Do you find the information you need?

Taxonomy & Taxonomies

A disorganised system will be prone to stagnation, have limited user adoption and dissolve into chaos!  Do you have a Taxonomy?

If a taxonomy is formed at the outset of an information management project, a foundation can be defined that will enable the organisation to expand and evolve their system as demands change.

Taxonomy – the hierarchical classification of entities. Including the principles that underlie such classification – according to Wikipedia.

Plural noun: taxonomies

“a taxonomy of …”

Early 19th century: coined in French from Greek taxis ‘arrangement’ + -nomia ‘distribution’.

Taxonomy Greek French

Use over time of the term Taxonomy.


Example Taxonomies: A car is a subtype of vehicle, so a car is a vehicle but not every vehicle is a car

For Food.


The story goes that if Microsoft had made completion of the properties box of all Office documents mandatory there would be no need for document management systems. But, “we are where we are”, we need to develop taxonomies – a set of chosen terms used to retrieve on-line content – to make the search and browse capabilities of the content, document or records management systems truly functional.

Be it a taxonomy designed for storage and management or one that supports better search, without them all types of management system are near useless.

Organising information

A business taxonomy should be the primary storage design for an enterprise’s content. Organising content in the same way supports the interoperability of systems. The benefit of having structured and unstructured information sources able to relate to common topics is limitless.

Increasing usability

By organising all corporate data in a single way, the overall usability of knowledge systems increases considerably. No longer will staff need to learn the methodology behind one system, only to find a different one for the next tool. Importantly, business users get to sift through information available to them to find what they need and avoid the duplication of effort that bedevils much of corporate life.

A business taxonomy forces system designers to classify metadata fields to content categories – for example, department, location, topic, document type, etc. A list of metadata values is then defined to populate each field in-line with the taxonomy. This restraint is critical to making system designers adhere to a strategic vision rather than one of their own.

Using a consistent taxonomy for content storage helps an enterprise understand the information it holds as well as that which is missing. By referencing like information within a single schema / plan it will be able to use related information that was previously divided into separate areas of management. This is particularly important, though more complex, when working with multi-disciplinary teams.

Steps to successful taxonomy design – curtesy of PPC

Roles and responsibilities

·         Governance board – define strategy and the appropriate type of content

·         Taxonomy team – ensure the value of content placement and metadata (a minimum of six and maximum of 12 members)

·         Content managers – approve and edit content

·         Content owners – publish content and apply metadata

Understand your content

·         More content means more time to re-tag

·         Clean out old or obsolete content

·         Every item has one correct categorisation

·         Items may be organised into multiple categories

·         Minimise number of ‘clicks’

·         Allow flexibility and redundancy

·         Strive for topical taxonomy

Before getting started understand your:

·         Audience

·         Publishers

·         Platform

·         Content

·         Limitations

Getting started

·         Keep it broad, shallow, simple and elegant

·         Six to 12 top-level categories.

·         Two or three levels deep.

·         Focus mainly on the primary, top-level concepts

·         Be inspired by existing schemes. e.g. industry standards and local practices

 Why Taxonomy is Critical to Master Data Management (MDM)

Organizations are paying more and more attention to Master Data Management (MDM) in this world of big data. MDM comprises a set of processes and tools that consistently defines and manages the non-transactional data entities of an organization.

MDM promises not just greater control over consistent reference data; but an ability to manage the relations between data entities in order to generate more effective business knowledge. From this perspective, MDM requires an understanding and agreement about the meaning of terminology. Hence, the natural role of taxonomy.

Taxonomy is about “semantic architecture” – it is about naming things and making decisions about how to map different concepts and terms to a consistent  structure.   One challenge to an MDM data architecture is ambiguity.  The same term can have different meanings.  Taxonomy includes mechanisms for understanding context and making meaning precise.   Another challenge is consistency, people naturally use terms inconsistently, if given a choice.  A thesaurus attached to the taxonomy can map terms together to account for these inconsistencies.

For more on the role of taxonomy in master data management see:

Taxonomies in Social Media Analytics

First let’s establish what ‘social media analytics’ and ‘taxonomy’ mean. According to Wikipedia:

Social media analytics (listening) is: “Measuring + Analysing + Interpreting interactions and associations between people, topics and ideas”. Some people use “social analytics” as a term in an interchangeable way with “social media analytics”.

Taxonomies in a social listening context are used to describe a product category, an industry vertical, or simply a subject, like the 2015 parliament elections in the UK. When used to analyse posts from social media, they act as “dictionaries” which include the words people use to discuss the subject/category online.

In social listening, when millions of posts about a product category in a specific language need to be analysed in order to extract insights, the following disciplines and skill sets are required:

  • Machine learning – to annotate sentiment with accuracy as high as possible
  • Taxonomy in order to know the themes and sub-themes or topics of conversation
  • Complex Boolean logic for data cleaning, i.e. excluding the irrelevant posts (noise)

What do you need to do to check you taxonomy or do you need to think about what your taxonomy will be for your forthcoming big data, information management / governance project?

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