## 1 Introduction  
During the last decade, there has been some emerging networking paradigms that were announced that they will become mainstream in the future, such as Delay Tolerant Networking (DTN) or Opportunistic Networking (OppNet). Many of the use cases for them, though, are nowadays better solved by other approaches mainly based on global connectivity. Some examples of these use cases were providing connectivity in sparsely inhabited areas, in underdeveloped regions, and during disasters. However, there are still some scenarios for which flexible ad hoc communications without infrastructure require a different approach, closer to OppNets. Times have changed, and the overuse of the terms DTN and OppNet everywhere for many years has led to a current situation where these paradigms are regarded with suspicion by the research community, and even cause one to be wary of them. And yet, the need for this type of communications is still present. Perhaps it is more convenient to talk about concepts such as disruption-tolerant MANETs, multihop device to device routing in 5G, pervasive IoT, or dynamic source routing, but at the end of the day the concept of devices directly communicating with each other asynchronously using other peer devices as relays is still relevant to this day. Scenarios with these needs are, for instance, proximity-based applications, privacy-preserving communications, limited energy distance communications, or long-distance space communications, among others. For the rest of this study, we use the term OppNet to refer to this paradigm, regardless of the specific technology used to implement it. Research on routing algorithms for OppNet is very important because it provides the core element that makes this technology work. Due to the asynchronous nature of the forwarding process, selecting the right neighbor to pass messages to, choosing a good number of copies of messages, and defining for how long messages are going to live in the network are crucial aspects of opportunistic networking that are included in the routing algorithm. High-performance algorithms are produced after following a rigorous process based on the scientific method, where evaluation, comparison, and testing allow to determine the best solution for a given scenario. Unfortunately, most studies on this topic use an experimentation based on self-produced network traces, traces obtained in a particular real scenario by other researchers that have been adapted, or traces that were captured on a real network with specific constrains. Validity of results is often limited to a specific scenario or network conditions, and therefore these outcomes are often not an actual indication of the universal validity of the solution that would allow its utilization by the global community. Obviously, this is not what researchers want, and there is no hint of any bad intention here. The reason of this situation is the lack of common frameworks and objective test environments for facilitating the production of quality routing algorithms enabling the optimal application in the scenarios requiring them. To solve this problem, methodological approach is required that is based on scientific rigor. Being able to design good algorithms that do not just hold water but that can be objectively evaluated and compared to others under fair conditions is the only way to choose the best option for a particular scenario. In this study, we propose the cornerstone of this methodology: A corpus of carefully selected scenarios, accessible to the entire community, that can be used for the actual comparison and assessment of routing algorithms. This has not been an easy task. It might seem that just selecting some common, already published scenarios would suffice for this objective. However, that would be incomplete. A valid corpus has to be representative of all possible scenarios; it has to be accessible to the entire community, using a standard format; and all of its scenarios have to be comprehensive, with no missing parts that could be completed in different ways.