# Spreadsheets as Interoperability Solution for Business Process Representation
## 2 Background and Related Works  
In the field of transforming some kind of process description into a process model, there are various research directions. In the following section, we briefly overview of these solutions. One of the existing methods is generating processes from text description. Such description can be provided in natural language [2] or in structured language. A part of the SBVR standard is SBVR Structured English [16]. There are methods of tranforming SBVR business rules into UML activity diagrams [17] (which are similar to BPMN models) or BPMN [9; 18]. Some papers consider the extended versions of SBVR, like SBPVR (Semantics of Business Process Vocabulary and Process Rules) [19] or sSBVRMM (simplified SBVR metamodel) [20]. The methods based on the natural language description have to be supported by some Natural Language Processing (NLP) system and as of today, practical applications of such methods constitutes a complex issue. In turn, translation from other representations requires models in designed using these representations, what faces practical difficulties as such models often do not exist. Another method which provides good quality models is translation from other representation. An example of transformation approach is mapping of the Unified Modeling Language (UML) use case diagrams into process models [21; 22]. UML activity diagrams can be also represented in form of logical expressions [23]. Thus, a mapping between workflow patterns and formal specification is possible. Although its purpose is mainly to extract logical specification from the process model, the set of mapping rules allows to generate a model based on a logical expression that defines relations between activities. The broad family of process model generation methods is process discovery. This is one of the process mining techniques [24], which mostly do not require any human activity. Such techniques consist in analyzing event logs from the system and extracting process structure from logs. There are many existing algorithms, mostly implemented using the ProM process mining toolkit (See: [[http://www.processmining.org/](http://www.processmining.org/)]([http://www.processmining.org/](http://www.processmining.org/))). It is important to noting that process mining discovers process models as they are in reality. Thus, if the process in reality is different than the reference model or specification, the process discovery techniques will not be able to discover a correct model. Most process mining algorithms discover Petri nets or some other simple representations. However, nowadays, with the development of algorithms and tools, there are also algorithms to mine BPMN models directly [25]. The most similar approach to ours was presented by [PERSON] and [PERSON] in [26; 27]. The authors presented three approaches for business process modeling using spreadsheets characterized by different levels of complexity:  
1. Simple approach--this solution concerns simple processes modeled only using sequences of activities. 2. Branching approach--concerns not only sequences, but also more complex flow structures. It uses such elements like successors in order to represent complex control flow, as well as gateways and events. For specifying the condition, the \"Description\" column is used. In the case of several successors, this can be realized by using a comma-separated string of row numbers as property value. 3. More Properties approach--it extends the branching approach with additional properties specified explicitly like the assigned roles, input documents, etc. Moreover, this approach allows for adding customized properties as new columns to the spreadsheet. However, they will not be presented in the model. An example of transforming a spreadsheet to a process model according to the Branching approach from [26] is presented in Table 1 and the corresponding process model in Figure 1. Rows of the table represent model flow objects.