Wardley Maps offer a powerful way to analyse a business's competitive landscape, value chain, and the evolution of its components — but most Enterprise Architecture frameworks have not formally incorporated them. This paper examines how Wardley Mapping complements EA methods, proposes a meta model integration using the Inspired Holistic Architecture Language (HAL), and demonstrates practical benefits including reduced effort, improved model fidelity, and richer strategic insight. A useful read for enterprise architects and business architects looking to bring greater contextual awareness into their architecture practice.
Managing Large-Scale Collaborative Modelling: Meta Model Extensions for Enterprise Architecture Tools
As enterprise architecture initiatives grow to span multiple teams, geographies, and time zones, the repositories and tools supporting them face real challenges: information overload, ownership conflicts, version management, and the need to present different views to different user communities. This paper formalises a set of meta model and meta-meta model extensions — including context, domains, filters, versioning, and scenarios — developed through real-world deployment of a collaborative EA modelling platform. The result is a more manageable, flexible, and scalable foundation for large-scale collaborative architecture work.
Cooking up a MEAL: Creating a Meta Enterprise Architecture Language
Enterprise architecture tools struggle to interoperate, and existing exchange standards like XMI are notoriously unreliable in practice. This paper proposes MEAL — a Meta Enterprise Architecture Language — a human-readable, domain-specific language designed to define, populate, query, and analyse EA models and repositories, and to serve as a high-level API between tools. It presents the requirements, a prototype implementation in Smalltalk, and example syntax demonstrating the concept's practical promise.
An Integrated Meta Model for Strategy, Business Architecture, Risk and Change
Popular enterprise architecture frameworks like TOGAF and ArchiMate each provide meta models, but none are broad enough to fully support strategic planning, contextual analysis, and business architecture alongside risk, change, and programme management in an integrated way. This paper describes the development of HAL2023 — an updated version of the Inspired Holistic Architecture Language — synthesising concepts from TOGAF 10, ArchiMate 3.2, BizBOK 11, SABSA, MEMO, and the Inspired consulting practice into a single, coherent meta model validated across multiple industries. It addresses not only what the model contains, but how it can be practically applied without overwhelming practitioners.
An Advanced Meta-Meta Model for Visual Language Design and Tooling
Most enterprise modelling tools hard-code their notations and meta models, making adaptation slow, expensive, and technically demanding. This paper presents an advanced meta-meta model — the foundational layer that governs how modelling languages and tools are defined — designed to support arbitrary meta models, multiple visual representations, multi-level modelling, and runtime adaptation without specialist programming skills. Targeting a property graph implementation, it draws on two decades of experience with the EVA toolset and a systematic review of leading platforms including Eclipse, MetaEdit+, and XModeler.
Why Modelling Notations Fail — and How to Design Visual Languages That Actually Work
Graphical models are central to enterprise architecture and information systems work, yet they frequently fail to deliver value — not because the underlying analysis is wrong, but because the notations are poorly designed, mismatched to their audience, or unable to highlight what matters. This doctoral research paper sets out a programme of design science research aimed at improving visual language design and tooling, drawing on insights from human cognition, perception, semiotics, and graphic design. It introduces polymetric diagramming as a technique for making models more expressive and proposes a meta-meta model and tool architecture to support more effective visual language design and use.