The Whiteboard

They can be the same software. That isn’t the essential difference. There are many exceptions and edge cases but the central difference in moving from on premise to SaaS is that you are moving from a large capital budget item that takes a long time to approve to the steady drip of transaction or usage fees from here on out, which can be funded from the operating budget.

It mostly depends on whether you are the cloudor or the cloudee. If you are consuming cloud services theoretically there isn’t much difference, but practically there is. You will likely be paying more for a private cloud (not so much because it is inherently more expensive, but because there isn’t any competition) and consuming the private cloud will generally be more secure. If you are the cloudor (the provider of the cloud service) it is working a bit against you . You are forced to have excess capacity that you must pay for in order to provide for the potential surge.

A good ontology simplifies your information management systems because it creates an enterprise-wide definition of what things are called and their interrelationships. In our experience, even the complex requirements of multi-billion, global companies can be organized into ontologies of about 1000 concepts. Because ontologies reuse properties they can represent the real world complexities of a business using many fewer properties than logical models would need.

The world of traditional information technology is black or white. If something isn’t the same, then it is different. Every new distinction requires the creation of a new table. This creates a problem because once a new table is created the concept is considered new and unique from every other concept, causing redundancy and confusion. In the semantic world, shades of grey are tolerated. Once you formally define a concept, the semantic model creates a ‘web of similarity’ enabling the inference engine to associate the new concept to other classes that are similar. Queries are able to search not only for explicit information defined in the black and white world, but also for the ‘grey’ information found in the inferred subclasses. This enables users to ask much simpler questions and get much more complete information in return.

Inference is one of the ways that semantic technology simplifies information systems. Many of the manual assertions that must be made in the traditional systems can happen automatically in a semantic model. The more things you can infer, the fewer you need to assert, which greatly simplifies the system. Another way semantic technology reduces complexity is that it reuses predefined concepts through composition. This might sound a lot like the inheritance concept that is widely used in object oriented programming, but it is not. Let’s say that we want to define a trip to the doctor as an event that happens in a clinic. We would call that concept a ‘patient visit.’ Like object-oriented inheritance, the patient visit will inherit some of the attributes associated with the event, such as the date. Unlike object-oriented inheritance, the clinic concept contributes to the definition of what a patient visit is, but the patient visit doesn’t inherit any of the attributes of a clinic. A visit isn’t a type of clinic, yet the clinic is part of the definition of ‘patient visit.’ Semantic concepts are like words that can be assembled in an infinite number of ways. Objects in object-oriented programming are more like phrases; they can definitely be reused but with many more limitations. Reusing classes and properties significantly reduces the number of attributes required to model a business process, so we have much more flexibility in how concepts can be reused.

The cynical response is to invoke the “Gartner Hype Cycle” and say it’s been overhyped. But that just begs the question: why do things get overhyped? In general the reason is that someone comes up with a new approach to solving a vexing problem. At first it didn’t even have a name it just solved a specific problem. Eventually someone generalizes it and gives it a name. The very early adopters buy into the problem and how this approach solves the problem. However success creates a problem. The problem is that the early successes get associated with the category (SOA in this case) and new practitioners show up eager to do “SOA” or whatever it is that is trendy. There isn’t a problem with the technology per se, but the new wave of practitioners are more interested in being in the category than actually solving the problem that the approach was designed for. And so the solution becomes decoupled from the problem. No wonder the second wave is disappointed. No wonder there is a hype cycle. And no wonder that as Gartner themselves put it , almost everyone is doing SOA and only about 5% are achieving the benefits. The benefits require discipline not buzzwords and technology

Since the semantic model is free of structure, it is easier to map concepts to different structural representations enabling reuse of classes and properties. Reuse is a profound way to reduce complexity. In a traditional system, attributes are not reused. Every time you create a new table and put new attributes on it you’ve created additional attributes. Even if you gave them the same name, there is no guarantee that on this new table they might not mean something different. The technology treats them as if they are different. Property reuse enables a drastic reduction in the number of properties needed to represent the complexity of a large domain. In semantics, properties are first-class objects, which means that they exist independent of any class or table. They can be reused and still retain their original meaning, so you need fewer of them. Additionally, because properties are first-class objects we can define relationships between properties. For example, if we declare that the property “hasParent” is a sub-property of the property “has Ancestor” then anyplace we assert that someone has a particular Parent, a semantic reasoner infers that that particular person is also an ancestor of the first person. In semantic modeling the definition of the classes and properties is separate from the process of building applications or database structures. This separation frees up the modeler to focus on the meaning and inclusion criteria for each class and intentionally avoid having to make decisions about how to store, structure or organize the information within the system.

An Enterprise Service Bus (ESB) is not a product but a style of architectural development. It is essentially SOA done right. The essence of an ESB is that all apps and all services talk only to the bus and not directly to each other. To the extent that they talk to each other they are coupled and violate the advantage ESB is attempting to convey.

Semantic technology uses ontologies to describe the business in a way that both humans and machines can understand. Since the semantic schema is independent from actual computer systems, e.g., legacy or future applications and databases, it allows us to find the commonalities across business processes, which serves to greatly simplify the enterprise architecture. semantic arts_schemaGenerally, people believe that the real world is complex and messy and that our information systems bring order out of chaos. However, the opposite is true. The real world tends to be much simpler than how we represent it in our database and applications schemas. For example, take a stapler. Our purchasing system refers to it as an item with a price; our manufacturing system breaks it down into an itemized list of plastic and metal and our administrative system keeps track of how many of them are on the shelf above the printer. However, in the real world it is just a thing that shoots a bit of metal through sheets of paper to fasten them together. Since semantic technology defines things separately from the applications or databases, you only have to do it once. In traditional IT systems, each thing is redefined within the context of what the information system is tracking, thereby creating multiple references about a single thing.