Category Archives: Automated Enterprise Architecture Modeling

May 18, 2017 · 7:57 am

Michael Herman, Blockchain Developer, Enterprise Architect and Data Scientist: #Graphitization Inventor

Michael Herman is an expert when it comes to the mathematical modeling, analysis, and visualization of almost everything:

Large enterprise organizations,
Commercial, global-scale, cloud services platforms,
Organization principles and belief systems,
Human platforms,
Aircraft engines, and
Muscle cars.

Michael is the inventor of the #Graphitization Continous Transformation Model – a closed-closed loop feedback process for the ingestion, modeling, analysis, visualization, systems optimization, and life cycle management of any type of strategy, system, asset, architecture, or process.

Figure 1. #Graphitization Continuous Transformation Model

A key concept of #Graphitization is the implementation of Transformative Changes that result in positive increases in business value in the system being modeled.

#Graphitization

What is #Graphitization?

#Graphitization is a data science and enterprise architecture framework and process model for modeling, ingesting, organizing, analyzing, and visualizing any domain of endeavor by using graphs – networks of connected objects and relationships with each object and relationship annotated with additional descriptive information (metadata).

The primary applications of #Graphitization are:

System optimization,
Systems life cycle management, and
Transformative Change in resulting in positive increases in business value for the system being studied.

A system is defined as any collection of strategies, system components, assets, architectures or processes.

References

#Graphitization Continuous Transformation Model

The #Graphitization general model is described in Figure 2. as it applies to the design and optimization of large enterprise organizations.

Figure 2. #Graphization Continuous Transformation Model: Large Enterprise Organizations

The same model can also be used to improve the design and operation of many different types of systems:

Large scale enterprise organizations (public and private sector)
Aircraft engines, muscle cars, and other high-performance engine systems
Commercial, global-scale, cloud services platforms
Automated service composition of cloud services-based data systems
Large collaborative ecosystems: employee groups, business partners, social networks
Large ecosystems of competing or competitive business organizations
Organization principles and belief systems
Conventions software applications and architectures: desktop, server, and web apps
International standards for visual modeling languages
Parallelspace ModelMate
Enterprise Data Management
Internet of Things (IoT)
Architecture Reference Models

Standards

NEO Enhancement Proposal (NEP) Standards Author

Principal author: NEP-10 Composite Smart Contracts
“This NEP proposes a solution to the scenarios where a smart contract supports extensions to an existing standard. Conforming to this NEP involves implementing a single required, constant-valued operation and method `supportedStandards`, and possibly creating one or more new NEPs to define any new, required set(s) of required operations and methods.”
Reference: https://github.com/neo-project/proposals/blob/master/nep-10.mediawiki

Projects and Publications

0. SerentityData Graph

Model-based off-chain and on-chain (blockchain) graph data creation, migration, visualization, and analysis

Abstract

SerentityData Graph is an entity-relationship modeling, serialization, and graph analysis solution that supports development of traditional full-stack and blockchain smart contract applications. SerentityData features tight Neo4j integration for on-chain & off-chain graph data visualization and analysis.

Description

SerentityData Graph is an open source, entity-relationship modeling, serialization, and graph data visualization and analysis solution that supports the development of traditional full-stack, blockchain-based smart contract, and Neo4j graph database applications.

Starting from a single data model, SerentityData supports the automatic code generation of entities and relationships that support symmetric development of: (a) off-chain data in traditional multi-tier full-stack applications, (b) on-chain data management for blockchain-based distributed ledger technology apps (dApps), and (c) Neo4j enterprise graph applications.

SerentityData features complete life-cycle integration with Neo4j for on-chain and off-chain graph data creation, migration, visualization, and analysis. Live code walk-throughs and demonstrations will enable you to begin using SerenityData and Neo4j immediately. Github: https://github.com/mwherman2000/serentitydata-compiler

Resources

My blog: https://hyperonomy.com/

Related blog posts

Michael Herman, Blockchain Developer, Enterprise Architect and Data Scientist: #Graphitization Inventor https://hyperonomy.com/2017/05/18/michael-herman-inventor-of-graphitization/
#Graphitization of the Enterprise https://hyperonomy.com/2017/01/02/graphitization-of-the-enterprise/
Tokenize Every Little Thing (ELT) https://hyperonomy.com/2018/01/24/tokenization-of-every-little-thing-elt/
#Graphitization of .NET Applications: Marrying Open EA Data with Graph Databases https://hyperonomy.com/2016/10/19/crossing-the-ea-chasm-marrying-open-ea-data-with-graph-databases/
#Graphitization of Ray Dalio’s Principles: Iteration 1 https://hyperonomy.com/2016/12/29/graphitization-of-ray-dalios-principles/
#Graphitization of Ray Dalio’s Principles: Iteration 2 https://hyperonomy.com/2016/12/30/graphitization-of-ray-dalios-principles-iteration-2/
Crossing the EA Chasm: #Graphitization of ArchiMate 3.0 – Iteration 1 https://hyperonomy.com/2017/01/17/crossing-the-ea-chasm-graphitization-of-archimate-3-0/
Crossing the EA Chasm: #Graphitization of ArchiMate 3.0 – Iteration 2 https://hyperonomy.com/2017/02/08/crossing-the-ea-chasm-graphitization-of-archimate-3-0-iteration-2/
Crossing the EA Chasm: Automating Enterprise Architecture Modeling #1 https://hyperonomy.com/2016/10/22/crossing-the-ea-chasm-automating-enterprise-architecture-modeling/
Crossing the EA Chasm: Automating Enterprise Architecture Modeling #2 https://hyperonomy.com/2016/11/04/crossing-the-ea-chasm-automating-enterprise-architecture-modeling-2/
Crossing the EA Chasm: ArchiMate “Keep Calm and Have IT Your Way” https://hyperonomy.com/2016/11/17/crossing-the-ea-chasm-archimate-have-it-your-way/
Crossing the EA Chasm: Open Repository Strategies for Enterprise Architecture https://hyperonomy.com/2016/10/04/the-ea-chasm-open-repository-strategies-for-enterprise-architecture/
Crossing the EA Chasm: Enterprise Architecture Diagrams Your Grandmother (and CIO) Will Love https://hyperonomy.com/2016/10/13/archimate-diagrams-your-grandmother-and-cio-will-love/
#Graphitization of ArchiMate: Getting MMOR from ArchiMate using the ModelMate Master Online Repository https://hyperonomy.com/2017/02/10/crossing-the-ea-chasm-how-to-use-the-modelmate-online-repository-mmor/
#Graphitization of the Amazon Leadership Principles (introducing Personal Leadership Principle Maps) – Iteration 1 https://hyperonomy.com/2017/05/08/amazons-principles/
What are the differences between improving the design (and operation) of an aircraft engine, a muscle car, a large enterprise, and/or an integrated commercial global cloud services platform …all running at hyperscale? https://hyperonomy.com/2017/04/10/whats-the-difference-between-improving-the-design-and-operation-of-an-aircraft-engine-a-muscle-car-a-large-enterprise-and-a-commercial-global-cloud-services-platform/

Live Neo4j Models

http://hobby-icgaeohcoeaggbkeabhldpol.dbs.graphenedb.com:24789/browser/ Userid: ModelMate_Master_Datasets10 Password: YqeZAH4ODEJqglkEsK5p

YouTube Channel: https://www.youtube.com/playlist?list=PLU-rWqHm5p46bIDXPNf4c2JP_AOkopnV5

12. NEO Persistable Classes (NPC) Platform 2.1: Preview https://www.youtube.com/watch?v=N-jiJOZwiFg&list=PLU-rWqHm5p46bIDXPNf4c2JP_AOkopnV5&index=5
NEO Persistable Classes (NPC) Platform 2.0: Deep Dive https://www.youtube.com/watch?v=Nj4-m2o94VE&list=PLU-rWqHm5p46bIDXPNf4c2JP_AOkopnV5&index=6
NEO Persistable Classes 1.0: Deep Dive (Video 2 of 3) [Update 1] https://www.youtube.com/watch?v=qwteL1BiCjM&list=PLU-rWqHm5p46bIDXPNf4c2JP_AOkopnV5&index=7
NEO Persistable Classes Platform 2.2: Structured Storage & Reusable, Indexed, Non-Fungible Entities https://www.youtube.com/watch?v=vnAxyCAZ1ec&list=PLU-rWqHm5p46bIDXPNf4c2JP_AOkopnV5&index=10

Related Github Projects

SerentityData Entity Compiler (serentitydata-compiler) https://github.com/mwherman2000/serentitydata-compiler/blob/master/README.md
NEO Persistable Classes (NPC) Compiler 2.1 (npcc) – Compiler for the NEO Persistable Classes (NPC) Platform 2.1 https://github.com/mwherman2000/neo-npcc2
NEO Persistable Classes V1.0 – An Efficient Object-Oriented Framework for C#.NEO Smart Contract Development (ORIGINAL) – https://github.com/mwherman2000/neo-persistibleclasses

Recognition

NeoDraw – NEO Persistable Classes Platform 2.0: NEO-Microsoft dApp Competition (4th place prize – USD$15,000) – https://neo.org/blog/details/3074 and https://neo.org/awards.html

Keywords

blockchain on-chain data modeling symmetric programming data management .NET C# NEO Stratis Ethereum Technical Case Study Developer Best Practices

1. Large scale enterprise organizations (public and private sector)

The first applications of #Graphitization were in the field of traditional enterprise architecture modeling and analysis:

Business Architecture
Application Architecture
Technology/Infrastructure Architecture

References

2. Aircraft engines, muscle cars, and other high-performance engine systems

It turns out that the modeling and analysis of any complex system is an ideal candidate for #Graphitization.

References

What are the differences between improving the design (and operation) of an aircraft engine, a muscle car, a large enterprise, and/or an integrated commercial global cloud services platform …all running at hyperscale?

3. Commercial, global-scale, cloud services platforms

One particularly important application is the modeling and analysis of very large, commercial, global-scale, cloud services platforms.

References

What are the differences between improving the design (and operation) of an aircraft engine, a muscle car, a large enterprise, and/or an integrated commercial global cloud services platform …all running at hyperscale?

4. Automated service composition of cloud services-based data systems

Call the solution “Expedia for Microsoft Azure/AWS/SFDC/…” or whatever you prefer, today’s commercial cloud services platforms are still a pain in the ass to use for creating non-trivial applications. Left, right, and center you have to hand-code a myriad of worker processes simply to reformat and pass data around.

#Graphitization is an optimal approach for modeling the underlying cloud services platform services catalog.

References

5. Large collaborative ecosystems: employee groups, business partners, social networks

Project “Boston” is named after some potential business partners and the embryo for the idea coming from my months as a founding Groove Networks business partner (including many of my most important relationships that I still maintain today).

6. Large ecosystems of competing or competitive business organizations

Modeling of large ecosystems of competing/competitive business organizations is a straightforward #Graphitization use case.

7. Organization principles and belief systems

On the surface, the #Graphitization of principle and belief-based frameworks is pretty straightforward but this is because the basic #Graphitization serves as the substrate for many advanced data ingestion, analysis, and visualization projects.

Below are the results of the #Graphitization of two principle and belief-based frameworks:

Bridgewater Associates: Ray Dalio’s Principles
Amazon: Jeff Bezos’ Amazon Leadership Principles

References

8. Conventional software applications and architectures: desktop, server, and web apps

Modeling of complex, multi-language, multiple runtime software environments is a use case that is an ideal application of #Graphitization.

References

9. International standards for visual modeling languages

A significant investment has been made in applying #Graphitization to language modeling; specifically, languages for enterprise architecture like ArchiMate.

ArchiMate References

10. Enterprise Data Management

Modeling and analyzing enterprise data structures and stores is a common application of #Graphitization; including the modeling of taxonomies and master data.

References

RE: Managing Master Data With ArchiMate

11. Parallelspace ModelMate

Parallelspace ModelMate is an approach (platform and language framework) for creating domain specific languages (DSLs) for enterprise architecture. It is realized using #Graphitization and the ArchiMate enterprise architecture modeling language.

References

12. Internet of Things (IoT)

IoT is an interesting beast. It is a reference to an application service for processing raw events from a device or dynamically generated events from a software system. IoT also defines a conceptual software and data flow architecture that can also be used for the dynamic creating and maintenance of complex systems such as large enterprise architectures.

References

13. Architecture Reference Models (ARMs)

An ARM is easily modeled (and analyzed) using #Graphitization. SharePoint and Azure Stack are two good examples.

References

General References

Continuous Transformation and Transformative Change are key principles of the Total Enterprise Architecture Model (TEAM) (click here)
To dig deeper, check out Graphitization of the Enterprise (click here)
[Enterprise Architecture, Big Data, CRM, ERP, …] Tools and Methods Don’t Generate Business Value (click here)
Crossing the EA Chasm: The Surveyor

Best regards,

Michael Herman
Enterprise Architect and Data Scientist
Parallelspace Corporation
M: 416 524-7702
E: mwherman@parallelspace.net
B: http://hyperonomy.com
L: https://www.linkedin.com/in/mwherman/recent-activity/posts/
Skype: mwherman2000

Living at the intersection of Enterprise Architecture, Enterprise Knowledge, and Data Science

ArchiMate is registered trademark of The Open Group.

1 Comment

Filed under ArchiMate, Architecture Reference Models, Automated Application Architecture Analysis, Automated Enterprise Architecture Modeling, Graphitization, How do we think, Microsoft Azure, ModelMate Information Architecture for ArchiMate, ModelMate Information Architecture for Languages

February 8, 2017 · 4:44 pm

Crossing the EA Chasm: #Graphitization of ArchiMate 3.0 – Iteration 2

First Draft: April 5, 2017

This article documents a number of parallel efforts to improve the usability, understandability, utility, and correctness of the ArchiMate 3.0 Specification. In particular, this article extends a well-received previous article Crossing the EA Chasm: Graphitization of ArchiMate 3.0 – Iteration 1 where I posed the question:

Wouldn’t it be nice to have an authoritative reference for ArchiMate 3.0, more specifically, a repository for the enterprise architecture language‘s elements and relationship matrix, that is queryable.

This article documents the current iteration of the ModelMate project, Iteration 2, whose goal is to create an improved queryable repository for a corrected version of relationship matrix (more correct relative to the Appendix B tables in the current ArchiMate 3.0 Specification).

Background

Over the past few months, I’ve written several articles commenting on the current state of the ArchiMate language for Enterprise Architecture including:

In addition, there are almost weekly postings about usability issues or errors with the Specification in the Linkedin ArchiMate group, the GitHub Archi issues log, LinkedIn Pulse, and the Google ArchiMate group; as well as other forums [1][2].

The recent effort, called the ModelMate project, is a focused effort to create a more broadly applicable, usable, useful, ArchiMate-based, extensible language environment for enterprise architecture as described in these 4 articles:

Current Scenario

The current scenario is highlighted by the following points taken from the above references:

“[People should be] encouraged to try to model these examples for yourself: to start learning how to “think in ArchiMate” as your second or third written language.” The way the ArchiMate language is currently designed and, more importantly, described makes this difficult.
In an abstract sense, the extension of the ArchiMate language is supported but, in reality, few if any broadly adopted extensions have appeared in the market. A better approach is described here: Crossing the EA Chasm: ArchiMate 3.0, fix it or re-purpose it?
There is no single, authoritative, machine-readable version of the ArchiMate 3.0 relationship matrix; let alone one that is easily accessible and queryable.
The Open Group’s insistence on using abstract terminology to name element types and relation types presents users with additional challenges.

Problem Description

At a data level, the root causes of the problems with the ArchiMate 3.0 relationship matrix in Appendix B of the ArchiMate 3.0 Specification include:

No machine-readable version of the tables are available for external validation for correctness
The tables contain errors in the approximately 11,000 relations that are represented in the tables. Is is estimated that there are few hundred to a few thousand errors present in the current ArchiMate 3.0 tables
The tables contain all possible (valid) relations but do not differentiate between Core relations and Derived (non-Core) relations.

All three issues are critical for the ArchiMate 3.0 Specification and these tables to be trusted and more generally useful.

In addition, the Derived Relation Derivation Algorithm has never been published by The Open Group. Attempts to create an alternative algorithm have highlighted that the text of the ArchiMate 3.0 Specification is neither consistent nor complete when it comes to identifying the set of Core Relations and a correct and complete Derviation Algorithm.

Lastly, when dealing with 1000+ Core Relations and several thousand Derived Relations (8000-9000 or more), it’s difficult to analyze and visualize what the ArchiMate 3.0 relationship matrix looks like in total, or when subdivided by Domain (Layer) or Aspect, or when focused on a specific element prototype (e.g. Node).

Solution Overview

The goal of this solution is to publish a very detailed, rich, unnormalized version of the latest and greatest ArchiMate 3.0 relationship matrix in multiple formats; including:

CSV text file
Microsoft Excel workbook
Microsoft Access database
Neo4j Cypher Query Language (CQL) queryable graph database file

When loaded into Microsoft Excel, the CSV and Microsoft Excel workbook format files appear as shown in Figure 1 (below).

Figure 1. ModelMate Master Datasets: Excel 2016 and CSV File Formats

The Microsoft Excel (and CSV) format file can also be used with the Microsoft Excel Web App (Figure 2) and the Microsoft Excel format can be used to create custom SharePoint lists (Figure 3).

Figure 2. ModelMate Master Datasets: Excel 2016 format file in MIcrosoft Excel Web App

Figure 3. ModelMate Master Datasets: Custom SharePoint List created from Imported Excel 2016 Format File

When loaded into Microsoft Access, the Microsoft Access database format files appear as shown in Figure 4 (below).

Figure 4. ModelMate Master Datasets: MS Access Database file format

To create a queryable graph database version of the ArchiMate 3.0 relationship tables (in effect, the entire ArchiMate 3.0 metamodel), the Cypher Query Language (CQL) file depicted in Figure 5. was created.

Figure 5. ModelMate Master Datasets: Neo4j CQL File

Figure 6 is an example of the output from a single line CQL query run against the ArchiMate 3.0 graph database (implemented using Neo4j). If you look closely at the CQL statement at the top of this screen shot (click Figure 6. to enlarge it), you’ll see that it is selecting all of the relationships across all of the element prototypes in the Technology/Infrastructure domain of the ArchiMate 3.0 metamodel that connect to the Node element prototype.

Figure 6. ModelMate Master Datasets: Graph Mining Analysis Sample

File Downloads

You can download the files referred to in this article from the GitHub repository. Click here to download the ModelMate Master Datasets files.

In addition, there is a Neo4j Cypher Query Language (CQL) file available for download that will ingest all of the element prototypes and relations into a graph database using a single Neo4j shell invocation. From the Windows Powershell or Windows Command Prompt, use:

“C:\Program Files\Java\jre1.8.0_91\bin\java.exe” -classpath “C:\Program Files\Neo4j CE 3.0.6\bin\neo4j-desktop-3.0.6.jar” org.neo4j.shell.StartClient -c dump > MasterDataSet.cql

Lastly, there is Microsoft Access 2016 database version of the CSV file that is available for download if you prefer using Microsoft Access SQL queries or graphical SQL queries.

Solution Details

Below is a copy of the workflow and dataflow used to create the Parallelspace ModelMate Master Datasets. It’s not as messy as it looks – it’s true mashup and a valuable one at that. It’s primarily the result of the truly ad-hoc collaboration between 3 enterprise architecture professionals with an interesting mix of diverse goals (Gerben Wierda, Ed Roberts and myself); each of us with our own set of preferred development technologies and goals (with Excel being the greatest common denominator (GCD)).

Figure 7. ArchiMate 3.0 Relationship Matrix Resolution Process

The numbered steps in Figure 7. are explained below:

Data Sources. There are many sources of information about the ArchiMate relationship matrix in addition to the Appendix B tables in the ArchiMate 3.0 Specification. The list in Figure 7. is a fairly complete. Key data sources include the GitHub Archi repository for the most widely used ArchiMate modeling tool for enterprise architecture and Gerben Wierda’s multiple ArchiMate resources publishing under the Mastering ArchiMate brand.

“MA Core Set” Spreadsheet. Wierda worked to consolidate various data sources from Step 1 above to create the “MA Core Set” Mastering ArchiMate relationship matrix (plus a number of other relationship matrices that Wierda used for comparative analysis and troubleshooting purposes). The “MA Core Set” represents the “seed” or Core Set of (non-derived) ArchiMate relations. Wierda created this Core Set over several iterations reviewing the word-for-word text of the Specification, the inheritance diagrams, as well as incorporating his extensive practical knowledge and experience documenting ArchiMate in the book entitled Mastering ArchiMate – Edition II.

The “MA Core Set” tab in the AllowedRelationsArchiMate30VBA-public.xlsm Excel spreadsheet also includes additional columns that are reserved for calculating and storing an intermediate 3-column, reverse-transposed version of the relationship matrix (Step 3 below).

CreatePrologList() Visual Basic for Applications (VBA) Macro: This macro is used to perform the actual reverse-transposition of the “MA Core Set” relationship matrix into the 3-column format which including a column for storing the relation(source,target) 3-tuple formatted data (in Prolog format). The 2-D relationship matrix is the input to the macro (along with some additional master data tables that are part of the VBA code). The 3-tuples are the essential output of the VBA macro (stored “in-place” in the first 3 columns of the spreadsheet).

CoreSet.prolog File. To proceed through to the next step of the workflow, the Prolog format data is copied from the spreadsheet and pasted into a plain text file called CoreSet.prolog, for example (or any other filename you would like to use).

Derivaton.py Python Script and outfile.csv. The Derivation.py script contains is the “magic sauce”. Written by Wierda, Derivation.py reads the CoreSet.prolog file and executes a complex and detailed algorithm to expand the Core Set of ArchiMate relations read from the CoreSet.prolog file into a number of alternative output formats, including CSV and Prolog formats.

To support the ModelMate project, a version of Derivation.py was modified to output a number of additional CSV columns (outfile.csv). Columns:

SourceElement
TargetElement
Relation
RelativeStrength
IsInputRelation
StandardVersion
ScriptVersion

Outfile.xml File. Steps 6 and 7 are part of a sequence of activities that were used to create a relationships.xml file that is compatible with the relationship configuration requirements of the Archi modeling tool. This process, originally implemented by Ed Roberts, owner of Dallas-based Elparazim, uses Excel to load the outfile.csv save it out as an outfile.xml file.

For Step 7, Ed Roberts wrote an XSL Transform script that when applied to the outfile.xml file creates the Archi-compatible relationship.xml that is used by the Archi model to automatically configure the element-element relations supported in a given version of Archi (e.g. Archi 4.0).

Steps 8-10 mark an alternative data flow created to support the needs of the ModelMate Master Datasets project.

In Step 8, the contents of the ModelMate-compatible modified CSV output from Step 5 (outfile.csv) is copy-and-pasted into the Parallelspace_ModelMate_MasterDatasets_CoreAndDerivedNN.xlsx Excel workbook (where NN is a version number).

A matrix of automated Excel functions in the Complete spreadsheet merge the elements and relations master data attributes from the Elements and Relations spreadsheet with the data from the Derived spreadsheet to compute the corresponding column values in the Complete spreadsheet. Think of the Complete spreadsheet as a super-unnormalized version of the relationship matrix. The InInputRelation column values indicate whether a specific relation (and it’s companion source and target elements) are Core relations or Derived relations.

The workbook contains 4 spreadsheets (Derived, Complete, Elements, and Relations):

Derived spreadsheet – copy-and-pasted version of the outfile.csv from Step 4. The “input” spreadsheet.
Columns:
1. SourceElement
2. TargetElement
3. Relation
4. RelativeStrength
5. IsInputRelation
6. StandardVersion
7. ScriptVersion
Complete spreadsheet – leverages the master data in the Elements and Relations tabs to expand the columns in the Derived spreadsheet to include additional metadata property columns for the source and target elements as well as the relations. The “output” spreadsheet that will be saved as a CSV file in Step. 9.
Columns:
1. SourceElement
2. TargetElement
3. Relation
4. RelativeStrength
5. IsInputRelation
6. StandardVersion
7. ScriptVersion
8. RelationName
9. RelationLabel
10. RelationQualifiedLabel
11. RelationForwardVerbLabel
12. RelationReverseVerbLabel
13. RelationQualifiedForwardVerbLabel
14. RelationQualifiedReverseVerbLabel
15. SourceName
16. SourceLabel
17. SourceQualifiedLabel
18. TargetName
19. TargetLabel
20. TargetQualifiedLabel
21. SourceDomainName
22. SourceDomainLabel
23. SourceDomainQualifiedLabel
24. SourceAspectName
25. SourceAspectLabel
26. SourceAspectQualifiedLabel
27. TargetDomainName
28. TargetDomainLabel
29. TargetDomainQualifiedLabel
30. TargetAspectName
31. TargetAspectLabel
32. TargetAspectQualifiedLabel
Elements spreadsheet – master data attributes and values for each element prototype.
Columns:
1. ElementCode
2. ElementLabel
3. ElementName
4. ElementQualifiedLabel
5. DomainName
6. DomainLabel
7. DomainQualifiedLabel
8. AspectName
9. AspectLabel AspectQualifiedLabel
Relations spreadsheet – master data attributes and values for each relation prototype.
Columns:
1. RelationCode
2. RelationName
3. RelationQualifiedLabel
4. RelationForwardVerb
5. RelationQualifiedForwardVerb
6. RelationReverseVerb
7. RelationQualifiedReverseLabel

In Step 9, columns 4-32 of the Complete spreadsheet are saved as a separate CSV format file (using the same versioned file name as the parent workbook but with a suffix of .csv).

Also considered part of Step 9, the CSV file is imported into an empty Microsoft Access database. The datatype of the InInputRelation is changed to be a Yes/No (boolean) field. The database file is given the same name as the CSV file but with a suffix of .accdb.

Step 10 uses a series of Cypher Query Language (CQL) script files to create and populate a Neo4j graph database – to enable simple but powerful ad-hoc queries against the ArchiMate 3.0 relationship tables/metamodel.

Step 10.1. Merge all of Source and Target Element Prototypes

Script 1. Merge Source and Target Element Prototypes

Step 10.2. Label Elements with Element, Domain and Aspect Names

Script 2. Label Elements with Element, Domain and Aspect Names

Step 10.3 Create the Metamodel Relationships

TODO

Results

Use Cases

This section documents the results of the following use cases (queries against the Neo4j graph model):

All Business domain source and target element prototypes and all related Core and Derived relationships
All Core relationships where the source element prototype is from the Business domain
All Core relationships where the source and target element prototypes are from the Business domain
All Application domain source and target element prototypes and all related Core and Derived relationships
All Core relationships where the source and target element prototypes are from the Application domain
All Core and Derived relationships where the source and target element prototypes are from the Technology/Infrastructure domain
All Core relationships where the source and target element prototypes are from the Technology domain
All Core relationships where the source and target element prototypes are from the Technology domain and are identical to each other
All Core relationships where the source and target element prototypes are from the Technology domain and are different from each other (non-self referencing)
All Core and Derived relationships where the source and target element prototypes are from the Technology domain and are different from each other (non-self referencing)
All Core and Derived relationships where the source and target element prototypes are from the Technology domain and connected to the Node element prototype
All Core relationships where the source and target element prototypes belong to the Passive Structure aspect
All Core relationships where the source and target element prototypes belong to the Active Structure aspect
All Core relationships where the source and target element prototypes belong to the Behavior aspect

Use Case Results

Click on any of the figures to enlarge them in a separate browser tab.

Business Domain Use Case Results

Use Case 1: All Business domain source and target element prototypes and all related Core and Derived relationshipsUse Cases

Figure 8. is the result of an ad-hoc CQL query against all element prototypes in the Business domain; more specifically, where both the source and target element prototypes are in the Business domain.

Figure 8. All Business domain source and target element prototypes and all related Core and Derived relationships

Use Case 2: All Core relationships where the source element prototype is from the Business domain

Figure 9. is the result of an ad-hoc CQL query against all Core relationships where the source element prototype is from the Business domain.

Figure 9. All Core relationships where the source element prototype is from the Business domain

Use Case 3: All Core relationships where the source and target element prototypes are from the Business domain

Figure 10. is the result of an ad-hoc CQL query against all Core relationships where both the source and target element prototypes are from the Business domain.

Figure 10. All Core relationships where the source element prototype is from the Business domain

Application Domain Use Case Results

Use Case 4: All Application domain source and target element prototypes and all related Core and Derived relationships

Figure 11. is the result of an ad-hoc CQL query against all element prototypes in the Application domain; more specifically, where both the source and target element prototypes are in the Application domain.

Figure 11. All Application domain source and target element prototypes and all related Core and Derived relationships

Use Case 5: All Core relationships where the source and target element prototypes are from the Application domain

Figure 12. is the result of an ad-hoc CQL query against all Core and Derived relationships where the source element prototype is from the Application domain.

Figure 12. All Core relationships where the source and target element prototypes are from the Application domain

Technology Domain Use Case Results

Use Case 6: All Core and Derived relationships where the source and target element prototypes are from the Technology/Infrastructure domain

Figure 13. is the result of an ad-hoc CQL query against all Core relationships where both the source and target element prototypes are from the Technology/Infrastructure domain.

Figure 13. All Core and Derived relationships where the source and target element prototypes are from the Technology/Infrastructure domain

Use Case 7: All Core relationships where the source and target element prototypes are from the Technology domain

Figure 14. is the result of an ad-hoc CQL query against all Core relationships where both the source and target element prototypes are from the Technology domain.

Figure 14. All Core relationships where the source and target element prototypes are from the Technology domain

Use Case 8: All Core relationships where the source and target element prototypes are from the Technology domain and are identical to each other

Figure 15. is the result of an ad-hoc CQL query against all Core relationships where both the source and target element prototypes are from the Technology domain and are identical to each other.

Figure 15. All Core relationships where the source and target element prototypes are from the Technology domain and identical to each other

Use Case 9: All Core relationships where the source and target element prototypes are from the Technology domain and are different from each other (non-self referencing)

Figure 16. is the result of an ad-hoc CQL query against all Core relationships where both the source and target element prototypes are from the Technology domain and are different from each other (non-self referencing).

Figure 16. All Core relationships where the source and target element prototypes are from the Technology domain and different from each other (non-self referencing)

Use Case 10: All Core and Derived relationships where the source and target element prototypes are from the Technology domain and are different from each other (non-self referencing)

Figure 17. is the result of an ad-hoc CQL query against all Core and Derived relationships where both the source and target element prototypes are from the Technology domain and are different from each other (non-self referencing).

Figure 17. All Core and Derived relationships where the source and target element prototypes are from the Technology domain and are different from each other (non-self referencing)

Use Case 11: All Core and Derived relationships where the source and target element prototypes are from the Technology domain and connected to the Node element prototype

Figure 18. is the result of an ad-hoc CQL query against all Core and Derived relationships where both the source and target element prototypes are from the Technology domain and are connected to the Node element prototype.

Figure 18. All Core and Derived relationships where the source and target element prototypes are from the Technology domain and connected to the Node element prototype

Aspects Use Case Results: Passive Structure, Active Structure, Behavior

Use Case 12: All Core relationships where the source and target element prototypes belong to the Passive Structure aspect

Figure 19. is the result of an ad-hoc CQL query against all Core relationships where the source and target element prototypes belong to the Passive Structure aspect.

Figure 19. All Core relationships where the source and target element prototypes belong to the Passive Structure aspect

Use Case 13: All Core relationships where the source and target element prototypes belong to the Active Structure aspect

Figure 20. is the result of an ad-hoc CQL query against all Core relationships where the source and target element prototypes belong to the Active Structure aspect.

Figure 20. All Core relationships where the source and target element prototypes belong to the Active Structure aspect

Use Case 14: All Core relationships where the source and target element prototypes belong to the Behavior aspect

Figure 21. is the result of an ad-hoc CQL query against all Core relationships where the source and target element prototypes belong to the Behavior aspect.

Figure 21. All Core relationships where the source and target element prototypes belong to the Behavior aspect

Feedback

Please add your comments and feedback to the end of this article.

Best regards,
Michael Herman (Toronto)
Parallelspace Corporation
mwherman@parallelspace.net

*ArchiMate is a registered trademark of The Open Group.

1 Comment

Filed under ArchiMate, Architecture Reference Models, Automated Enterprise Architecture Modeling, Crossing the EA Charm, Definitions, Domain Specification Languages (DSL), Enterprise Architecture, Enterprise Architecture Chasm, graph database, Graphitization, ModelMate, ModelMate Information Architecture for ArchiMate, ModelMate Information Architecture for Languages, Progressive Enterprise Architecture Map (PEAM), The Open Group

Tagged as Archi, ArchiMate, Graphitization

January 27, 2017 · 2:58 pm

Crossing the EA Chasm: ArchiMate 3.0, fix it or re-purpose it?

It is the end of January 2017 and, recently, there has been a lot of discussion in the LinkedIn ArchiMate group about the ArchiMate language for enterprise architecture (EA), its “idioms”, usability, adoption, etc.

In addition, in the article Crossing the EA Chasm: Reflections on the Current State of ArchiMate, I asked some questions related to ArchiMate’s purpose and whether it is adequately addressing all of enterprise architecture’s stakeholders’ needs. Crossing the EA Chasm: Re-visioning the ArchiMate Specification is a related article.

These discussions led to this short-form question, the key topic for today:

ArchiMate 3.0, fix it or re-purpose it?

Fixing ArchiMate

On the “fix it” side of the discussion, people will literally be working to fix the language forever. The Open Group is committed to supporting these kinds of efforts; it’s the foundation for why they exist.

But is there a better, compatible approach? I think there is.

Re-purposing ArchiMate

As a starter, let’s look at the evolution of and technology hierarchy that supports high-level programming languages. Pick your favorite language. Many of you will choose Java; I’m a C# person. (It doesn’t really matter.)

Before the advent of managed, cross-platform execution environments (like the Java VM and the .NET Runtime that provide memory management and garbage collection, advanced exception management, data protection, secure execution contexts, etc.), prior languages like C and C++ followed a simple compilation model as illustrated in Figure 1.

Figure 1. C/C++ Compilation Model

This scenario is synonymous with the current lower-level language support available in ArchiMate 3.0. There’s effectively one language level and that’s all you have.

The C# (.NET) compilation model ups the ante by introducing a cross-platform intermediate language (Microsoft Intermediate Language (MSIL)) as shown in Figure 2. Java achieves something similar using Java bytecode.

Figure 2. C# Compilation Model: Role of the Microsoft Intermediate Language (MSIL)

Re-purposing ArchiMate as a Lower-Level Intermediate EA Language

In an approach similar to the way the .NET Framework uses MSIL, ArchiMate can be re-purposed as the lower-level intermediate language for creating higher-level EA languages.

The article Modeling a Company and Its Locations, Markets, Employees, Investors & Roles: Proposals, Wishes & Dreams is a small but real-life, practical example of how this can be executed to create a new EA language for describing Business Organizations (as illustrated below in Figure 3).

Figure 3. Business Organization EA Language, an ArchiMate 3.0 Specialization

This approach more easily and more formally supports the concept of domain-specific languages (DSLs) for enterprise architecture.

As The Open Group moves ArchiMate forward, the published higher-level EA languages can incrementally adopt the new changes – in the same way the Java JIT compilers and Microsoft JIT compilers are updated to adopt new instruction sets from Intel or AMD.

Making It Real

The Archi modeling tool can ~~easily~~ be adapted to serve as the reference implementation for these new EA languages. This is relatively easy to accomplish because all of the ArchiMate relationships remain the same; and, at least initially, it’s ~~simply~~ a matter of extending Archi’s existing ArchiMate elements with families of new elements that address the scope of each new EA DSL. It is a SMOP.

More food for thought… Please post your comments below.

Best regards,
Michael Herman (Toronto)
Parallelspace Corporation
mwherman@parallelspace.net

*ArchiMate is a registered trademark of The Open Group.

4 Comments

Filed under ArchiMate, Architecture Reference Models, Automated Enterprise Architecture Modeling, Crossing the EA Charm, Domain Specification Languages (DSL), Enterprise Architecture, Enterprise Architecture Chasm, The Open Group

Tagged as ArchiMate, Architecture Reference Models, Domain Specific Languages, DSL, ModelMate, MSIL

January 25, 2017 · 4:39 pm

Modeling a Company and Its Locations, Markets, Employees, Investors & Roles: Proposals, Wishes & Dreams

This article presents some new approaches for modeling answers to the following frequently asked question:

How do I model X in ArchiMate?

NOTE: You are encouraged to try to model these examples for yourself: to start learning how to “think in ArchiMate” as your second or third written language. Archi is a great free tool for learning the ArchiMate language. You can download the Archi .archimate file containing the model used for this article from here. You can download the latest version of the Archi 4.0 modeling tool from here (which includes full support for the ArchiMate 3.0 language).

ArchiMate 3.0 is used as the baseline enterprise architecture modeling language for this discussion; especially the new Grouping element.

The Proposals

There are 2 new proposals described in this article: one more generic and one more specific.

Proposal 1: A new (general) approach for visually presenting answers to the question “How do I model X in ArchiMate?” using a metamodel-level reference model modeling strategy
Proposal 2: A specific approach (reference model) for modeling a Company and its Locations, Markets, Employees, Investors, etc. and their Roles.

The second proposal is an example or use case for the former.

Proposal 1: Modeling of Best Practice Modeling Patterns

Proposal 1 is illustrated in Figure 1 and Figure 2. These figures illustrate a general approach for modeling and visually presenting answers to the question “How do I model X in ArchiMate?”.

Rather than provide simple, less-informative, textual answers such as “use Business Collaborations to model Companies” or in ArchiMate 3.0, “use Groupings to model Companies”, why not:

Leverage Specialization relationships to model, name, and visually illustrate, in these examples, alternative representations of a Company element
From a presentation perspective, place the new best practices modeling pattern on the left – side-by-side – with the portion of the applicable elements of the base-level ArchiMate metamodel on the right

as illustrated in Figure 1 and Figure 2.

NOTE: Proposal 1 is illustrated with 2 examples. The merits of the individual examples are discussed below in Proposal 2. The comparison of these 2 examples is not part of Proposal 1.

Figure 1. Metamodel-level Reference Model for a Company using Business Collaboration

Figure 2. Metamodel-level Reference Model for a Company using Grouping

Proposal 2: Specific approach (reference model) for modeling a Company

Proposal 2 asks the question: Of the 2 options presented above (or any additional alternative options), which option represents a best practice reference model for modeling a Company and its Locations, Markets, Employees, Investors, etc. and their Roles.

The only tangible difference between the modeling strategy in Figure 1 vs. Figure 2 is:

Figure 1 derives Business Organization from Business Collaboration
Figure 2 derives Business Organization from Grouping (a new element introduced in ArchiMate 3.0)

These choices, in turn, have a secondary effect in terms of the valid set of relationships that can be used to compose or aggregate the elements that comprise a Business Organization.

To aid your consideration, Figure 3 provides a more concrete example using the second option: using Groupings to represent Companies (my current preferred solution).

NOTE: The goal of these models is to model the active structure of a Business Organization which excludes concepts like Business Processes and Business Services.

Figure 3. Proposal 2 Example: Bridgewater Associates

What do you think?

Please add your comments, thoughts, and questions below.

Best regards,

Michael Herman (Toronto)
Parallelspace Corporation
mwherman@parallelspace.net

*ArchiMate is a registered trademark of The Open Group.

8 Comments

Filed under ArchiMate, Architecture Reference Models, Automated Enterprise Architecture Modeling, Crossing the EA Charm, Definitions, Enterprise Architecture, Enterprise Architecture Chasm, Graphitization, ModelMate Information Architecture for ArchiMate

Tagged as ArchiMate, Architecture Reference Models, Grouping, ModelMate, proposal, specialization

December 30, 2016 · 10:10 am

#Graphitization of Ray Dalio’s Principles: Iteration 2

This article is the third in a series on #Graphitization. Click here to explore the other articles in this series.

Iteration 2 is a small iteration that had a goal of improved key phrase-based exploration and visualization of The Principles of Ray Dalio. This iteration builds on the ModelMate model of The Principles described earlier in this series: #Graphitization of Ray Dalio’s Principles: Iteration 1 and represents a significant improvement in terms of understanding which principles are realized by specific combinations of key phases.

Iteration 2 uses the same query used in Iteration 1. This time, the Linkurious graph visualization app is used to display the subgraph of all Topics, Principles, Subprinciples, Commentary, Questions, etc. directly or indirectly related to the key phrases “radically” and “transparent”. This concept is represented by the following simple query:

MATCH path =
 (pub:Publication_Principles_RayDalio_ModelMate)-[*]->(principle)
 -[r:HAS_KEYPHRASE]->(phrase:KeyPhase_Principles_RayDalio_ModelMate)
 WHERE phrase.Phrase CONTAINS "radical"
 OR phrase.Phrase CONTAINS "transparen"
 RETURN path;

The Principles subgraph containing all elements that are directly or indirectly related to the key phrases “radically” and “transparent” is shown below (click to enlarge).

Figure 1. All Topics, Principles, Subprinciples, etc. with Traceability to the Key Phases “radically” and “transparent”

The underlying graph is implemented using the ModelMate framework and implemented using the Neo4j graph database.

Best regards,

Michael Herman (Toronto)
Parallelspace Corporation
mwherman@parallelspace.net

7 Comments

Filed under Automated Enterprise Architecture Modeling, continuous transformation, Data Science, Graphitization, How do we think, ModelMate, Progressive Enterprise Architecture Map (PEAM)

Tagged as cypher, graph database, graphirization, knowledge graph, Linkurious, Neo4j, Ray Dalio, subgraph, The Principles

December 16, 2016 · 1:35 pm

Crossing the EA Chasm: Reflections on the Current State of ArchiMate

HBR: Great CEOs See the Importance of Being Understood

It is very interesting to read the above HBR article and then reflect on the current state of the ArchiMate language for Enterprise Architecture. Here are a few quotes from the article (as well as a few homework questions).

Best wishes for the New Year (modeled as a Principal, Driver, Goal, or Constraint? :-))

Here are 5 quotes from the HBR article:

“Perfecting and polishing a message matters less than how it’s reflected and refined by the intended audiences.”

Does ArchiMate support reflection and refinement in the minds of stakeholders? What needs to be changed/improved? What are the useful qualities needed for a language to support reflection and refinement in the minds of stakeholders (reflection and refinement by the stakeholders themselves)?

“One of the greatest obstacles in promoting more proactive, pro-user initiatives, she quickly discovered, was that her people were prisoners of their existing vocabulary. They interpreted her calls for customer obsessiveness by intensifying existing efforts rather than discussing or describing new ways to add new value.”

Is this also a description of ArchiMate’s current state? Are we stuck in a deepening “hole of hieroglyphics”? [link] Are we prisoners of ArchiMate’s existing vocabulary?

“Microsoft’s Satya Nadella, for example, has been linguistically maneuvering from a proprietary Windows/Office software legacy to cloud computing, platform, and open systems contexts. Machine learning, for example, is now as integral to Microsoft’s new value vocabulary…”

Is Machine Learning part of the ArchiMate vocabulary? …maybe …early stage at best. Does ArchiMate resemble an open technology environment for fostering innovation in enterprise architecture?

“Entrepreneurial founders, of course, have both semantic and rhetorical advantages over their successors in this regard. A company’s creator disproportionately owns and influences its vocabulary.”

This quote has 2 edges represented by each of these 2 sentences. Food for thought.

“Understanding the importance of being understood is what makes great CEOs great communicators.”

This also applies to CIOs and enterprise architects. How does ArchiMate help CIOs and enterprise architects become great communicators? …or does it hinder them? How can this situation be improved?

For more thoughts on this topic, check out:

Best wishes for the New Year (modeled as a Principal),

Michael Herman
Parallelspace Corporation
mwherman@parallelspace.net

*ArchiMate is a registered trademark of The Open Group.

7 Comments

Filed under ArchiMate, Automated Enterprise Architecture Modeling, Crossing the EA Charm, Enterprise Architecture, ModelMate

Tagged as ArchiMate, CEO, chasm, cio, communications, Enterprise Architecture Chasm, refinement, reflection, reflections

November 17, 2016 · 12:11 am

Crossing the EA Chasm: ArchiMate “Keep Calm and Have IT Your Way”

What would the nirvana of “Have IT Your Way” EA actually look and feel like?

First, a bit of required pre-reading: check out Crossing the EA Chasm: Re-visioning the ArchiMate Specification.

My apologies if you haven’t already read the preceding article. It was part of an initial draft of this article until I realized the topic of ArchiMate customization needed to stand on its own. It became the main course; leaving this article to be the dessert and, hence, much more enjoyable.

This article consists of alternate visualizations of the same underlying ModelMate enterprise architecture model and, for the most part, the same view. The only variables are the modeling scheme and zoom factor used to render each view:

Colored dots
ArchiMate iconography
Microsoft Enterprise Viso Stencil
Amazon Web Services (AWS) 2D iconography
Amazon Web Services (AWS) 3D iconography

The first figure is an animation/slide show. It depicts a succession of views – each drawn with one of the above schemes.

This slideshow requires JavaScript.

Figure 1. Single Open EA Repository: “Have It Your Way” Views
(Dots, ArchiMate, Microsoft Enterprise Stencil, AWS 2D Icons, AWS 3D Icons)

Zoom factor is an interesting variable. In the first 2 frames of the above animation, the transition from the large scale view using the “dots” scheme to the smaller scale view using the ArchiMate scheme is one example of how different schemes can benefit from being used together in the same view. In this example, it’s the benefit of masking the detail in large scale views while allowing the detail to be unwrapped in small scale views. The benefit is more esthetically pleasing and understandable views for each range of zoom factors.

Figure 2. ArchiMate Icons: View Detail
(same underlying ModelMate model)

Figure 2 renders the view using the ArchiMate scheme, primarily. In addition, the colors of the dots denote the combination of schemes that are available in this ModelMate model. The top color of each dot denotes the ArchiMate element type and the bottom color denotes the element type based on a fine-grained Microsoft enterprise schema/taxonomy. For example, the highlighted component is a SQL Server Instance (denoted by the dark gray color in the top half of the dot). The yellow-green color (aided by the icon) identify the component as an ArchiMate infrastructure service. (Click on Figure 2 to enlarge it.)

Figure 3. Microsoft Enterprise Visio Icons: View Detail
(same underlying ModelMate model)

Figure 3 is a similar view to Figure 2 but the Microsoft Enterprise Visio Stencil is used as the primary scheme. The pink color of the selected component denotes that it is an IP Subnet; the dark purple, an ArchiMate Network element. (Click on Figure 3 to enlarge it.)

Figure 4. Amazon Web Services (AWS) 3D Icons: View Detail
(same underlying ModeMate model)

Figure 4 is virtually identical to Figure 3 except the AWS 3D set of icons is used as the primary scheme for rendering this view. (Click on Figure 4 to enlarge it.)

Each of these visualizations was rendering using the Linkurious graph visualizer running against a ModelMate model materialized in a Neo4j graph database.

Next Steps

More nirvana? Being able to see multiple schemes, side-by-side and interconnected at the same time rendered in a single view (e.g. ArchiMate for on-premise, AWS and/or Azure schemes used for the cloud, MS SharePoint stencil for the SharePoint information architecture, etc.). “More news at 11…”.

The Aperitif

Lastly and simply for your humor, I offer the following cartoon as the aperitif.

Figure 5. “Enterprise Architecture Made Easy”
Credit: Geek&Poke

Have IT Your Way.

Best regards,
Michael Herman (Toronto)
Parallelspace Corporation

mwherman@parallelspace.net

*ArchiMate is a registered trademark of The Open Group.

5 Comments

Filed under ArchiMate, Automated Application Architecture Analysis, Automated Enterprise Architecture Modeling, Crossing the EA Charm, Enterprise Architecture, ModelMate, Progressive Enterprise Architecture Map (PEAM)

Tagged as ArchiMate, chasm, Enterprise Architecture Chasm, Hamburger, Have It Your Way, Linkurious, ModelMate, Neo4j

November 4, 2016 · 9:02 pm

Crossing the EA Chasm: Automating Enterprise Architecture Modeling #2

[Updated November 6, 2016: Added Database/Web Services Farm Example #2]

In the previous article Crossing the EA Chasm: Automating Enterprise Architecture Modeling, I included a simple example of how a current state enterprise architecture model can be created and maintained automatically.

The same ModelMate enterprise architecture model has now been extended to include a total of 832,789 ArchiMate entities connected by 828,859 relationships (with several million property values) and was created automatically from scratch in about 15 minutes.

Database/Web Services Farm Example #1 (Single Subnet)

Below is a simple example of an automatically generated view depicting the database services and web services configured on the 38 servers connected to a particular IP subnet. There’s a total of 355 nodes in this accurate and up-to-date current state view. (Click the image to enlarge it)

Figure 1. Database/Web Services Farm Example #1 (Single Subnet)

Pretty cool. The green dots are database services (SQL Server instances to be exact – almost every possibly product edition can be found in this subnet: SQL Server Express, Developer, Enterprise, Datacenter, etc.) modeled as Infrastructure Services; the blue dots, servers (Windows physical and virtual servers) modeled as Infrastructure Nodes; and, the purple dots, web servers (IIS virtual directory applications to be exact) modeled as Infrastructure Functions.

The small orange dots represent the network adapter configurations of the network adapters configured into each server. The most central dot is the IP gateway (network router) for this subnet.

Database/Web Services Farm Example #2 (All Subnets/All Farms)

Figure 2. Database/Web Services Farm Example #2 (All Subnets/All Farms)

The red dots are IP subnets (32 in this ModelMate view) connecting 208 server Nodes that host either a SQL Server Instance (376 Infrastructure Service elements) and/or an IIS Virtual Directory Application (1597 Infrastructure Function elements). The small orange dots are network adapter configurations. (Click the image to enlarge it)

Microsoft Exchange Server Farm Example

Here’s one more example of an auto-generated view from the same ModelMate model: a Microsoft Exchange email, collaboration, and unified communications services farm. In this view, the blue dots are the Windows Services running on each of these 3 Windows Servers in this view (out of a total of 5 servers in the complete farm). The orange dot highlighted in gray near the top of the server on the right side, for example, is an IIS virtual directory application that is hosting an Outlook Web Access (OWA) web service. (Click the image to enlarge it)

Figure 3. Microsoft Exchange Server Farm Example

The larger red entity contains all of the descriptive information (metadata) for each server’s processor; the smaller red dot, the memory configuration for the server.

The Neo4j graph database from Neo Technologies was used as a key component of the ModelMate platform. A special ModelMate tool was created for automatically uploading any SQL Server database into a graph database (including all tables, columns, primary keys, primary key constraints, composite keys, foreign keys, foreign key relationships, implied entity relationships, NULL value processing, DateTime data type handling, etc.).

Have a great weekend,

Michael Herman (Toronto)

Parallelspace Corporation

mwherman@parallelspace.net

*ArchiMate is a registered trademark of The Open Group.

4 Comments

Filed under ArchiMate, Architecture Reference Models, Automated Enterprise Architecture Modeling, Crossing the EA Charm, Data Science, Enterprise Architecture, ModelMate

Tagged as ArchiMate, chasm, collaboration, database, datacenter, email, Enterprise Architecture Chasm, graph database, Microsoft Exchange, Microsoft SQL Server, ModelMate, Neo4j, unified communications

October 28, 2016 · 12:02 am

ModelMate Architecture Reference Model

[Updated October 28, 2016]

This article describes the architecture reference model for deploying a comprehensive, integrated enterprise architecture modeling and data science platform based on ModelMate.

The audience for this article is IT professionals including enterprise architects, solution architects, and security architects who want increased visibility into the deployment of their custom applications, entire data center environments, business process definitions, and LOB applications such as SAP, Oracle Financials, Salesforce, Microsoft SharePoint, and Microsoft Dynamics CRM.

A primary use case is organizations with a requirement to move one or more on-premise applications or capabilities to the cloud or need a better understanding of how their hybrid on-premise/cloud environments (e.g. Salesforce cloud applications and on-premise or third-party customer loyalty solutions).

ModelMate

Quoting from Crossing the EA Chasm: Open Repository Strategies for Enterprise Architecture, “ModelMate is a working implementation of a Microsoft SQL Server and Neo4j graph database-based repository for managing arbitrarily large collections of arbitrary entities, properties, relationships, views, etc.to enable analysis, visualization, and understanding using easily-available open source and COTS (commercial off the shelf) business intelligence (BI), data visualization, and machine learning (ML) platforms, tools and cloud services.”

The primary goal of ModelMate is to provide automated support for the Continuous Transformation Framework of the Progressive Enterprise Architecture Model (PEAM) depicted in Figure 1.

Figure 1. Progressive Enterprise Architecture Model

Continuous Transformation Framework

The Continuous Transformation Framework is a Deming Cycle based on the following 4 phases:

Listening & Learning
Knowledge > New Designs
Plan & Act
Transformative Change > New Outcomes

The Framework is depicted as a continuous cycle as shown in Figure 1 above. The Framework can also be flattened and presented as a (repeating) sequence of 4 processes (Figure 2).

Figure 2. Continuous Transformation Framework

Why all of this discussion about PEAM and the Continuous Transformation Framework? It is because to be able to understand and value the ModelMate Architecture Reference Model, it’s important to understand the class of problems it is trying to solve. Automated support for Continuous Transformation is the pain; ModelMate is the pain killer.

ModelMate Architecture Reference Model

There are 3 high-level layers in the ModelMate Architecture Reference Model:

Apps that use the ModelMate repository
Continuous Transformation Framework
ModelMate Open Hybrid Repository (MOHR)

These 3 layers (and 4 categories of apps) are illustrated in Figure 3. Each app category corresponds to one phase in the Continuous Transformation Framework.

Figure 3. ModelMate Architecture Reference Model: 3 Layers

The choice of apps that your organization selects for each category depends on the medium-term and long-term drivers and goals for your enterprise architecture program. The app groups map to specific phases of the Framework:

Listen & Learn phase
- Ingestion
Knowledge > New Designs phase
- Pure Modeling and Layout apps
- Modeling, Layout & Visualization apps
- Data Science apps
- Custom Mobile and Web apps
Plan & Act phase
- Program & Project Management apps
Transformative Change > New Outcomes phase
- Operations and Change Management apps

Figure 4 lists a sample or representative list of applications that can fulfill the needs of each app category (each phase of the Continuous Transformation Framework).

Figure 4. ModelMate Architecture Reference Model: Apps

Ingestion

Ingestion apps are responsible for scanning the enterprise’s operational environment: systems, assets, and processes. Information captured about each entity includes its structure, metadata, performance and usage data. Operational business data is usually not needed and not captured.

Sources of data include business process logs, configuration management databases, LOB application configurations (SAP, SharePoint, Salesforce, Microsoft Dynamics CRM, Oracle Financials, etc.), operations management systems (Azure OMS, Microsoft System Center, etc.), Microsoft MAP Toolkit, performance monitoring logs, usage and audit logs, etc.

These are inbound data sources used to automatically update and maintain the EA models stored in ModelMate. Ingestion apps are the primary data sources for the Listen & Learn phase of the Continuous Transformation Framework.

Pure Modeling and Layout Apps

There are several types of apps that comprise the Knowledge > New Designs phase of the Framework. Pure Modeling and Layout Apps are applications that support the manual modeling of entities, relationships, and metadata as well as the manual layout of stakeholder specific views.

The apps in the group do not support any built-in analysis and visualization capabilities beyond manually-created basic views. In addition, pure modeling and layout apps do not include an end-user scripting capability for performing automated, user-defined custom analysis or visualization.

Archi is an example of a pure modeling and layout app.

Modeling, Layout & Visualization Apps

These types of apps support manual modeling of entities, relationships and metadata and the manual layout of stakeholder specific views but also include basic, advanced, and/or custom analysis and visualization capabilities.

BiZZdesign Enterprise Studio and other advanced EA modelers are examples of apps that belong to the Modeling, Layout & Visual Apps group – supporting the needs of the Knowledge > New Designs phase of the Framework.

Data Science Apps

Data Science Apps include non-traditional “enterprise architecture” modeling and analysis apps. This group includes both open sources as well as COTS (commercial off the shelf) data science tools and platforms. Data Science apps provide advanced analysis, machine learning and visualization capabilities enabled through open access to enterprise architecture data via standard protocols and APIs (e.g.ArchiMate Exchange File Format, OData, SQL Server stored procedures, entity models, and advanced query and analysis languages such as R, Cypher, and T-SQL).

Examples of Data Science apps include: R Studio, Microsoft Power BI, Tableau, Domo, Linkurious, Microsoft Excel and the Neo4j graph browser.

Custom Mobile and Web Apps

This is the last group of apps that support the Knowledge > New Designs phase of the Framework and includes both no-code and code platforms for creating custom reporting, analysis, visualization apps.

No-code custom apps designed with Microsoft PowerApps (and Microsoft PowerFlow) are examples of the former; traditional C#/VB.Net, Java, and Node.js/JavaScript apps are examples of the latter.

Program & Project Management Apps

Program & Project Management Apps support the Plan & Act phase of the Framework.

Traditional portfolio, program, and project managements apps are examples of applications in this group. Collaboration tools such as Microsoft SharePoint, Confluence, and Jira can also belong in this group. Collaboration tools can also be considered as “horizontal” solutions that can be used across all phases of the Framework.

Operations and Change Management Apps

All of the effort to create and manage a functioning enterprise architecture solution only realizes direct business value when it leads to Transformative Changes being made in the enterprise’s strategies, systems, assets, and processes; and measurable, positive New Outcomes result from the changes.

Examples of apps in this category include change management applications that support IT Service Management (ITSM) disciplines such as ITIL. ServiceNow is an example of an ITSM app.

Please provide your feedback in the Comments section below or feel free to email me directly.

Best regards,
Michael Herman (Toronto)
Parallelspace Corporation
mwherman@parallelspace.net

*ArchiMate is a registered trademark of The Open Group.

All other trademarks, servicemarks, registered trademarks, and registered servicemarks are the property of their respective owners.

4 Comments

Filed under ArchiMate, Automated Application Architecture Analysis, Automated Enterprise Architecture Modeling, Business Value, continuous transformation, Crossing the EA Charm, Data Science, ModelMate, Power BI, Progressive Enterprise Architecture Map (PEAM), Salesforce, SharePoint

Tagged as ArchiMate, Architecture Reference Models, cloud, Data Science, Enterprise Architecture, ModelMate, Neo4j

October 22, 2016 · 1:06 am

Crossing the EA Chasm: Automating Enterprise Architecture Modeling #1

If you have been following my Crossing the EA Chasm blog series (and related articles), you’ll have noticed a number of common themes:

How to challenge the Enterprise Architecture Chasm (and The Strategy Chasm)
Use of Open Repository Strategies for unlocking and automating access to enterprise architecture data
Continuous Transformation through Progressive Enterprise Architecture Management
1. Listening and Learning
2. Knowledge and Understanding leading to New Designs
3. Planning and Acting
4. Transformative Change leading to New Outcomes
Enabled through software like the ModelMate project that makes it easy to integrate open EA data with open source and COTS (commercial off the shelf) software for modeling, analysis, machine learning and visualization.

Automating Enterprise Architecture Modeling

Automated enterprise architecture modeling (and automated application architecture analysis) are activities that belong to the Listening and Learning phase of the Continuous Transformation Framework.

Figure 1. Progressive Enterprise Architecture Model: Continuous Transformation Framework

Supporting the above themes, the Technology layer diagram below is automatically generated from a simple, single line query applied to an automatically created and dynamically maintained model of 500+ Windows and Linux servers (blue dots) with 550+ server network adapter configurations (yellow dots) connected to 25 network gateways (blue dots representing 25 network routers/switches). The data originates from a series of tables maintained by a configuration management database (CMDB) solution. There is no way to understand what the Technology environment looks like by simply looking at these tables. However, in the visualization below, it is easy to see that there are at least 14 different server farms, application clusters, and data centers.

Figure 2. Automatically Generated Technology Layer Model and View

In this ModelMate model, servers are represented by Nodes with 179 properties; network adapter configurations as Devices with 69 properties each; and, network gateways as Devices with 4 properties per device.

This is just the beginning as additional information about web application, database, DNS, and directory and domain management services is used to add additional detail to the current state Technology layer of this enterprise architecture. “More news at 11…” (click here).

This effort was made easier through the use of ModelMate and the Neo4j Community Edition free, open source graph database and the Cypher query language.

Best regards,

Michael Herman (Toronto)

Parallelspace Corporation

mwherman@parallelspace.net

4 Comments

Filed under ArchiMate, Architecture Reference Models, Automated Application Architecture Analysis, Automated Enterprise Architecture Modeling, Crossing the EA Charm, Data Science, Enterprise Architecture, ModelMate, Progressive Enterprise Architecture Map (PEAM), The Open Group

Tagged as CMDB, Configuration Management Database, graph database, ModelMate, Neo4j

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Category Archives: Automated Enterprise Architecture Modeling

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0. SerentityData Graph

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