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Practical Ontology For Enterprise Data Management
 

Practical Ontology For Enterprise Data Management

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As a methodologist and software engineer, I’ve designed CASE tools that collect and impose organization on meta-data at all levels of detail. ...

As a methodologist and software engineer, I’ve designed CASE tools that collect and impose organization on meta-data at all levels of detail.
As a enterprise architect, I’ve worked in an environment that uses planning-level data.
In a planning context, you need a method for quickly characterizing the problem space at the enterprise level.
I’ve stumbled on to a way to do that.

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  • As a methodologist and software engineer, I’ve designed CASE tools that collect and impose organization on meta-data at all levels of detail.\nAs a enterprise architect, I’ve worked in an environment that uses planning-level data.In a planning context, you need a method for quickly characterizing the problem space at the enterprise level.I’ve stumbled on to a way to do that.\nBut first, for orientation, you can’t go wrong thinking about the journalist’s 5W’s.When we are collecting data about Enterprise’s data,we need to knowwhat . . ., who . . ., when . . ., where . . ., and why . . . \n\n
  • Here are my short definitions of the words practical, ontology, and enterprise.\n
  • Here is the essence of my working method.If you don’t remember anything else I say today,just remember “The message is the feature.”\nEverything else follows from that.\n
  • Why do I say “The message is the feature.” ???\nI work in a corporate ITS organization.\nIn that context, we rarely produce software products.\nWe mostly work on integrating products that we purchased.\nBut, what does that really mean?\nBusiness units communicate with each other by sending messages.If you analyze that message traffic, you discover almost everything you need to know.\n
  • At the most basic level, there are just three kinds of message.\nRequest - Response . . . Whether it is called a purchase order, work ticket, job ticket, reservation, or whatever; in essence it is a work order request that some product or service be done or delivered.\nQuestion - Answer . . . One business unit is requesting data from another business unit that is the custodian of that data.\nPublish - Subscribe . . . The business unit that is the authorized observer announces a business event. It “publishes” it. Other units that have an interest in that kind of event may “subscribe” to those announcements.\n\n
  • The five W’s may be refined according to the type of message.\nIn every case, you should write the message out a a well-formed English sentence. (Of course, if your organization works in some other language, you should use that language.)\nFor example:\nThe who should relate to the role or actor that sends and receives the message.\nThe where should relate to the computer applications or services that are acting as the electronic proxies for those actors.\nThe when and why should relate back to a workflow. The why is the workflow -- At “run time” the work flow will typically be triggered by a higher-level “master” work-order.The task will usually represent a delegation of some work from one organization to another.\n
  • For the “Question - Answer” message, the most important fact is the “who” -- Who is the “system of record” for the data involved?\n
  • For “Publish -- Subscribe” the you want to know who is responsible for publishing.\nAll kinds of business events need to be published.Don’t confused data events with business events, the data got changed for a reason.The business event is the reason, and that is what you want to capture.\n
  • The operations folks are more interested in the five H’s rather than five W’s.\nOh, I cheated. The “How to do it?” question breaks down into several other questions.\nAs you are analyzing messages, you will need to pick up answers to these questions as well.\n
  • Here is the simple technique. \nThis is “Object Oriented Analysis 101”.\nThere are three steps:\nOne: Write the message out as a complete sentence.Two: Underline the nouns.Three: Figure out that the noun is referencing using entity-relationship concepts.\n
  • In the noun side of the ontology, you focus on the nouns that refer to entities.\n
  • You can analyze the message content to discover the capabilities that are implicit in the messages.\nObviously, if a business unit is requesting a product or service from another unit, the other unit is expected to have the capability of producing that product or service.\n
  • Going somewhat beyond the message, you can identify the function required.\nThese might go into a business architecture or technical architecture.\n
  • The nice thing about standards is that there are so many to choose from.\nThe not so nice thing is that information is often lost or even garbled in the process of translating from one notation to another.\nI prefer to work in structured English, it has the advantage of flexibility and being both human-readable and machine-readable.And, I believe, there is less information loss.\n
  • I am going to demonstrate the ideas I’ve been talking about \nin a structured English notation.\nThe particular notation that you use does not really matter.\nThe main point is that you have a way to capture different kinds of business process knowledge.\n\nYou also don’t need an expensive tool.\n5x8 cards will work almost as well as most of the meta-data systems that you might buy.\n\n
  • This is a structured English notation for defining plans.\nYou can use this notation to identify work that may proceed in parallel workflows.\nIf you diagram this, you get a kind of precedence chart or state-transition diagram.\n
  • Here is an example.\nThe nouns are underlined.\nA syntax analyzer would warn that some of the nouns have no antecedent in the post-condition.\n\nYou can take the algebra out of a programming notation, but you cannot take the programming out.\n
  • This is a structured English notation for defining procedures -- a sequence of tasks that are assigned to a single role.\n
  • Here is an example of that notation.\nNote that the primary actor can delegate a task to another role.\n\n
  • Structured English become executable once the nouns are known.\nIn natural language, nouns represent variables that are assigned values at run-time.\nThis notation provides the means of identifying the nouns and their relationships.\n
  • Here is an example.\nSome nouns may belong to a base vocabulary.\nThe base vocabulary contains terms that are common to all business situations.\nThe base could also be extended to include terms that are common to a given industry.\n\n
  • In the business world, a number is not a mathematical abstraction.\nIt always represents a measurement with a unit of measure and some limited precision.\nThis illustrates one of the differences between computer programming and business programming.\nIn computer programming, someone would be concerned with how this concept would be represented in the hardware.\nIn business programming, we simply require that the run time will do the right thing.\n
  • This is a structured English notation for defining dialogs, protocols, and use case scenarios.\n\n
  • Here is an example.\nThis basic idea is that it reads like a stage play.\n“He said” . . . “She said” plus some direction about what is happening in the background.\n\nI derived this notation from a chat-bot notation called “ALICE”.\nIn essence, this part of the system would execute like a chat-bot.\nBut, with some refinement, it can be used as any kind of event-driven production system.\n\nIn the context of an ontology, this notation provides a way to capture this kind of message exchange.\n\n
  • \n

Practical Ontology For Enterprise Data Management Practical Ontology For Enterprise Data Management Presentation Transcript

  • Practical Ontology forEnterprise Data Management5 Ws:An enterprise needs to knowwhat data they own,who uses it,when it is updated,where it is stored and used,why it is useful.
  • Practical . . . OntologyPractical Ontology Delivers value  What exists Easy to use  RelationshipsScope:Enterprise – produces a set of products and services for a specific market / constituency
  • Simple Technique The message is the feature.Everything follows from that.
  • The message is the feature. Generally, enterprise ITS organizations spend most of their resources integrating purchased components, not building them. Business processes communicate by sending messages. If you analyze those messages, you discover almost everything about the data.
  • Three Kinds of Message Request – Response : Work Order Please deliver cake to customer. Question – Answer : Query What is order’s delivery-address? Publish – Subscribe : Notice Oven has reached preheat-temperature.
  • Request – Response : What = What action is requested? (Write English sentence.) Who = Actor requesting, actor responding. Where = Components (are proxies for actors) When = Task Delegation / Hand-off Why = Business Process Workflow
  • Question – Answer : What:  What is the question? (Write it in English)  What is the expected form of the answer? Who = Client is asking System of Record Where = Components (proxies for actors) When and Why:  Details needed for operation (task in workflow)  Details aggregated into metrics
  • Publish – Subscribe : What = Business Event Fact (Write it in English) Who = Who publishes? Who needs to know? Where = Components that proxy for who. When = Other actor needs to know:  Asset Changes  Account Changes  Outages  Work started / completed / suspended Why = Audit / Tracking (Metric) / Trigger
  • Five Message Hs: How . . . How often = frequency of message How fast = response time needed How long = record retention period How much = Mega / Giga / Tera / Peta – Bytes How do:  How protected = encryption / access control  How transported = infrastructure used  How formatted = XSD / . . .
  • Message ==> Nouns ==>1.Write the message out as a full sentence.2.Underline the nouns.3.Analyze the nouns: Each noun refers to . . .  Entity: Identifiable / Countable  Entity Attribute: Describes some entity.  Attribute Categories: Example: Color Green  Entity-Owned Collection: Set, Bag, or List of . . . Entity is defined by its supertypes and attributes
  • Entity Facts What is the operational meaning of a data record? Who  . . . is entity custodian? (business process)  . . . has access to which fields? Where is entity record? (system of record) When is the entity data changed? (life-cycle: business events) Why is it useful? (ROI / ROA)  Clients that query  Business metrics derived  Compliance with rules / regulations / best practice
  • Message ==> Capability Request – Response ==> Ability to provide a service / product Question – Answer ==> Ability to interpret the query and answer it Publish – Subscribe ==> Publisher is qualified observer . . . (sufficient for an internal notice) ==> Publisher is authority for that event data . . . (necessary for wider audience)
  • Capability ==> Function / Feature What capability?  User Story / Use Case  Given . . . When . . . Then . . . Who = Which business process provides? Where = Which application / component provides? When = Business Process Task (business event) that requires capability Why = Business benefit (faster / better / cheaper)
  •  Structured English Notations (natural language structured for processing) SQL – Data Description Language Interface Description Languages  CORBA IDL  Java Interface declaration / equivalent in language X  Web Service Description Language (WSDL) Business Process / Workflow Description  Business Process Modeling Notation (BPMN)  Business Process Execution Language (BPEL) Miscellaneous XML  XML Schema Document (XSD)  Web Ontology Language (OWL)  Resource Description Framework (RDF)  ALICE (Chat-Bot NLP: translate queries to standard form)
  • Examples in Hum• Hum is not a product. It is an experiment.• Open source - written in Smalltalk.• Examples to show basic concepts.• Point is that you can do this kind of thing using structured natural language as the notation.• 5x8 cards will work almost as well
  • Each of these statementsPlan Tree indicates a message. Goal: <imperative statement> Post-Condition: <assertion statement> Preconditions: • <assertion statement> • <assertion statement> Action: • <role> : <imperative statement>
  • Plan Tree - ExampleGoal: Bake a cake according to recipe.Post-Condition: Cake is baked per recipe.Preconditions:• Oven is at preheat-temperature per recipe.• Cake batter is in a prepared cake pan.Action:• Cook : Bake in oven for bake-time given in recipe.
  • Role-Action : ProcedureRole: <Role-Name>.Action: <imperative statement>• <imperative Statement>• <role-name> : <imperative statement>• If <condition>: • ...• ...
  • Role-Action : ExampleRole: Cook.Action: Bake in oven for bake-time given in recipe.• Open the oven door.• Place the pan in the oven.• Close the oven door.• Oven: Bake for the bake-time given in recipe.Message delegates step to automated oven (role).
  • Noun RelationsDictionary: <title indicates context>• A <noun> is a <noun>.• <noun> attributes include <noun>, . . .• <noun> categories include <noun>, . . .• <noun> contains a <collection> of <plural noun>.• ...
  • Noun Relations - ExampleDictionary: Baker’s vocabulary.• A mixing-bowl is a container.• Recipe attributes include temperature, duration, . . .• Cake-type categories include layer-cake, bunt-cake.• Recipe contains a list of steps.• A temperature is a measurement. Yellow nouns above could be in a base vocabulary.
  • Base VocabularyDictionary: Base vocabulary. • A weight is a measure. • Measure attributes include quantity, precision, unit-of-measure, method. • Unit-of-measure categories include Wh,VAh,V. • Wh is shorthand for Watt-hours. • ...(Could be open source like OpenCyc.)
  • Dialogs and Use CasesDialog: <arbitrary title giving overview>.Context: <name-of-context for disambiguation>.(Vignette -- starts with a specific user statement)• U: <user statement>• S: <system response> • <role> : <action statement>
  • Dialog - ExampleDialog: User authentication.Context: New session.U: [User arrives with cookie.]S: Hello [user name]. What would you like to do?Context: Expect user request.U: I want to pay my bill.S: Your balance is [user account balance]. Would you like to pay by credit card or PayPal?
  • Summary• Enterprise ITS needs to know what data it owns and who uses it, when, where, and why.• Enterprise actors communicate with messages.• By analyzing message nouns and context, we discover ontology content.• Structured English provides human readable information that is also machine readable once the nouns are identified.