This paper attempts to define the transparency problem. The context is the changeover from a text culture to a machine culture in law. The paradigm change to electronic procedures reveals new contexts for justice. Note that equal access to e-procedures does not guarantee justice. The transparency of the law leads to the transparency of programs. We formulate two requirements for legal machines: 1) the architecture of the program must be made accessible; and 2) the program must provide legal protection. The implementation of these requirements is a subject for software engineering. A need therefore arises for the requirements to flow down to lower level specifications. In the end we define program transparency as a compliance problem.

This paper investigates an approach which is called structural legal visualization (SLV). It is about diagrammatical views which facilitate comprehension of the meaning of legal contents. Complexity reduction is a motive. An issue is the complexity of the entire legal system and the layman's limited ability to understand legal institutions and the millions of documents. A sequence of views in SLV can be compared with a narrative. SLV differs from information visualization and knowledge visualization. SLV relates to a scenario-centered graphical narrative rather than information display or user interfaces. SLV is about the generation (synthesis) of diagrams. The sequence of images depends on the user's goals. Different pathways through the informational space are concerned. With respect to an object's change or non-change, two variations of SLV are identified: dynamic SLV and static SLV. The latter is divided into two: incremental SLV and alternate focuses SLV.

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Knowledge visualization (KV) and knowledge representation (KR) are distinguished, though both are knowledge management processes. Knowledge visualization is subject to humans, whereas knowledge representation – to computers. In computing, knowledge representation leverages reasoning of software agents. Thus, KR is a branch of artificial intelligence. The subject matter of KR is representation methods. They are classified into (1) knowledge level and symbol level representations; (2) procedural and declarative representations; (3) logic-based, rule-based, frame- or object-based representations (supporting inference by inheritance); and (4) semantic networks. In legal informatics, methods of legal knowledge representation (LKR) are dealt with. An essential feature of LKR is the representation of deep knowledge, which is mainly tacit. It is easily understood by professional jurists and hardly by amateurs from outside law. This knowledge comprises the teleology of law and a whole implicit framework of legal system. The paper focuses on (1) identifying key features of KV and KR in the legal domain; and (2) distinguishing between visualization, symbolization, formalisation and mind mapping.

This paper addresses enterprise architecture (EA) compliance framework. A meth-odology to check EA non-compliance with laws and regulations is still a challenge. We think that a compliance methodology should take into account “shared” relevant laws and a requirements engineering framework. We continue discussing the view of enterprise architects on legal informatics which was proposed by Reinhard Riedl. We reflect mainly on two articles: Riedl (2011) and Čaplinskas (2009) who proposes a vision driven approach on requirements elicitation in the context of enterprise engineering.