# Framing Algorithm-Driven Development of Sets of Objectives Using Elementary Interactions
## 4 Platform Concept
### Participant Manager  
In general, various stakeholder groups influence the development process of an MCDA system [64, 65, 22, 6]. A set of potential stakeholder groups includes decision-makers, interest groups, experts, and planners [11].  
In the case of the platform proposed, initiators are a distinct group in the MCDA application design process. The initiators define the goal of the MCDA application, and the system boundaries, and invite potential participators. They ensure all involved stakeholders are represented, i.e., that the entirety of platform users can provide specialist knowledge and preferences of the affected stakeholders at the same time. The initiators take the role of MCDA application users. The initiators are expected to know the goal of an MCDA application, know when it makes sense to develop an SOO, and know what specifications need to be given for the development of an SOO. However, the initiators need to know comparatively little about the development process itself, and the algorithms of the platform should be able to handle the process unattended. Depending on the level of sophistication of the algorithms achievable, minor manual intervention may still be essential, as was the case in the validation study (Section 5) for the definition of an objective. The idea of the platform concept, however, is that no manual interventions are required for developing an SOO after having defined a goal.  
Furthermore, end-users are a specific group that is subsumed under the term _interest group_ in the set given above. End-users can be defined as stakeholders without specialist knowledge about the assessment object, and who are impacted by an MCDA application-based decision. End-users in the context of the water infrastructure example are citizens.  
It is required to estimate the capabilities of each platform user depending on his/her role. For example, the contributions of a proven expert to the SOO elements have to be more weighted than the \"guesses\" of the end-users. Hence, an open, i.e., visible for all participants of the platform, competency model is created and maintained during the platform operation. This model is used to weigh the impact of EIs answered. For example, the more expertise a participant demonstrates, the more impact the participant's contributions will have on the SOO elements. The competency model captures domain-specific competencies and provides all required user-characterizing attributes, such as reliability. Among possible sources of the proposed competency model are:  
* Assessment results: When a user registers on the platform, an introductory test is done that assesses the technical expertise of the user regarding specific domains. The provision of an initial test has to be performed by the initiators. During the design process, the assessment of the technical expertise can be extended, e.g., by a collaborative question design tool [66].
* Self-estimation: If a user identifies him-/herself as an end-user, the initial focus of the EIs may be set on contributing to preferences.
* Reputation: In crowdsourcing systems, contributors often are assigned an attribute reputation [67], which is a measurement of the quality of their previous contributions to the system. At the same time, reputation is used to derive system permissions. An example is the Question and Answer software Stack Overflow [63]. ResearchGate is another example of a platform that assigns a reputation index to each user openly [61].