Liaison between projects is all too often preempted by methodological issues. So when some communication is needed alternatives should not be limited to no models at all or a medley of ambiguous ones.
Archetypal Development Models
Software engineering processes can be regrouped in two categories: phased ones are segmented with regard to responsibilities, tasks and the nature of artifacts, agile ones are iterative, with a single team sharing responsibilities for the definition, building and acceptance of final outcomes.
With regard to modeling languages, both approaches may encounter parochial pitfalls: tasked teams of phased projects may go through turf wars and misunderstandings, agile teams could tend to autarkic biases and objections to models.
Stories Must Be Set in Context
Agile projects start right away with writing users’ stories into software, making no use of intermediate development artifacts other than code. With business analysts and software engineers working side by side, the semantics of business objects and activities is meant to be directly, if progressively, inscribed into software artifacts.
Nonetheless, users’ stories, being by nature specific, are to be set against the broader context of enterprise business objectives. Teams may therefore have to communicate with outside entities and, considering that source code is seldom the preferred language of other units, agile teams may have to resort to means they would otherwise disparage. They would be in a better position if stories could be docked to open concepts to be used to contrive messages in line with projects’ needs and creeds.
Developments Must be Shared
Paraphrasing Einstein, the only reason for phased processes is so that everything doesn’t happen at once. In that case intermediate artifacts are to be introduced between tasks. But then, suppliers and customers, often from different backgrounds and with different concerns, have to agree about the semantics of the development flows. Moreover, the accuracy and consistency of agreed upon definitions must stand the test of time whatever the changes on each side.
As illustrated by model based software engineering processes, that objective is essentially attainable for programming languages; otherwise blurred footprints and ambivalent semantics require cumbersome maintenance of transformation rules as well as regressive updates of previous versions of the artifacts. In that case open concepts may help to prevent the corruption of a core of sound specifications by surroundings ambiguous ones.
Open Concepts: Yet Another Conceptual Framework ?
As many will have noticed, there is no lack of frameworks, conceptual or otherwise. So what could be the point of yet another one ?
The answer, as it should be, is to be found in its impact on the use, or reuse, of artifacts by projects and teams, whatever their preferred development model. And that’s why the open source paradigm applied to open concepts is critical:
- The difference between generalization and specialization is fully taken into account so that the semantics of sub-types defined by different projects cannot be modified.
- The concept of Individuals is used to guarantee that business objects and activities are consistently identified across projects.
- The semantics of sub-types are consistently, but not necessarily uniformly, defined across projects.
- There is no overlapping of semantics even when subsets of individuals overlap.
Those are very strong constraints which, combined with the already limited footprint of open concepts, will result in a very compact set of concepts. When implemented with ontologies ensuring interoperability with models, that is to make the difference: a small set of concepts, built from well-known principles, with clear properties and benefits, to be shared by projects independently of their modeling languages and development methods.
- Thread: Project Management
- Open Concepts
- Conceptual Thesaurus
- Open Concepts Will Make You Free
- Thread: Agile
- UML & Users’ Concerns
- UML Semantic Master Key
- From Stories to Models
- Agile Business Analysis: From Wonders to Logic
- Agile & Models
- Open Ontologies: From Silos to Architectures
- Ontologies & Enterprise Architecture,
- Systems, Information, Knowledge
- Knowledge Architecture
- Ontologies & Models
- Enterprise Governance & Knowledge
- Data Mining & Requirements Analysis
- Ontologies as Productive Assets
- Caminao Ontological Kernel (Protégé/OWL 2)
- Focus: Individuals in Models