The question I am trying to answer today is whether there is difference between data architecture and Information architecture - if yes what is it, and if no then why is there none. Information is something that has been there since a very very long time, communication is a medium by which the information actually flows. Doesn't necessarily mean that the information is preserved in it's original form, an example would be the ancient scriptures that were written by people centuries ago, or the hieroglyphs on the ancient buildings. That is information preserved, but we cannot establish the credibility or accuracy.
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With today's technologies we do have a way to preserve information in very rich and vivid formats e.g pictures, audio, video etc. electronically. And they will be preserved till we are not back to the stone ages. Data architecture deals with the representation of data as it is stored physically, it brings about the relations and links between different entities that represent the front system to which it feeds the data. Information architecture deals with more dynamic aspects of a system. With the flows, activities and information supply models. Its more of a system that would sit on top of a Data system and draw inferences from. A good example would be a BI tool, which gathers information, stores it and presents it in the ways desired/requested. Communication Architecture in software terms is the definition of interactions between different systems/components within an enterprise.
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To take a high-level perspective of this subject we could divide it in three basic parts:
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Data Architecture - Focus on data storage irrespective of collectively being meaningful data.
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Information Architecture - Consolidates data from different data architectures and provide a contextual or meaningful data that is targeted towards a certain objective
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Communication Architecture - Focus is more on mapping different terms/concepts of different business groups and stakeholders to provide them relevant information. Canonical models/architecture plays critical role in communication architecture
This is a strict interpretation of the basics: Data is just values, text or numeric, for example: "2000 euro". Information is data in context, for example: "2000 euro was paid by Mr. John Doe. on the 1st November to settle invoice 12345". I think it follows that there is a difference between Data Architecture and Information Architecture, but I also think this is less defined and less accepted. My view is that Data Architecture is confined to Databases, their design management, loading, security and general management etc. but would also encompass ownership, users, stakeholders etc. plus aggregated data i.e. OLAP, Data Marts, Data Warehouses etc. Information Architecture includes Data Architecture plus things like messaging, SOA, unstructured data e.g. content management, document and records management, Digital Asset Management, together with data capture and disposal plus dissemination and targeting of information together with all the governance standardas like CobiT or MIKE2. But the biggest fundamental diference is that Information Architecture will also include information held in non-electronic form.
For the Communication Architecture, part lies in Information Architecture, like I mentioned above, targeting information and its dissemination. But should also include the plumbing i.e. networking - it depends on the context of the word Communication. On the other hand, you can look at it much like the OSI model - communication architecture lies in the transport, network and the data link layer. Information is session, presentation and application layers. But, let us first differentiate Information and Communication. Information is a source ( may be of knowledge, happenings and findings ), of intelligible data or intelligence/meaning ( need not necessarily be computer oriented but has some structure ).
Even steller noise is an information for astronomers, but for general user it may be noise ( unwanted infromation or intelligible information ). Communication is a process, method to convey the information. right from sign language to speech or pictures, internet, 3G, etc. It has its method, protocol and language ( like English, French, Spanish, etc. ) and has an structure. Information may be structured or unstructured. Information articulation is a science where as information analysis or abstraction of it is a data analysis ( for example the sound of a dolphin is an information for where as analysis of it for characterisation is a data analysis, or the rise and fall of stocks is an information where as reason extraction is data analysis of same information ).
Speaking from a different perspective, the question at hand requires a tilted viewpoint and a reference point for better comprehension. Information is a processed data in any particular form that may become knowledge if validated and found capable of further reuse. Surely, all information that flows may not become knowledge and may (sometimes even may not) serve ad-hoc problem or a tentative mission of an enterprise. Our analytical abilities, duly assisted by emerging qualitative BI (Business Intelligence) tools, are improving drastically the means of information generation both in terms of quality as well as quantity. So, perceptibly and logically, raw data with predefined variable parameters for layout and maintenance is of much importance in comparison to the processed data (information) which has variable life spans in various contexts of business operations. Crux of the question is whether we need to readjust our thinking processes and methodologies to revamp system architecture framework so as to escape information overload - and not simply translating data into knowledge as per requirements without undergoing intermittent transition to Information. Indirect analogy - if one can read between lines - MLM, Direct marketing, etc. - for instance, one of good innovations in this direction (though for a specific purpose) is CAEX (Computer Aided Engineering Exchange). CAEX is a good innovative idea not only for providing impetus to dynamism for new product development followed by rapid market allocation for the businesses but also arguably an answer to some of information overload problems.
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