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DIKAR Framework connects data to action and measurable results
Listen to Nicklas Malmsjö in the presentation “From Records to Value", Arkeion conference, Royal Swedish Academy of Engineering Sciences (IVA), Stockholm 2025-10-14
The conceptual core of DIKAR Framework
Data → Information → Knowledge → Action → Result
From the DIKAR model to the DIKAR Framework
Original DIKAR Model
Source: Ward and Peppard Strategic planning for information systems p 506, 2002)
The original DIKAR Model
The DIKAR Model – Data, Information, Knowledge, Action and Results – is associated with N. Venkatraman and was described by Ward and Peppard (2002). It provides the conceptual foundation for the DIKAR Framework.
The DIKAR Framework
Since 2016, Nicklas Malmsjö has developed this foundation into a practically applicable umbrella framework for data-driven governance and AI-ready information management. The DIKAR Framework emphasizes the importance of preparatory work, interdisciplinary collaboration, iterative application, connections to complementary frameworks and standards and value creation.
Common perspective
Organisations often manage data, information, knowledge, actions and results as separate domains. DIKAR Framework provides a common perspective for understanding how these elements link and connects and how these connections affect measurable results.
A common structure and shared language enables organisations to:
ensure data and information quality
build knowledge
make informed decisions
turn insights into action
achieve measurable results
continuously improve the information process (iterative approach)
DIKAR Framework connects disciplines such as:
Data governance
Information management
Records management
Knowledge management
Analytics
Enterprise architecture
AI governance
Information architecture
Information security
Information management is no longer only about compliance or long-term preservation. It is about creating results and value.
To succeed, organisations need:
high-quality data
usable information
shared and understood knowledge
decisions that lead to action
actions that lead to results
connecting underlying models and frameworks
The DIKAR Framework connects this entire chain and enables continuous improvement through an iterative workflow.
DIKAR Framework uses the DIKAR model as a simple underlying logic.
DIKAR stands for Data, Information, Knowledge, Action and Result.
The quality of results is influensed by the quality of the actions taken.
The quality of your actions is influensed by the knowledge available.
The quality of your knowledge is influensed by the information on which it based on.
The quality of your information is influensed by the underlying and its context.
The DIKAR Framework therefore focuses not only on the individual stages but also on the conditions and connections that enable movement between them. Weakness in one part of the process can affect subsequent stages and ultimately the results.
The DIKAR Framework approach is iterative – results can generate new data, insights and feedback that inform subsequent cycles.
The links between the stages
The DIKAR chain is only as strong as the transitions between its stages(Data-Information-Knowledge-Action-Result). Value is not created automatically when data becomes information, knowledge leads to action or action produces results. Each transition requires the right conditions, capabilities and collaboration to carry the process forward. Breakdowns often occur in these handovers — where information, responsibility or meaning is lost between functions and disciplines (Ward and Peppard pp. 506, 2002).
The RAKID perspective
The DIKAR model can also be read in reverse described as RAKID. This perspective allows you to start with the results you want to achieve and then work backwards to determine what actions, knowledge, information and data are required. (Ward and Peppard pp. 507-508, 2002)
The DIKAR Framework builds further on this logic and emphasizes the connections between data, information, knowledge, action and results. DIKAR Framework also emphasizes the interdisciplinary capabilities, ways of working, models, methods, standards and practices to create effective connections between them.
Achieving results requires collaboration across multiple disciplines, including:
IT and system development
records and information management
information architecture
analytics and business development
legal, security and governance
The DIKAR Framework provides a common structure that aligns these perspectives and enables effective collaboration.
A data-driven organisation requires cross-disciplinary collaboration.
Just like a house, where electricity, water and ventilation must be coordinated to function as a whole, a data-driven organisation must also be coordinated into a coherent and functioning system.
This is where the DIKAR Framework comes in.
By applying DIKAR Framework organisations can:
create structure in information management
clarify roles and responsibilities
ensure data quality
connect analysis to decisions
turn decisions into action
achieve measurable results
The DIKAR Framework is designed for practical implementation.
It integrates:
data quality and provenance
long-term preservation and authenticity
analysis, decision-making and results
Through coordinated alignment of:
strategy (goals and desired outcomes)
infrastructure (systems, standards, models and metadata)
operational processes (e.g. data collection, classification, quality assurance)
a stable foundation for data-driven development is established.
The DIKAR Framework provides the overall perspective, structure and direction while the practical implementation needs to be shaped and adapted to each organisation´s context, conditions and needs. The operational work therefore needs to be carried out locally by interdisciplinary teams.
Start simple:
Choose one process, decision or problem
Map it using DIKAR Framework
Identify where it breaks
Fix one thing and follow up the result
The DIKAR Framework is continuously evolving through practical application, professional dialogue and collaboration across disciplines and organisational contexts.
Explore ongoing discussions, applications and perspectives in the DIKAR Framework Linkedin group.
The DIKAR Framework builds on established theory and research in information and knowledge management including the DIKW and the DIKAR model (Ward & Peppard, based on N. Venkatraman) as well as related fields such as information systems, archival science, information science, knowledge management and organisational theory.
The result is a coherent framework for data-driven public sector development and AI-ready information management.
Background
The DIKAR Framework was developed by the information strategist Nicklas Malmsjö, Uppsala Sweden.
It builds on a strong Scandinavian tradition of structured and transparent public sector development.
Since 2016, the DIKAR Framework has evolved from the original theoretical DIKAR model into a practically applicable interdisciplinary umbrella framework for data-driven governance and AI-ready information management, particularly adapted to the public sector.
The further development involves using the DIKAR model's value chain (data-information-knowledge-action-results) to connect established models, standards, disciplines, and working methods under a common umbrella framework to provide wholeness, direction, and structure throughout the entire data-driven information process.
The framework bridges theory and practice and provides a structured way of understanding how data can contribute to information, knowledge, action and results and ultimately to value for organisations, citizens and society.
Further reading
DIKAR model
Ward, John; Peppard, Joe, "Strategic planning for information systems", 2002
Based on the work of N Venkatraman page 207, 506-512.
Examples of relevant standards etc
Data
ISO 11179 (metadata registry standard)
Information and records
ISO 15489 – Records management
ISO 23081 – Metadata for records
ISO 14721 – OAIS reference model for digital preservation
ISO 16363 – Trusted digital repositories
MoreQ – European specification for managing electronic records and archives.
Knowledge management
ISO 30401 – Knowledge management systems
Architecture
TOGAF – Enterprise Architecture
Governance and security
ISO 27001 – Information security management systems
IS0 37301 Compliance management system
ISO /IEC 42001 I– Artificial intelligence management systems
ISO 9001 – Quality management systems
Policies etc
OECD AI principles
EU AI act – Artificial intelligence regulation framework
European commission European Interoperability Framework (EIF) – Interoperability in public sector systems
For more information about the DIKAR Framework:
mail: contact.dikarframework@gmail.com
Nicklas Malmsjö
Linkedin
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