an optimal way to leverage them.

If we consider that these tools mimic aspects of an intelligent being, then we need to leverage them in a fashion that manifests the cognitive capability in preference to simply deploying a point-solution.  This involves thinking about the tools somewhat differently.

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As I release my 3rd Alpha-version of Sparql Droid I thought I’d document a few lessons learned and open items as I work with the Android environment.  Some of my constraints are based on targeting smart phones rather than tablets, but the lessons learned around development environments, screen layouts, and memory management are valuable.

I’ll start on the development side.  I use Eclipse and the android development plugin is very helpful. It greatly streamlines the development process.  Principally, it automates the generation of the resources from the source files.  These resources, such as screen layouts and menus, require a conversion step after being edited.  The automation, though, comes at a price.

Taking a step back, Android doesn’t use an Oracle-compliant JVM.  Instead it uses the Dalvik VM.  This difference creates two major ramifications: 1) not all the standard packages are available; and 2) any compiled Java code has to go through a step to “align” it for Dalvik. This alignment process is required for class files you create and for any third-party classes (such as those found in external JAR files).  Going back to item 1, if an external JAR file you use needs a package that isn’t part of Dalvik, you’ll need to recreate it.

The alignment process works pretty fast for small projects.  My first application was a game that used no external libraries.  The time required to compile and align was indistinguishable from typical compile time.  However, with Sparql Droid, which uses several large third-party libraries, the alignment time is significant – on the order of a full minute.

That delay doesn’t sound so bad, unless you consider the Build Automatically feature in Eclipse.  This is a feature that you want to turn off when doing Android development that includes third-party libraries of any significance. Turning off that feature simply adds an extra step to the editing process, a manual build, and slightly reduces the convenience of the environment.

With my first Android project, I was able to edit a resource file and immediately jump back to my Java code and have the resource be recognized.   Now I have to manually do a build (waiting a minute or so) after editing a resource file before it is recognized on the code side.  Hopefully the plug-in will be improved to cache the aligned libraries, saving that time when the libraries aren’t being changed.

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The semantic technology concepts that comprise what is generally called the semantic web involve paradigm shifts in the ways that we represent data, organize information and compute results. Such shifts create opportunities and present challenges.  The opportunities include easier correlation of decentralized information, flexible data relationships and reduced data storage entropy.  The challenges include new data management technology, new syntaxes, and a new separation of data and its relationships.

I am a strong advocate of leveraging semantic technology.  I believe that this new paradigms provide a more flexible basis for our journey to create meaningful, efficient and effective business automation solutions. However, one challenge that differentiates leveraging semantic technology from more common technology (such as relational databases) is the lack of mature tools supporting a business system infrastructure.

It will take a while for solid solutions to appear.  Support for mainstream capabilities such as reporting, BI, workflow, application design and development that all leverage semantic technology are missing or weak at best.  Again, this is an opportunity and a challenge.  For those who enjoy creating computer software it presents a new world of possibilities.  For those looking to leverage mature solutions in order to advance their business vision it will take investment and patience.

In parallel with the semantic paradigm we have an ever increasing focus on mobile-based solutions. Smart phones and tablet devices, focused on network connectivity as the enabler of value, rather than on-board storage and compute power, are becoming the standard tool for human-system interaction.  As we design new solutions we must keep the mobile-accessible mantra in mind.

As part of my exploration of these two technologies, I’ve started working on a semantic technology mobile application called Sparql Droid. Built for the Android platform, my goal is a tool for exploring and mashing semantic data sources.  As a small first-step I’ve leveraged the Androjena port of the Jena framework and created an application with some basic capabilities.

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A few months ago I blogged about my new computer and my quest to use only OpenOffice as my document tool suite (How I Spent My Christmas Vacation).  For a little over a month I was able to work effectively, exchanging documents and spreadsheets with coworkers without incident.  However, it all came crashing down.  My goal in this blog entry is to describe what worked and what didn’t.

OpenOffice provides five key office-type software packages.  Writer for word processing, Calc for spreadsheets, Impress for presentations, Base for database work and Draw for diagrams.  There is a sixth tool, Math for creating scientific formulas and equations, which is similar to the equation editor available with MS Word.

As one of my coworkers suggests when providing positive and negative feedback, I’ll use the sandwich approach.  If you’ve not heard of this approach, the idea is to start with some good points, then go through the issues and wrap up with a positive item or two.

On a positive note, the OpenOffice suite is production worthy.  For the two tools that seem to be most commonly used in office settings, word processing and spreadsheets, the Writer and Calc tools have all the features that I was used to using with the Microsoft Office (MS Office) tools.  In fact for the most part I was unaware that I was using a different word processor or spreadsheet. From a usability perspective there is little or no learning curve for an experienced MS Office user to effectively use these OpenOffice tools.

Of key importance to me was the ability to work with others who were using MS Office.  The ability for OpenOffice to open the corresponding MS Office documents worked well at first but then cracks began to show.

OpenOffice Writer was able to work with MS Office documents in both the classic Word “doc” format and the newer Word 2007 and later “docx” format.  However, Writer cannot save to the “docx” format.  If you open a “docx” then the only MS Office format that can be used to save the document is the “doc” format.  At first this was a small annoyance but obviously meant that if a “docx” feature was used it would be lost on the export to “doc”.

Another aggravating issue was confusion when using the “Record Changes” feature, which is analogous to the “Track Changes” features in MS Word.  Although the updates made using MS Word could be seen in Writer, notes created in Word were inconsistently presented in Writer.  The tracked changes were also somewhat difficult to understand when multiple iterations of edits had occurred.  At work we often use track changes as we collaborate on documentation so this feature needs to work well for our team.

I eventually ran into two complete show-stoppers.  In the first case, OpenOffice was unable to display certain images embedded in an MS Word document.  Although some images had previously been somewhat distorted, it turned out that certain types of embedded images wouldn’t display at all.  The second issue involved the Impress (presentation) tool.

I’ve mentioned that Writer and Calc are very mature and robust.  The Impress tool doesn’t seem to be as solid.  As I began working with a team member on a presentation we were delivering in February I discovered that there appears to be little compatibility between MS PowerPoint and Impress. I was unable to work with the PowerPoint presentation using Impress.  The images, animations and text were all completely wrong when opened in Impress.

To be fair, I have created standalone presentations using Impress and the tool has a good feature set and works reliably.  I’ve used it to create and deliver presentations with no issues.  OpenOffice even seems to provide a nicer set of boilerplate presentation templates than the ones that come with MS PowerPoint.

My conclusion after working with OpenOffice now for about 3 months is that it is a completely viable solution if used as the document suite for a company. However, it is not possible to succeed with these tools in a heterogeneous environment where documents must be shared with MS Office users.

I will probably continue to use OpenOffice for personal work.  I’ll also continue to upgrade and try using it with MS Office documents from time to time.  Perhaps someday it will be possible to leverage this suite effectively in a multi-platform situation. Certainly from an ROI perspective it becomes harder and harder to justify the cost of the MS Office suite when such a capable and well-designed open source alternative exists.

Have you tried using alternatives to MS Office in a heterogeneous office tool environment?  Have you had better success than I have?  Any pointers on being able to succeed with such an approach?  Is such an approach even reasonable?  Please feel free to share your thoughts.

I was participating in a code review today and was reminded by a senior architect, who started working as an intern for me years ago, of a testing technique I had used with one of his first programs.  He had been assigned to create a basic web application that collected some data from a user and wrote it to a database.  He came into my office, announced it was done and proudly showed it to me.  I walked over to the keyboard, entered a bunch of junk and got a segmentation fault in response.

Although I didn’t have a name for it, that was a standard technique I used when evaluating applications.  After all, the tried and true paths, expected inputs and easy errors will be tested early and often as the developer exercises the application using the basic use cases.  As Boris Beizer said, “The high-probability paths are always tested if only to demonstrate that the system works properly.” (Beizer, Boris. Software Testing Techniques. Boston, MA: Thomson Computer Press, 1990: 76.)

It is unexpected input that is useful when looking to find untested paths through the code. If someone shows me an application for evaluation the last thing I need to worry about is using it in an expected fashion, everyone else will do that.  In fact, I default to entering data outside the specification when looking at a new application.  I don’t know that my team always appreciates the approach.  They’d probably like to see the application work at least once while I’m in the room.

These days there is a formal name for testing of this type, fuzzing.  A few years ago I preferred calling it “gorilla testing” since I liked the mental picture of beating on the application. (Remember the American Tourister luggage ad in the 1970s?)  But alas, it appears that fuzzing has become the accepted term.

Fuzzing involves passing input that breaks the expected input “rules”.  Those rules could come from some formal requirements, such as a RFC, or informal requirements, such as the set of parameters accepted by an application.  Fuzzing tools can use formal standards, extracted patterns and even randomly generated inputs to test an application’s resilience against unexpected or illegal input.

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The Internet is full of examples of simplifications creating vulnerabilities.  A good number of these can be represented as indirection enablers.  IP addresses, domain names, URIs, tiny URLs, QR Codes and now Microsoft tags.  Each of these serves the purpose of simplifying and decoupling.  We have seen many exploits for the first four, what about these last two?

As you likely know, QR Codes and Microsoft tags are graphical images targeted at print media, though there is no reason they can’t be used in an online fashion.  They are most often presented as rectangular graphics (examples below).  The reason for using them is to provide an easy way for someone to access a web page (or other online resource) related to the printed content.  Since these images represent character data they can also be used to house information, like contact details, that do not require online access to interpret.

The use case is simple: install a special program that interprets the codes or tags; point the camera from a smart phone or computer at the graphic; and voilà, your phone presents a web page, phone number or other embedded content. Basically this avoids having to manually enter a URL.  Depending on a company’s marketing strategy this is a powerful feature since a particular ad might want to direct a person to a URL that embeds  information about the specific advertisement, media source, publication page and so forth.  Typing in a complicated URL would put off many people but this removes most of the effort while making the print media interactive.

The main issues with adoption are educating the public about the use of these codes and getting people to install the reader software.  Some of you may recall Radio Shack trying to do something similar several years ago.  They created a scanning device, given out for free, that people had to connect to their PCs.  They could then scan a specific item in a Radio Shack catalog or advertisement and be brought to a web page with detailed information and ordering instructions.

Although that particular attempt failed, these newer approaches have the advantages of being broadly available, leveraging a common accessory on a smart phone (camera) and providing benefits to more than one company.  It will be interesting to see if any of the competing standards catch on with the general public (beyond the two mentioned already there are others such as Data Matrix, Quickmark and PDF417).

My concern, however, isn’t whether these graphical links become popular, it is whether they present another security risk. I believe that they do, in a manner similar to Tiny URLs, yet possibly more insidious.

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