Overview

The thesis postulates a way of Structuring an Information Universe using a Fourth Spatial Dimension; in particular, applying the combined ‘Necklace’ and ‘CyberCity’ approaches in order to facilitate an ontological model that provides a hierarchical structure for understanding relationships with data, thus providing an abstract method for enabling a so called 'Digital Backbone' with large data sets or numerous end-user applications as needed by organisations.

Modern Digital Services

The UK Government Digital Strategy and Delivery Service Manual expresses Digital in terms of People, Process, Information and Technology, the ‘Offerings’ (sometimes referred to as Digital Services) are further broken down according to a standards-based Framing Taxonomy of grouping operators known as ‘Services’ (such as Professional SME or named workflow interactions of activities, that contain multiple touchpoints known as Digital Services), ‘Platforms’ (bespoke aggregations of Products brought together for a named purpose) and ‘Products’ (fixed or unchangeable ‘off-the-shelf’). UK Government departments that require these Offerings, procure them via demand signals as placed on commercial procurement Channels, associated with Crown Commercial Services, which then facilitate the contractual transactions over either Frameworks or Dynamic Purchasing Systems. A true Digital Service embraces Customer-Centric thinking ‘at-its-heart’, where it encapsulates process, daily decision making, procedures and customer domain services, as its main impact pivots. Thus, all decisions need to be focussed on a seamless Customer Experience and its associated data (chunked, streamed or otherwise), through the design and identification of touchpoints in context, every function involved, from first interaction to ongoing relationship making up a single interaction or an ongoing journey. A Digital Service keeps in mind questions such as "what do they want", "what are their needs" or "how would they like to do business". Ultimately, it bespoke, simplify or differentiate a joined-up personalized Customer Experience by prioritizing the discrete areas that matter the most to a User when interacting with information via a ‘Digital Backbone’.

Structuring a Digital Backbone

A modern Digital Backbone is a carefully designed distributed communication layer (Data Mesh), consisting of individual building blocks, enabling an enterprise to react to rapid changes through providing the necessary Platforms (Data Fabric) needed in supporting short and long-term scalability through automation when undertaking Digital Workflows. Thus, it provides a comprehensive enabler backend for driving transformation; whether it’s artificial intelligence, process automation, analytics, cloud or something else, focussing on data as an organisations’ most important strategic asset.

The current explosion of interest in ‘Big data’ is now driven by the inclusion of much more unstructured data for analyses. According to analyst consensus, 80 percent of data falls into the ‘unstructured’ category, which is fundamentally different from ‘structured’ data. Unstructured content is largely created by humans: inconsistent, emotional, careless, opinionated, lazy, driven, over-worked, always unique, humans. In a 1998 Reuter’s report, information overload is seen as a problem by 42% of respondents. In the United Kingdom 47% stated that information overload damaged their relationships and 42% thought it reduced their job satisfaction. The principal reason is due to the amount of data and the plethora of isolated storage structures/methods used in organising it. Appreciating the origins of data and its hierarchical pyramid of future needs, as part of a Digital-First organisation, is the first step into producing actionable insights through applying logical structures in the form of 'Ontologies', ‘Taxonomies’, direct keyword ‘Tags’ or applying 'Semantic data' that exposes business value.

Understanding Information Overload

Information overload has been a problem for organisations where there have been a number of attempts to ease this problem from studies of the different types of information which cause overload to a more visual approach, the latter being particularly popular since the advent of the graphical user interface (GUI). Organisations are placing great value on the end-user device and its importance as a portal into managing information assets with numerous end-user device strategies to enable the best, most appropriate, hardware/management interface for both private and public sector knowledge workers. In recent years, studies have concentrated on the management or structuring of this complex information, re-branding it as ‘Big Data’ and the ways in which it is visualised within the office workspace environment.

Big data is commonly described as data that exceeds the processing capacity of conventional database systems. The data is too big, moves too fast, or doesn’t fit the structures of your database architectures. To gain value from this data, you must choose an alternative way to process it. While the term may seem to reference the volume of data, that isn’t always the case. The term big data – especially when used by vendors – may refer to the technology (which includes tools and processes) that an organisation requires to handle the large amounts of data and storage facilities.

References

Published Works

  • Richardson, D. E. (2009) ‘Structuring an Information Universe using a Fourth Spatial Dimension‘, PhD Thesis, Staffordshire University, United Kingdom.
  • Richardson, D. E. (2005) ‘Managing Shared Data‘, UK Patent Application No. GB2414574-A United Kingdom Intellectual Property Office (IPO).
  • Richardson, D. E. (2003/2004) ‘The Future Virtual Office’, BCS Chartered Institute for IT – Cheltenham Branch, Guest lectures Series.

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Concept

Virtual Gatekeeper was constructed as a means of demonstrating the implementation of the GMM model. All categories are visible with the addition of a central core which records use of the system linking into the database. In addition, search slots are shown; these record the results of searches made by the knowledge worker and recorded by the system. It should be noted that the conceptual model is based around the Workspace which consists of a number of search slots that are tied to it. Each labelled search slot would represent a single search that is useful for the category in which the knowledge worker resides. In this way a search (semantic or hyper-semantic) covers all lower categories that are based either on the local system of the knowledge worker and unique to their session, or search across all lower categories associated with the category which they are in.

Play Demo

Searching across documents/categories of project workspaces or across the entire project workspaces assigned to multiple knowledge workers is facilitated, the results of which are then shown as a search slot workspace as indicated in the inner ring and labelled accordingly. Should this search workspace become further tailored or sorted according to further refinement by the knowledge worker, then this can be promoted to the outer ring as a newly named workspace with the previous search block being cleared. This means that the project will now include dynamically updatable shared documents as part of its structure since these are being changed by other knowledge workers who are associated with that particular project.

Model

The Thesis has modelled its outline solution on the following five issues concerning the management of information:

  1. Linking tasks and associated information
  2. Lack of current structure for ordering and accessing information
  3. Automation of indexing of information
  4. Persisted activity sessions
  5. Screen clutter of task documents

It has therefore attempted to solve these five issues by remodelling the design paradigm of a computer system rather than modifying the presentation layer directly, while leaving the data layer untouched. Techniques such as the Necklace or CyberCity approaches are examined as at their heart they facilitate an animation-based interaction architecture termed the ‘Cognitive Coprocessor’, where the behaviour of the interactive system can always be described as the product of the interactions of (at least) three agents.

However, in 2009 no system appeared to exist which satisfied all of the five issues. In particular issue 2, the ordering, accessing and structuring of information seems to have been a particular stumbling block. A possible solution for overcoming this issue is to use an ontological model within the design of the system to force the knowledge worker automatically to tag the categorisation levels.

  • Data are discrete symbols that represent facts. You might think of them as recordings or statistics.
    • There is no meaning or significance beyond the data’s existence.
    • Data may be clean or noisy; structured or unstructured; relevant or irrelevant.
  • Information is data that has been processed to be useful. I like to think of it as adding the first bit of context to data relating to “who”, “what”, “where”, and “when”.
    • Information captures data at a single point in time and from a particular context; it can be wrong.
  • Knowledge is the mental application of data and information. Most consider this as addressing questions around “how”.
    • Some consider knowledge a deterministic process, which is to say the appropriation of information with the intent of use.
  • Wisdom is the evaluation and internalization of knowledge. It applies insight and understanding to answer “why” and “should” questions.

Consequently, the thesis now proceeds to discuss an ontological model for categorising information within an Information Universe structuring approach.

The conceptual Generic Management Model for large datasets provides a means of satisfying the highlighted five issues and then provides an Information Universe Model foundation for developing domain specific applications upon that extend traditional 2D/3D representations of space through the incorporation of an additional spatial dimension.

In order to conceptualise the underlying data structure and relationship linking it was necessary to use techniques which were inspired from geometry and which map spatial dimensions in 4D onto stereographic geometric object representations in 3D. This facilitated the interaction of the underlying data objects which mirrored the data dimensionality.

This differs from present day approaches since the user interface is firmly coupled with the data repositories through the Information Universe Model. This Information Universe approach gives the foundation for developing domain specific applications such as the Virtual Gatekeeper concept. It does not however, define the design of the User interface in any way. Early evaluation revealed that this new system, based upon the model, was usable and reduced cognitive load for experienced knowledge workers.

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