Exploring the Data Management Body of Knowledge (DMBoK) for Data Citizens

Executive Summary

This webinar covers key topics in the advancement of data management and governance frameworks. Howard Diesel weighs the strengths and weaknesses of DMBoK Version 3 and makes the case for a comprehensive content strategy, along with effective board representation in international relations. He then works through international travel opportunities and the importance of global collaboration in data management, touching on open science, intellectual property, and volunteer-based organisational structures.

The webinar also covers the challenges of validating the CDMP exam, the future of open-source technologies, and setting up an architectural governance board. Howard outlines the growth of data management frameworks, the development of a digital vocabulary framework, and the role information governance and AI play in strengthening data management practices.

Webinar Details

Title: Exploring the Data Management Body of Knowledge (DMBoK) for Data Citizens
Date: 2025-07-10
Presenter: Howard Diesel
Meetup Group: African Data Management Community
Write-up Author: Howard Diesel

Review of the DMBoK Version 3

Howard Diesel opened the webinar picking up where the last one left off, continuing the review of DMBoK versions two and three. He thanked attendees for their feedback and help identifying gaps in the main team slides, then shared a ranking of standardised strengths, weaknesses, opportunities, and threats (SWOT), and asked for participation in a mentee quiz to gather further rankings.

In the previous webinar, Howard had worked through various perspectives on authority and weaknesses within the group, sharing that the review team had initially flagged slow update cycles as a significant weakness. The feedback since then opened up some alternative viewpoints worth considering.

Figure 1 DMBoK Version Two SWOT Analysis

Figure 2 Rank your DMBoK Weaknesses

Figure 3 Rank the DMBoK Version Two Strengths

Figure 4 Rank your DMBoK Weaknesses Pt.2

Figure 5 DMBoK SWOT

Strengths and Weaknesses of a Content Strategy

The recent assessment came out at -13, a predominantly negative score, with 24 identified weaknesses against just 17 strengths. The scoring assigned +2 for strengths, -2 for weaknesses, +1 for opportunities, and -1 for threats, on the logic that strengths can be relied on while opportunities remain uncertain. Key weaknesses noted included a lack of KPIs, inconsistent practices, unclear integration between knowledge areas, outdated information, and limited coverage of real-time data and streaming.

Howard was fairly critical about the DMBoK’s current relevance, worried it may now carry more weaknesses than strengths. One attendee said their own view of the DMBoK had shifted over time, feeling it’s noticeably weaker than it was five years ago, a sign of it slipping.

Identifying the target audience mattered a lot here, particularly around producing material that speaks to a younger generation entering the field. The group acknowledged their own experience makes them good at spotting risks and threats, but said they’d like to see a more proactive focus on opportunities for newcomers.

During the discussion on strategy and how the SWOT analysis was run, one attendee pointed out how easy it is for people to fixate on problems rather than opportunities or strengths. Keeping content regularly updated matters for staying relevant and useful, they said, since outdated information tends to hurt both perception and usability.

That observation echoes something Howard sees a lot in his own data strategy work, where complaints about obstacles tend to drown out conversations about potential improvements.

Howard also raised the issue of understanding core concepts degrading over time, and how that degradation speeds up given how exponentially things change. The longer it goes on, the more oversimplified the view of core ideas becomes, missing relevant angles and topics along the way, which chips away at a solid grasp of the important principles.

Figure 6 Rank your DMBoK Weaknesses Pt.3

Figure 7 Rank your DMBoK Version Three Opportunities

Board Representation and International Relations

Concerns came up about the makeup of the editorial board, specifically how many members are based in the US relative to other countries. Several attendees raised this, and it drew a fair amount of attention. Worth noting: while a lot of members are indeed US-based, the discussion was about the editorial board specifically, not the DAMA International board.

International Travel Opportunities

The conversation then moved to opportunities. Six of eleven identified opportunities are currently active, with Canada included given its relevance to North America. Questions came up about China and Saudi Arabia too, and someone asked whether a reference to Denmark was correct, it turned out to actually be Belgium. The complaints on this front seem to be growing, which suggests it’s a real issue worth watching.

Global Collaboration and Data Management Opportunities

Howard stressed how much global collaboration and localised partnerships matter, particularly given regulatory frameworks like Canada’s data privacy laws or the AI Act and GDPR in Europe. A localised approach is what lets specific regional issues get addressed while still scaling publications and content built at the DAMA chapter level. He also flagged the need to bring academic insight into these collaborations, a real shift from the mostly corporate focus of five years ago toward a more inclusive strategy that values a wider range of perspectives.

The private sector and government both face their own challenges here, and higher education matters too, since data is a genuinely valuable asset for universities even if they’re slower to adapt. All these entities, it turns out, share a lot of the same concerns about data management.

Frameworks like the DMBoK don’t represent higher education and local government well, which is a gap worth noting. One attendee was frustrated by how complicated schools find these issues and pushed for more accessible solutions. There’s also a growing body of academic research on international frameworks for effective data governance, tackling real-world challenges, particularly in regions like Africa.

Howard pointed to the growing importance of data governance, data literacy, and data management in smaller institutions, not just the big universities, even though the scale differs. People at these institutions are actively looking for research on what’s worked elsewhere, since data challenges tend to be universal regardless of size.

There’s been a real shift since the pre-COVID days, when data management was mostly viewed through a corporate lens, to now being seen as essential for educational institutions too. Access to relevant research has grown alongside that, a sign that effective data practices are being taken seriously in academia.

Data governance is picking up real momentum right now, with universities both locally and internationally discussing it. Researchers are increasingly publishing on data as a realised asset, and there’s a genuine collaboration emerging between commerce professionals and academics.

It points to a broader trend: the old divide between practical and scholarly work is narrowing, making room for a more dynamic exchange of ideas. All told, it’s opening up real opportunities for engagement and progress in data governance.

Figure 8 Academic Articles on Data Governance

Figure 9 Academic Articles on Data Governance Pt.2

Figure 10 Rank your DMBoK Version Three Opportunities

Figure 11 Rank your DMBoK Version Three Publication Threats

Open Science, Intellectual Property, and Volunteer-Based Organisational Structure

Intellectual property came up as a real concern in the context of Open Science, particularly as global collaboration grows and more diverse contributors get involved in creating content. Sorting out potential conflicts in IP ownership matters here, especially given that IP originating in the US carries specific rights tied to that origin.

One attendee suggested that as things like DMBoK 3 develop, ownership rights will need careful positioning to keep things fair for every contributor involved, alongside a real focus on quality control.

Howard raised concerns about the quality of content coming out of volunteer-based organisations like DAMA, and the fragmentation that comes with it, both of which make it harder to compete with frameworks backed by full-time staff.

There’s something of a “volunteer complex” at play too, where being run by volunteers can create a perception of slower pace that hurts responsiveness and effectiveness. PMI, which also relies on volunteers, takes a different approach, treating volunteer roles with the same seriousness as paid ones. PMI’s collaboration tools also get described as building a strong sense of community and enabling immediate interaction, which makes their exam sign-up process feel noticeably smoother than DMBoK’s.

Howard drew a distinction between how PMI is structured operationally and its PMP certification, noting that while PMI does have some full-time staff, a lot of the work still runs on volunteers. There’s a perceived gap between PMI’s approach and that of other organisations doing global collaboration, especially given PMI’s standing as a standard-setter in project management. Even so, PMI’s certification carries international recognition, and it’s a level of credibility other frameworks, DMBoK included, could reasonably aspire to.

Figure 12 Rank your DMBoK Version Three Publication Threats Pt.2

Challenges of Validating the CDMP Exam

Registering for CDMP exams with the South African government requires evidence of backing from a recognised university or academic institution to validate the qualification, and it’s unclear whether PMI offers that kind of academic endorsement for its own certification. Validation typically comes down to the original documents supplied, original degrees or certificates along with their identification numbers.

One attendee pointed out that in South Africa, getting a certification like the CDMP integrated into the national qualification framework (NQF) needs approval from academic institutions, which matters because companies need to link certifications to the Skills Development Fund to make claims. Without an NQF number, that’s simply not possible.

Future of Open Source and Global Collaboration in Technology

One attendee shared they’d decided to wait for version 3 to release, since they feel it better matches where their career is headed. They’re a little uneasy about what might change between now and 2027, and questioned why there isn’t more openness to open-source approaches, drawing a comparison to Python, developed and maintained entirely by a volunteer community with no paid staff, as an example of staying adaptable in a fast-changing environment.

Post-COVID, the data landscape keeps shifting, which puts pressure on new frameworks to stay relevant as content ages quickly. One attendee pointed to the value of a global collaboration platform that could pull in expert insight on digital rights management (DRM), noting the tension between protecting proprietary knowledge and the benefits of open access, and that clinging to older models risks losing real opportunities. Strategies for fostering that kind of collaboration and keeping content continuously updated are being explored to work through these challenges.

Howard then turned to building a structured approach to content control, keeping a solid core while allowing for modular extensions, a system that can absorb new information, ideas, and local perspectives, and let the community contribute papers directly. The initiative, called “Global Voices,” aims to open up contribution portals and categorise content for different audiences, executives and practice managers among them. A peer review process may get added too, to strengthen credibility and visibility of submissions, alongside a proposed taxonomy for classifying articles by topic, governance and security, for instance.

The data management field is growing, but professionals in it are stretched thin, which makes it hard to find time to invest in a fast-moving industry. A collaboration tool similar to what PMI uses, with structured templates and community support, could help drive more engagement and growth in data certification and practice. The goal is publishing collaborative calls built around core principles, with room to extend into areas like reference and master data.

Ontologies and knowledge graphs are helping global collaboration along, enabling a more granular approach to creating and managing content. As people get comfortable working with these frameworks, they can contribute genuinely valuable content that becomes part of a broader body of knowledge. The emphasis is on keeping a streamlined core framework while making community-driven extensions faster and more efficient, which includes establishing content lineage and building living documents to keep the knowledge base growing and adaptable.

Figure 13 TOWS Strategy

Figure 14 TOWS Strategy Themes

Figure 15 SWOT Strategy Analysis

Creation of an Architectural Governance Board

Howard made the case for a comprehensive reference framework architects can use to build an architectural governance model, one that lets people see how their projects fit into the bigger picture, while encouraging contributions through a controlled vocabulary that keeps additions appropriate. The aim is a structured way for users to classify their work and pull up detailed information easily, which strengthens collaboration and integration across the framework.

Growth of Data Management Frameworks

Growing this framework properly means making it practical and accessible, not just theoretical. Engaging the audience takes clear methods and models that make implementation simple. The core should stick to the “why” and “what,” while global collaboration handles the “how” through practical templates and implementation frameworks.

That’s what makes it possible to produce genuinely relevant content, the kind authors like Jeanette McGilleray put out, with specific techniques for applying principles such as data quality within organisations. Keeping the vocabulary aligned with the core model reinforces the fundamentals while making adoption and execution easier.

One attendee stressed how much clarity and structure matter for data management certification and practice, particularly in Latin America, and how important it is to establish a common language around data governance, since plenty of companies and job seekers don’t have a clear picture of what data management even covers.

Certifications like APMI are well recognised for project management roles, but there’s often real confusion around what qualifies someone for a data management position. Howard suggested frameworks that offer a standardised approach to data governance would help, giving the field better communication and shared understanding.

The rapid growth of AI and big data is a real opportunity for advancing data management frameworks and initiatives. With competitors emerging and technology moving at such a fast clip, it matters more than ever to sharpen our understanding of what actually makes data good.

That understanding is what drives better decision-making and keeps data management visible. A SWOT analysis helps here too, identifying strengths worth leveraging, opportunities worth capitalising on, and weaknesses worth addressing, all in service of making better use of the current landscape for data.

Tackling opportunities means identifying specific strategies to capitalise on them, while at the same time assessing weaknesses and threats and building actionable plans to address them. The real work is in exploring how these factors interact and making changes that improve service delivery and overall performance.

Figure 16 TOWS Strategy Pt.2

Development of a Digital Vocabulary Framework

There’s an ongoing debate about how to manage the dictionary itself, whether to lean on the dictionary as-is or move toward an ontology or controlled vocabulary. Howard emphasised how much language and meta-models matter for structuring information effectively.

Howard stressed the need for a comprehensive content delivery framework that serves two types of users: those who want a structured, wiki-like experience, and those who’d rather move freely between topics. Ontology or a similar referencing mechanism matters a lot here, he said, alongside key challenges like managing digital rights, enabling user contributions, maintaining quality, and speeding up how quickly articles become available, all while sticking to acceptable procedures and frameworks.

There’s an upcoming three-hour session dedicated to pinning down the definition of data management and whether it still holds up, particularly against existing frameworks like Dewey. Getting participants aligned on what data management actually means matters, since it’s the foundation everything else, vocabulary and requirements included, gets built on.

That alignment matters because disagreement here risks fragmenting publications and undermining the strength of the existing foundation. A professional editor would also be brought in to keep the output clear and cohesive.

Howard also pointed to room for expansion beyond the first version, with a structured progression from version one through to later revisions, version two and its own revision, for instance, setting a solid standard. He voiced some concern about getting that alignment right, acknowledging it would be a real shame if it didn’t happen, while staying hopeful it will.

Information Governance and the Role of AI in Data Management

One attendee shared that discussions around information governance date back to 2009, when IBM launched the International Information Governance Council, which they were part of. A big part of its success in South Africa came down to enthusiasm around regulatory change, particularly new standards introduced by the Institute of Directors, tied to the King Report, King III specifically, which shaped a lot of corporate governance practice.

King 2, released in 2009, had a real influence on corporate governance at director level and stressed the importance of effective information management. With King 4 currently in draft, there’s room for further progress here. The King series is widely regarded as a solid global standard for corporate governance, though it doesn’t fully address the concerns Christina raised around universities and other sectors. Understanding what actually drives directors, and aligning that with these governance frameworks, matters for effective corporate management.

Howard talked through the complexity of aligning stakeholders with the right roles, and the difficulty of managing the back-and-forth between technicians and executives. Different issues need different handling, he said, and the Chief Digital Officer ends up playing a critical role in navigating all of that.

The complexity of data management across different levels came up too, along with the importance of a unified approach when engaging multiple stakeholders at once. Howard also stressed keeping content presentation consistent across areas, to avoid confusion during transitions.

One attendee brought up the Zachman framework, noting how important it is for content to suit different personas, executives included. Drawing on their own experience, they made the case for using AI tools like “Claude” to strengthen quality control and keep document presentation consistent, seeing real potential in AI-driven solutions for improving data management, provided there’s the right oversight.

Having a professional editor keep things consistent within and across chapters came up too, the goal being a cohesive narrative that reads as if it were written by one voice, the DMBoK’s.

The board has already outlined this approach, with uniformity of content as the priority, and there’s an intention to lean on available technology to support that.

Using advanced technology, AI especially, responsibly matters for shaping the future while staying accountable. Howard flagged the real risk of losing control when working with AI tools, since they can’t be held accountable for their own output. He also noted the advantage frameworks like the DMBoK have here, since their flexibility around content control helps sidestep legal complications. The suggestion, to actually harness AI well, is to limit its role to validation and consistency checks rather than letting it generate additional content on its own.

Howard stressed how much it matters to actually understand a tool before using it well, since some tools carry real risk while others are perfectly safe. One attendee shared they’d had genuinely insightful conversations with Claude, whom they now think of almost as a colleague, and said the experience gave them a fresh way of talking about data quality concepts, new terminology for expressing ideas they already had.