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 crossdisciplinary 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 2014
^{1} as a means of improving communications and recording progress within systems engineering groups or workshops which, by their very nature, are multidisciplinary. 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 caputure relevant 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
Data Reference Models (DRMs) are a simple way for mixed competence groups to communicate so as to develop and information management system.
Since 2014 our associates have applied DRMs widely in the field of development of decision analysis models and IT tools to handle statistical reporting across many domains. DRMs have now been applied across hundreds of developments of analytical tools. The recent launch of Agenda 2030 Sustainable Development Goals has been accompanied by a large number of indicators which have yet to be defined and specified. Therefore, this document has been prepared as a practical guide of how apply DRMs for the growing number of stakeholders needing this type of support. This is a contribution to this process so that policy makers, project teams and strategists can define their own DRMs. DRMs take people as far as guiding project teams to specify the necessary data requirements and way to manage this in an information system assisting programmers in implementing systems.
During the last 50 years IT has been applied to an increasing range of applications but potential users of the information systems, the stakeholders, often find the terminology and concepts involved in IT design systems difficult to understand. This compromises the communication within participatory systems development groups. For example, the challenge of developing an appropriate system to handle information on sustainable agricultural production, monitoring and evaluation is complicated by the number of indicators that need to be collected. There is a need to facilitate group communication on social, economic, financial, ecosystem and physical environmental factors to improve the ability of stakeholders to contribute their knowledge and understanding to the specification of an effective information system.
The DRM is a simple structured communications medium for mixed competency groups who share a common objective of agreeing on the specifications and operational structure of an information system. The most common application is in support of standardized target data, such as coefficients or indicators applied to establish comparative measures of performance. In the case of each measure or indicator, each has a separate DRM because the data requirements for each indicator are usually distinct or the calculation methods differ.
A DRM (see Figure 1) contains descriptions of all processes involved in a systems operation to provide a transparent reference for use by all involved including administrators, application domain experts, technical personnel, statisticians, survey designers, information technology specialists and stakeholders concerning the structure and processes involved. This level of transparency is intended to support assessment of feedback on any details within a DRM by stakeholders so as to end up with a commonly agreed and understood system.
The DRM is a tabular ladderlike description of an information process running from where and how specified data is collected, processed and output to target data of the final form such as an indicator. The DRM combines the methodologies applied to collected data to calculate indicator values in the form of formulae, equations and algorithms consisting of mathematical logic, algebraic symbols and operators but also contains narratives and descriptions for nontechnical stakeholders.
The process of filling in the DRM in the case of an indicator is to “walk through” the description of each indicator by following the grey arrows from top to bottom, in the description column and in sequence describe:
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What is the indicator
How is it calculated
What data is used to calculate it
How does the data move from its collection point to where it is recorded and calculated?
What is the method of data collection?
Where is the data and when does the collection take place?
Figure 1. Typical DRM structure
Once these descriptions are agreed, the DRM is completed by another "walk through" following the blue arrows from bottom to top, specifying these descriptions in the description column into data specifications in the specification column.
 From where and when is data collected?
 Is this by full population or sample survey or other?
 What are assumed data storage and transmission system and protocols?
 What is the data element specification in terms of:
 property (identity/name)
 metrics (unit of measure)
 type (numeric, text, logical)
 precision (length of data and the scale or number of digits after the decimal point) Although precision usually applies to decimals in the DRMs this is also applied to minimum precision (length) of text. The format applied is of the form 5/2 which in the case of a decimal signifies a total number of digits of 5 of 2 follow the decimal point. In the case of text, the format is 40/0 which indicates a minimum number of spaces for 40 letters
 What is the method of calculation (algorithm, formula, equation) using the data elements to estimate the indicator value?
 What are the units or measures (dimensional expression) of the indicator
Because sometimes the specification column content is somewhat technical/mathematical the narrative column is completed with a simple description of the content of the specification column. To ensure that this column is understood by all, and in particular, nontechnical stakeholders, it is best to complete this column as a group to ensure there is agreement on the understanding of this column and therefore the whole DRM.
The reference to precision in relation to data elements does not refer to statistical precision or accuracy but rather to the IT data definition as dimension (length) of numbers and precision in terms of the number of decimal places included in the case of decimals in recording data. This is of importance in defining the levels of detail of information to be collected so that rounding up and down which occurs in calculation does not introduce errors of representation. Also, precision ensures that what enters the information management system is coherent within the design of the database that stores primary data and where precision is a required specification. Primary data sets of data elements require minimum standards of precision to reduce errors in the indicator value estimates.
It is assumed that the primary data collected in a survey, as well as any additional data required and available from other sources, makes up the primary data of each DRM.
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 nonIT specialists. Since it is often nonIT specialists who are decisionmakers 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.