What is the difference between Information Architecture and Data Architecture?
Christine Thomson, Architecture Lead, Instructor, Mentor &
No doubt, for many of you, this question has come up. Perhaps your
organization has Information Architecture but no Data Architecture. Or
maybe, you are in the reverse. If this is the case, it can be easy to
think that they are the same, just different names. I had the experience
once of observing an innocent data architect expressing this
understanding to an Information architect. I will never forget the
rather harsh “correction” the data architect received.
It would seem, as new architecture disciplines emerge, which they have,
and continue to do, one needs to be aware that there will be a period of
confusion and negotiation to establish them. The case of Information
Architecture versus Data Architecture is such a situation.
Let us look at how each is defined. Then, we can decide if both are
Information, according to DAMA, is:
“data in context. Without context, data is meaningless; we create
meaningful information by interpreting the context around data… The
resulting information then guides our decisions.”
Another definition provided by the State Department of Public Works in
Queensland, Australia, asserts:
“Information is any collection of data that is processed, analyzed,
interpreted, organized, classified or communicated in order to serve a
useful purpose, present facts or represent knowledge in any medium or
They go on to say that:
“Information architecture is the means of providing a structured
description of an enterprise’s information, the relationship of this
information to business requirements and processes, applications and
technology, and the processes and rules which govern it.”
From this, we can see that the key factor when looking at Information
Architecture is that it deals with the relationships of knowledge,
information, and, yes, data, from any source that is relevant and useful
to the business.
In information architecture, ontologies are created and utilized
extensively. This is done as a means to determine how information
relates, so that technologies can be identified or created to support
working with the information in a powerful and meaningful way. Examples
of technologies supporting information architecture are search engines
and semantic web, e.g.
Resource Description Framework (RDF).
Looking back to DAMA, we get the following as the definition of data:
“[Data] is the representation of facts as text, numbers, graphics,
images, sound or video.”
We can then understand that data architecture is:
“composed of models, policies, rules or standards that govern which
data is collected, and how it is stored, arranged, integrated, and put
to use in data systems and in organizations.” (Business Dictionary)
The focus for data architecture is on gathering and storing the data.
Knowing the source and its use, the data architect is tasked with
choosing the best technologies to move and store the data to ensure its
availability and integrity for business use.
Information and Data in an EA practice:
Having provided these descriptions, we can see that the two do have a
connection, but are indeed distinct. The question is, do we need to
have these as two separate architecture disciplines or are they merely
a specialization of one or the other? While academically, the answer
is that they are in fact distinct, in an EA practice it may actually
work better to have one as an area of specialization within the other.
Organizations are challenged to determine if separating the the two
into their own domain discipline will enhance the architecture
practice. By seeing that they are different, requiring different
skills and resources, the EA program can ensure that each discipline
is fully supported.
However, there is overlap between the two. Treating them as unique
domains does come at a cost. By keeping them together, resources can
be pooled which could be more advantageous. But this raises the
question of, which way should it be done? Since information
architecture has a broader scope in terms of its view of sources and
data architecture requires some basic context for the data it
supports, one could easily argue that data architecture should be
under information architecture. Nevertheless, it could also be argued
that data architecture is foundational for information architecture to
happen. Information architecture might be seen as a specialization of
data architecture and would benefit from a mature data architect's
practice which has at the ready governance, principles and policies to
There is no one right answer. It requires an understanding of the
business, maturity in the EA practice, and readiness and availability
of the needed skills.
I have seen organizations that address information architecture as
part of their data architecture program. I have also seen data
architecture as a sub-domain of information architecture. And in some
organizations, I have seen information architecture happening, but
without the label. What I have not seen is the absence of either.
Both exist. Both are being done. It is on the EA practice to determine
the most effective way to fulfill the mandate of each.