# (R-ISSUES) Rural Interoperable System of Systems for Unified Environmental Stewardship
## 5 The R-ISSUES Model  
At this point, the authors introduce a conceptual model: \"Rural-Interoperable System of Systems for Unified Environmental Stewardship\". A concise explanation of the model is as follows:  
* It is rural because it intends to support digital rural jobs in different sites and similar businesses related to biodiversity conservation. * It is interoperable, as it uses the documented information model RSHP [62], which is compatible with formalization standards according to this reference, OWL2, and RDF, promoting semantic interoperability. * It is for a system of systems (SoS), as the model provides a common understanding of the systems engineering (SE) discipline for different coexisting organizations. Since the model aims to unify concepts along the lifecycle of environmental stewardship solutions (systems), it is represented in an ontology using a representation language for knowledge elements and relationships between those elements and attributes (such as assumptions or reasonings). This allows for semantic clusters and textual patterns (using semantic clusters) within the same knowledge base in RSHP [63]. This is remarkably interesting because the same ontology can be used for searching textual evidence within any research document, saving time, as demonstrated in [43], and, further, in the engineering lifecycle with specific systems-engineering-enabling tools [32]. It is possible to reuse this ontology by using tools compatible with the RSHP specification, with particular Application Programming Interfaces (APIs) or just by transferring the semantic relationships to own-made software or purchasing service menus because the ontology's elements presented in Table 6 are pretty intuitive. This is because the first use of ontology is to provide some semantic interoperability (and common understanding) between the researchers and the scientific and technological community. A specific use case of the R-ISSUES model's ontology is to detect research trends, providing a first set of readings for Q2 and Q4, which must be converted into textual alerts in documents obtained from search portals. Table 6 provides the terms (Concept), a short definition (Model Element), an attribute (Type of element), and a semantic cluster composed of the same keywords (for the bibliography Search Portal) and the list called Cluster extension (for Textual Alerts). After searching for research papers in the ScienceDirect(tm) portal, 154 research works were found, 48 of them under the scope and covering at least one concept. Table 7 shows the results. The authors consider the following readings as relevant \"per se\", without the need to apply a textual search inside the documents. Tables 8-10 summarize these references and remark on potential improvements for the R-ISSUES model but not specifically the questions (Q). As can be seen in Table 7, BUSINESS, CERTIFICATION, W-STORAGE, and E-STORAGE are missing concepts but also BIM OPEN DATA; nevertheless, to answer the research questions, all the documents are analysed by making use of a Natural Language Processing method, as explained in [43], and the Cluster of Table 6 for extending the Filter Clusters. Table 11 provides the composition of the textual alerts. generating readings. In the first approach, the Q2 answer is NOT IDENTIFIED YET, and Q4 is YES. Since scientific and technological production is constantly growing, it is not possible to ensure that the answers will remain true for a long time. Adding more readings to this research may also change the figures.