Extracting scientifically accurate terminology from an EU public health regulation is part of the knowledge engineering work at the European Centre for Disease Prevention and Control (ECDC). ECDC operates information systems at the crossroads of many areas - posing a challenge for transparency and consistency. Semantic interoperability is based on the Terminology Server (TS). TS value sets (structured vocabularies) describe shared domains as "diseases", "organisms", "public health terms", "geo-entities" "organizations" and "administrative terms" and others. We extracted information from the relevant EC Implementing Decision on case definitions for reporting communicable diseases, listing 53 notifiable infectious diseases, containing clinical, diagnostic, laboratory and epidemiological criteria. We performed a consistency check; a simplification - abstraction; we represented lab criteria in triplets: as 'y' procedural result /of 'x' organism-substance/on 'z' specimen and identified negations. The resulting new case definition value set represents the various formalized criteria, meanwhile the existing disease value set has been extended, new signs and symptoms were added. New organisms enriched the organism value set. Other new categories have been added to the public health value set, as transmission modes; substances; specimens and procedures. We identified problem areas, as (a) some classification error(s); (b) inconsistent granularity of conditions; (c) seemingly nonsense criteria, medical trivialities; (d) possible logical errors, (e) seemingly factual errors that might be phrasing errors. We think our hypothesis regarding room for possible improvements is valid: there are some open issues and a further improved legal text might lead to more precise epidemiologic data collection. It has to be noted that formal representation for automatic classification of cases was out of scope, such a task would require other formalism, as e.g. those used by rule-based decision support systems.