## 2 Literature Review
### Ontologies for Regulatory Technology
Supporting the decision-making process in pharmaceutical product development requires a systematic and integrated informatics framework based on formal and explicit modeling of related information. The utilized information models should be intelligible by both humans and software thus providing a common understanding for information sharing. Ontologies and the associated semantic technology support the smart discovery of data, the inference of data relationships, and the extraction of knowledge from enormous sets of raw data in various formats and from various sources. Despite the possible suitability of ontologies for the support of semantic data representations and modeling, there have not been many research attempts of utilizing ontologies in pharma manufacturing environments so far. [PERSON] et al. demonstrated the use of Purdue ontology for pharmaceutical engineering (POPE), for product and process development in a pharma production environment ([PERSON] et al., 2011; [PERSON] et al., 2012; [PERSON] et al., 2013). Overall, POPE is a comprehensive ontology, which fulfills to a great extent its aims, but there was no support of the POPE ontology for data integrity and furthermore, for ALCOA compliance. [PERSON] et al. (2010) tackled the regulatory compliance issue by presenting OntoReg ontology [5]. OntoReg consists of a process and a regulatory domain, and presents many similarities, concerning concepts, with the OntoCAPE [19] and POPE ontologies [20, 21, 22]. The structure of OntoReg was designed mostly based on concepts from European regulatory legislation. Extracts of this legislation were then applied to the aspirin production process to create some representative case studies, thus demonstrating the capabilities of ontological modeling and analysis of regulatory structures. OntoReg further provided the basis for RegCMatic [23], which is a methodology aiming to automate the extraction of regulatory information from relevant documents and the mapping of them to internal processes. OntoReg has been considered a noteworthy research effort towards the development of a solution offering an automated regulatory compliance validation approach in the pharmaceutical domain. Compliance management systems based on ontologies have also been proposed in domains other than the pharma manufacturing industry. The most prominent sector in the area of information technology solutions to automate regulatory compliance management is that of financial services, where the acronym RegTech was initially devised [13]. A series of major financial scandals that took place during the past few decades have, to a great extent, been attributed to violations of regulatory compliance. Similar to the pharmaceutical industry, apart from the very complex regulatory environment of financial services, there are also significant cost drivers justifying the increased interest in automated systems. Indicatively, governance, risk, and compliance costs are estimated to account for between 15 and 20% of banks' operational costs, while the cost of regulatory compliance is predicted to reach 10% of financial institutions' revenues [13]. Exemplary RegTech research efforts in the financial sector can be found in [13, 14, 24, 25, 26]. Other domains, for which RegTech ontologies have also been proposed in literature, include, but are not limited to, engineering [27, 28, 29], business process management [8, 30], business process quality [15, 31], computer security [32], as well as certification and accreditation of software intensive systems [33]. Finally, [PERSON] et al. [7, 12] have proposed a generic conceptualization for a shared understanding of a compliance regulation management process, intended to be applied to various sectors.