Enterprise Architecture in the Rail Domain

Home , Derek Hitchins, Information architecture

EA, IA, O

"Old MacDonald Had a Farm" is a children's song about a farmer named MacDonald (or McDonald) and the various animals he keeps on his farm. Each verse of the song changes the name of the animal and its respective noise. In many versions, the song is cumulative, with the noises from all the earlier verses added to each subsequent verse. It has a Roud Folk Song Index number of 745.

Renowned computer scientist Donald Knuth jokingly shows the song to have a complexity of in "The Complexity of Songs," attributing its source to "a Scottish farmer O. McDonald."

[2] [3] Systems Engineering (SE)

Systems of Systems (SoS)

Enterprise Architecture (EA)

Information Architecture (IA)

Ontology (O)

[4] Systems Engineering

The Art and Science of creating effective systems, using whole system, whole life principles" OR "The Art and Science of creating optimal solution systems to complex issues and problems"[8] — Derek Hitchins, Prof. of Systems Engineering, former president of INCOSE (UK), 2007.

[5] A logical sequence of activities and decisions that transforms an operational need into a description of system performance parameters and a preferred system configuration. (MIL-STD-499A, Engineering Management, 1 May 1974. Now cancelled.)

An interdisciplinary approach that encompasses the entire technical effort, and evolves into and verifies an integrated and life cycle balanced set of system people, products, and process solutions that satisfy customer needs. (EIA Standard IS-632, Systems Engineering, December 1994.)

An interdisciplinary, collaborative approach that derives, evolves, and verifies a life-cycle balanced system solution which satisfies customer expectations and meets public acceptability. (IEEE P1220, Standard for Application and Management of the Systems Engineering Process, [Final Draft], 26 September 1994.)

[6] SE guide to SoS, DoD, 2008 [7] • Virtual. Virtual SoS lack a central management authority and a centrally agreed upon purpose for the system-of-systems. Large-scale behavior emerges—and may be desirable—but this type of SoS must rely upon relatively invisible mechanisms to maintain it.

• Collaborative. In collaborative SoS the component systems interact

more or less voluntarily to fulfill agreed upon central purposes.

Control Local • Acknowledged. Acknowledged SoS have recognized objectives, a designated manager, and resources for the SoS; however, the constituent systems retain their independent ownership, objectives, funding, and development and sustainment approaches. Changes in the

systems are based on collaboration between the SoS and the system. Control • Directed. Directed SoS are those in which the integrated system-of- Central systems is built and managed to fulfill specific purposes. It is centrally managed during long-term operation to continue to fulfill those purposes as well as any new ones the system owners might wish to address. The component systems maintain an ability to operate independently, but their normal operational mode is subordinated to the central managed purpose. SE guide to SoS, DoD, 2008 [8] Dr J Kaplan, 2006 [9] Common SoS Characteristics: System of Systems: •operational independence of individual systems •managerial independence of the systems •geographical distribution •emergent behavior •evolutionary development

Many SoS definitions & characterizations look like a result of whiteboard brainstorming of lots of ideas of what systems of systems often look like. D.Cocks, INCOSE, 2006 [10] Dr W Reckmeyer, 2005 [11] Five Attributes of Systems of Systems

• Operational Independence of the Elements

• Managerial Independence of the Elements

• Evolutionary Development

• Emergent Behaviour

• Geographic Distribution

S.E.Sheard, Incose, 2008 [12] Stakeholders in the UK’s Liberalised Railway

• Association of Train Operating Companies • Department for Transport • HM Railway Inspectorate • Network Rail • Office of Rail Regulation • Passenger Transport Executives • Rail Passenger Councils • Rolling Stock Leasing Companies • Train Operating Companies

C.Roberts UoB [13] Whats in SoS World CxS Differences

SoS Systems Non-Complex CxS Systems

S.E.Sheard, Incose, 2008 [14] Dr B Write, 2005 [15] [16] C Siel, CE(Navy), 2005 Enterprise Architecture I see the ―Railway Service‖ expressed as an Enterprise Model, defined by a discrete number of architectural layers …

Performance Architecture

Business Architecture

Solutions Architecture

Information Architecture

Technical Architecture

Support Architecture

… here the content in each layer is related (e.g. information will have business processes to collect it and use it)

S Thurlow [17] The Value of an Architecture The lost opportunities of siloed evolution We see the ―Railway Service‖ expressed as an Enterprise Model, defined by a discrete number of architectural layers …

Performance Architecture Performance issues Business constraints Business Architecture Unique Training Solutions Architecture Duplicate/inconsistent Information Point2Point Interfaces Information Architecture Little reuse Technical Architecture Heterogeneous Single Supply Support Architecture Unique Support Application An EA approach defines a consistent ArchitectureApplication in each layer that applies A B across the whole enterpriseStack Stack But the Legacy estate often evolves from piecemeal procurement for point solutions as a vertical stack fragmenting the ability to combine opportunities S Thurlow [18] The Federal Enterprise Architecture (FEA)

The FEA is build with a collection of reference models, that develop a common taxonomy and ontology for describing IT resources. These include the, see image: Performance Reference Model, the Business Reference Model, the Service Component Reference Model, the Data Reference Model and the Technical Reference Model. It is designed to ease sharing of information and resources across federal agencies, reduce costs, and improve citizen services. It is an initiative of the US Office of Management and Budget that aims to comply with the Clinger-Cohen Act. Wikipedia [19] Enterprise architecture has become a key component of the information technology governance process in many organizations. These companies have implemented a formal enterprise architecture process as part of their IT management strategy. While this may imply that enterprise architecture is closely tied to IT, it should be viewed in the broader context of business optimization in that it addresses business architecture, performance management and process architecture as well as more technical subjects. Depending on the organization, enterprise architecture teams may also be responsible for some aspects of performance engineering, IT portfolio management and metadata management. The following image from the 2006 FEA Practice Guidance of US OMB sheds light on the relationship between enterprise architecture and segment(BPR) or Solution architectures. (From this figure and a bit of thinking one can see that software architecture is truly a solution architecture discipline, for example.)

Activities such as software architecture, network architecture, database architecture may be seen as partial contributions to a solution architecture. Wikipedia [20] Enterprise Architecture

A formal definition of the structure of an enterprise comes from the MIT Centre for Information Systems Research:

Enterprise Architecture is the organizing logic for business processes and IT infrastructure reflecting the integration and standardization requirements of the firm’s operating model.

It is often said that the architecture of an enterprise exists, whether it is described explicitly or not. This makes sense if you regard the architecture as existing in the system itself, rather than in a description of it. Certainly, the business practice of enterprise architecture has emerged to make the system structures explicit in abstract architecture descriptions. Practitioners are called "enterprise architects."

Wikipedia [21] Many enterprise architecture frameworks break down the practice of developing artifacts into four practice areas. This allows the enterprise to be described from four important viewpoints. By taking this approach, enterprise architects can assure their business stakeholders that they have provided sufficient information for effective decision making. These practice areas are Business: Strategy maps, goals, corporate policies, Operating Model Functional decompositions (e.g. IDEF0, SADT), capabilities and organizational models Business processes Organization cycles, periods and timing Suppliers of hardware, software, and services Information: Metadata - data that describes your enterprise data elements Data models: conceptual, logical, and physical Applications: Application software inventories and diagrams Interfaces between applications - that is: events, messages and data flows Intranet, Extranet, Internet, eCommerce, EDI links within and outside of the organization Technology: Hardware, platforms, and hosting: servers, and where they are kept Local and wide area networks, Internet connectivity diagrams, Operating System Infrastructure software: Application servers, DBMS Programming Languages, etc.. Wikipedia [22] An Extended Enterprise is a loosely coupled, self-organizing network of firms that combine their economic output to provide products and services offerings to the market. Firms in the extended enterprise may operate independently, for example, through market mechanisms, or cooperatively through agreements and contracts.

Alternatively referred to as a "supply chain" or a "value chain", the extended enterprise describes the community of participants involved with provisioning a set of service offerings.

The extended enterprise associated with "McDonald's", [the firm not the farm] for example, includes not only McDonald's Corporation, but also franchisees and joint venture partners of McDonald's Corporation, the 3PL's that provide food and materials to McDonald's restaurants, the advertising agencies that produce and distribute McDonald's advertising, the suppliers of McDonald's food ingredients, kitchen equipment, building services, utilities, and other goods and services, the designers of Happy Meal toys, and others.

Extended Enterprise is a more descriptive term than supply chain, in that it permits the notion of different types and degrees and permanence of connectivity. Connections may be by contract, as in partnerships or alliances or trade agreements, or by open market exchange or participation in public tariffs.[1]

How the Extended Enterprise is organized and structured and its policies and mechanisms for the exchange of information, goods, services and money is described by the Enterprise Architecture.[2] Wikipedia [23] Data Architecture in enterprise architecture is the design of data for use in defining the target state and the subsequent planning needed to hit the target state. It is usually one of several architecture domains that form the pillars of an enterprise architecture or solution architecture.

Wikipedia [24] Information architecture is defined by the R.I.P.O.S.E.[1] technique, 1989 [2] as: The conceptual structure and logical organization of the intelligence of a person or group of people (organizations).

Information architecture is defined by the Information Architecture Institute as: The structural design of shared information environments. The art and science of organizing and labeling web sites, intranets, online communities, and software to support findability and usability.[3][4] An emerging community of practice focused on bringing principles of design and architecture to the digital landscape.

The term information architecture describes a specialized skill set which relates to the interpretation of information and expression of distinctions between signs and systems of signs. It has some degree of origin in the library sciences. Many schools with library and information science departments teach information architecture [5]

Information architecture, in the context of information system design, refers to the analysis and design of the data stored by information systems, concentrating on entities, their attributes, and their interrelationships. It refers to the modeling of data for an individual database and to the corporate data models an enterprise uses to coordinate the definition of data in several (perhaps scores or hundreds) of distinct databases. The "canonical data model" is applied to integration technologies as a definition for specific data passed between the systems of an enterprise. At a higher level of abstraction it may also refer to the definition of data stores.

Wikipedia [25] Information Architecture

DATA REFERENCE MODEL

P. Allega Gartner ITXPO, Cannes, 2006

Gartner [26] Information Architecture in Context

EIM supports SOA

D. Logan, A. Lapkin, Gartner ITXPO, Cannes, 2006

Gartner [27] Information Architecture – Levels of Abstraction More Abstract Zachman Framework

Level View Data (What) Stakeholder

1 Scope/Contextual List of things important to the business (subject areas) Planner

2 Business Model/Conceptual Semantic model or Conceptual/Enterprise Data Model Owner

3 System Model/Logical Enterprise/Logical Data Model Designer

4 Technology Model/Physical Physical Data Model Builder

5 Detailed Representations/ out-of-context Data Definition (bits & bytes) Subcontractor

More Concrete

Wikipedia [28] Heterogeneity Abstraction Level Semantic Conceptual Conceptual Level Model Model

Is_a design of Is_a design of Is_a design of

Logical Logical Logical Logical Level Model Model Model 1 2 3

Implements Implements Implements Implements Implements Implements

Physical Oracle Oracle Level Oracle Oracle Not Interoperable SQL DB4 Interchangable Syntactical Interoperability

[29] Semantic Interoperability Information Architecture – Capturing Semantic Content

L.Oberst, 2006 [30] Barry Smith provides the following definition:

Ontology is the science of what is, of the kinds and structures of objects, properties, events, processes and relations in every area of reality. For an information system, an ontology is a representation of some pre-existing domain of reality which:

• reflects the properties of the objects within its domain in such a way that there obtains a systematic correlation between reality and the representation itself • is intelligible to a domain expert • is formalized in a way that allows it to support automatic information processing

An ontology in this sense is a thing made by a scientist or other domain expert. This thing is a formal theory, which accurately recapitulates the domain in light of the kinds of entities contained within it; that is, it is not ad-hoc, but in conformance with the world. Thus, an ontology is a true-to-the-world representation of its domain (SIGINT, calcium-regulated pathways, aircraft parts, etc.). This stands in contrast to the more popular usages by many in the fields of information and computer science, which see an ontology as merely an ad-hoc model built for some specific purpose.

Buffalo Ontology Site.mht Barry Smith [31] What is the W3C’s Web Ontology Language (OWL)?

Computer-understandable ontologies are represented in logical languages, such as the W3C OWL (Web Ontology Language).

However, logical languages are only a means to express content; they are themselves devoid of informational content. This situation is much like how the natural language English relates to information expressed in English. It is the information being imparted in the words that drives how the individual words are selected and sequenced into sentences. It's not the language (or logic) that makes the difference, but how you use it. Ontology is one way to use language and logic more effectively.

The W3C’s Web Ontology Language (OWL) is but a logic, you are on your own when it comes to saying something with it and of ensuring the accuracy of your assertions.

Buffalo Ontology Site.mht Barry Smith [32] An Ontology of Ontology’s

L.Oberst, 2006 [33] A Taxonomy

Wikipedia [34] Folksonomy (also known as collaborative tagging, social classification, social indexing, and social tagging) is the practice and method of collaboratively creating and managing tags to annotate and categorize content. Folksonomy describes the bottom-up classification systems that emerge from social tagging.[1] In contrast to traditional subject indexing, metadata is generated not only by experts but also by creators and consumers of the content. Usually, freely chosen keywords are used instead of a controlled vocabulary.[2] Folksonomy (a portmanteau of folk + taxonomy) is a user-generated taxonomy.

Wikipedia [35] Heterogeneity Although Physical Implementations are not interchangeable If they have a common Logical Model they can interoperate syntactically

Logical Logical Level Model 2

Implements Implements Implements

Physical Oracle Level

SQL DB4

Syntactical Interoperability

S.Thurlow [36] TAF - TAP

RAILDATA Centralbahnstr. 6, CH – 4051 Basel www.raildata.coop [email protected] [37] Patrick Mantell (UIC) eBusiness Conference 2008 [38] Figures and Sequence Diagrams 10 / 22 Orig. TAF, TSI, Annex a5 Version 1.0 22.06.2004 [39] RDO

Gerhard Langer, Siemens AG, IneGRail, Brussels, March 2009 [40] Gerhard Langer, Siemens AG, IneGRail, Brussels, March 2009 [41] Processing Layers in InteGRail

Gerhard Langer, Siemens AG, IneGRail, Brussels, March 2009 [42] EA – IA - O

Thank you and a safe journey home

[email protected] U-Tube [43]