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There are many existing information systems modeling approaches and languages. However, they can take time to learn and as a result slow down effective communications within systems groups with many types and levels of experience and specialization.

The OQSI Data Reference Model is a practical solution to this dilemma by providing a simple, intuitive but practical basis for the description and cross-disciplinary communication of the details of a complete information system in an effective manner.

Analytical refinement and granularity can be varied at will by altering the number of logical levels used.


DRM Data Reference Models were proposed during a DAI workshop in 20141 as a means of improving communications and recording progress within systems engineering groups or workshops which, by their very nature, are multi-disciplinary. DRMs are not designed primarily for systems engineers or information technology experts but rather for mixed ability groups. The scope of DRM applications is very wide and includes:
  • systems (process and project) design
  • decision analysis model identification - including algorithms, mathematical, statistical and logical procedures including operations research methods
  • a quantitative outline of a whole information systems architecture including all resource inputs including hardware, software, human resources, data processing logic, target data sets, data collection, date input and resource funding (finance)
  • developing comprehensive indicators that capture relevant cause and effect relationships of data elements and an indicator's function
  • a data, information & knowledge relationships model (data flow and quality)
  • design of data or information analysis systems for any purpose
  • data analysis training for any analytical application
  • providing business model context for a systems specifications
  • designing procedural manuals for users of administrative information system
  • identifying data redundancy
  • identifying complete datasets for complex representations such as environmental indicators
  • comparative gap analysis in any component of an information management system by comparing 2 DRMs
  • transparent medium for describing a system team's objectives
  • transparent medium for recording team progress by keeping the sequence of progressive DRM content changes
  • a record for monitoring and evaluation
Outline of DRM structure



















A generic example

DRM level
Example
Measure, a target, the reason for collecting dataA performance ratio, an indicator, a calculation of interest
Conversion of dataHow is the core dataset manipulated to provide output above? e.g. algorithm
What data is requiredWhat is the core dataset used as input to the conversion process above
Data elementsSpecifications of the data elements required: What does each data element convey about what?
Data element unitsSpecifications of the unit of measure of each data element
Where are the phenomena that data elements describe/measure?In statistical series, on a farm, in an industrial unit
In OOL: Where are the objects whose properties the data elements describe/measure?In statistical series, on a farm, in an industrial unit
Accessibility (location and time)Any periodicy to release of data or seasonality issues that determine availability
In OOL: What are the locational-state elements?Location and time dimensions added to specification to define required data collection location and time
Data quality requirementsSpecific data element quality requirements (e.g. sensitivity of Measure to data errors)
1. How can data elements be collected?Methods of data element collection
2. How can data elements be collected?Design of survey or access methods
2. How can data elements be collected?Costs of collection
How can data elements be transferred to where it will be converted into the desired measure?Methods of recording and transmission
2. How can data elements be transferred to where it will be converted into the desired measure?Costs of recording and transmission




The process of designing and rationalizing the management of information in a commercial or policy environment has become complex because of the large range of expertise, experience and knowledge (specializations) required to design systems or identify policies with the intent of achieving economic, effective and efficient results. This multi-disciplinary reality can create a communications challenge between decision makers who might not be information technology specialists, on what they want an information system to achieve. Decision-makers may know the end result they desire (e.g. to improve some functionality of their processes or get rid of, or reduce, a problem) but are not acquainted with the best means of designing actions to resolve the issue.

The DRM has the role of providing a means of describing what the decision-maker understands and intends (objectives for what?), the process of achieving the objectives (how?) in terms of actions and the information required to manage such actions. It can have two basic outputs which have different objectives:

  1. A description of the required process operation including: target data sets, data collection, conversion and delivery to the final user.
  2. This same structure can be used by process designers to implement the required information management system including data entry, data processing algorithms, data transfer and storage, processing power and communications infrastructure.

Unlike most systems modeling languages DRMs can be used to relate how:
  • data is collected
  • data is input to an information system
  • data is processed
  • processing outputs are applied outside the system
It places an information system within the context of what the data is used for by the people using the system including operators or administrations concerned with data processing. As such, DRMs can also be used for human resources planning in association with information systems design so as to identify those systems that have the highest likelihood of higher operational productivity to secure operational economy, efficiency and effectiveness.



The DRM is an attempt to represent the "whole system's" functional resources, including hardware, software and people. The DRM consists of a series of Levels each containing descriptions of why or how the data is collected, stored and analyzed. It can therefore be used to make explicit differences between current data sets and those that emerge as a result of new requirements of design options which identify which elements are to be added, to be deleted or where the specification is changed in terms of statistical error, precision of measurement or frequency of collection, for example.

A basic structure of a DRM is set out in the box on the left. The diagram shows 6 levels arranged in a vertical column (see below) The number of content would, in practice, vary according to the specific objective and complexity of the system being addressed by each DRM but it is advisable to maintain a common overall structure to enhance “ease of recognition and comparison".

The top levels A, B etc are essentially headline statements of purpose and specific objectives but this information is in fact derived from activities in lower levels as a result of the needs analysis and systems or policy analysis activities.



Legal processes that make use of implied DRMs

Besides design preparation in engineering and simulation, an example of a suitable application for DRM is the analysis and comparison of the so-called "administrative structures" or organizations that are responsible for statistical and regulatory information subject to pre-specified legal frameworks, procedures and methods. European Union legislation in such fields as the environment, agricultural policy (DG Agri) and statistics collection (EUROSTAT) can be "interpreted" as a rudimentary DRM.

For example the higher levels of a DRM describing such legislation would contain the legislative objectives and stated means of achieving those objectives. The logic of why any particular legislative act is deemed to be relevant to the resolution of specific issue might not always be evident but the assessment and identification of any rational logic depends upon the use of a decision analysis model. This consists of a deterministic model (usually a quantitative description of cause and effect or input output) so as to identify all of the factors that influence the outcome of the policy decisions or legislative acts. Sometimes the logic can be determined from the statutory information that the legislation requires to be collected to manage or oversee the policy. This can be data sets used to analyse emerging states (statistical information) or policy progress or to check the adoption of procedures that are regulated under the law (regulatory information). It is therefore apparent that in order to support such legislative frameworks that there is a need for a system of data collection and analysis which will require information technology resources. The details on the decision analysis models, data sets, how the data is collected and processed in terms of information technology specifications can make up additional levels of the DRM.



The multi-level structure of the DRM, or the need-solution cascade, is that of an object orientated description of the system consisting of distinct separate objects each with specific properties and method/s. The methods describe the object's contribution to the overall system's information process. This characteristic facilitates the ease with which a DRM can represent data flow in terms of simulation models built in an object orientated language with each level of the DRM being a Node.
The need and solution cascade is the basic structure of the DRM





Because of their basic object orientation DRMs are a good basis for integrating several business models, for example:
  • how data is collected and input to system
  • how system operational personnel perform
  • how users access output
  • what users do with the output
In this way it is possible to isolate functionality into discrete but related economic/financial profit centres to optimize the overall systems sustainability through operational economic and financial risk reduction.



DRMs have come about because some of the solutions for specifying systems proposed by information technologists have often been somewhat difficult to comprehend on the part of non-IT specialists. Since it is often non-IT specialists who are decision-makers concerning the commitment of resources to the implementation of systems, there is a need for a better communications medium that enables all aspects of a systems design to be presented within one document. The interfaces between each section need to be transparent enough to enable how a need at one level is handled by a solution at the next level down. The DRM therefore provides a means of presenting a cascade of needs and solutions at all levels of a systems operation. This recommendation will be extended with examples of different domain applications for DRMs.





What can be recognized from the DRM structure is that it is in essence another way of describing Kaufman's Needs analysis approach, the Organizational Elemental Analysis. This details the organizational elements at different levels of planning with a similar aim to the DRM. However, the DRM is also fundamentally a communications device that has an important role in maximizing the participatory nature of systems development and design.

Kaufman's approach is the subject of another OQSI recommendation.

1  McNeill, H.W., "Improving communications within systems groups", Decision Analysis Initiative 2010-2015, Portsmouth, August, 2014.- click to access
Updated:

15th August, 2015.
20th October, 2015.