# Cooperative Approaches to Data Sharing and Analysis for Industrial Internet of Things Ecosystems
## 4 Findings  
The following section presents the consolidated results of the interviews and the four evaluation workshops. They form and fill the concept of Figure 5, which also shows the identified macro building blocks. The left-hand side includes building blocks for specifying how a data cooperative is embedded into an IIoT business ecosystem (macro view), namely the _goal of the cooperative, roles the cooperative and the members_ assume, as well as their _fundamental services and the service interplay_, including a catalog of IIoT analytics services. The right-hand side shows building blocks that organize the internal structure of the cooperative (micro view), namely the specification of the _IIoT analytics solutions_, _IT and data governance_, the _accounting and pricing system_, and _measures to ensure trust_. \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt}} \hline
**Interview Series 1** & **Interview Series 2** \\
**with Existing Business Networks** & **with Experts in Data Sharing \& Analysis** \\ \hline CO1 Cooperative in the context of a large winery & DS1 Logistics and supply chain with object tracking and analysis \\ \hline CO2 Cooperative in the trade of bedding supplies & DS2 Streaming IoT data for analysis, fishing industry \\ \hline CO3 Cooperative in the context of bakeries & DS3 Analytics infrastructure for device coordination; drone hospital deliveries initiative \\ \hline CO4 Cooperative in the context of energy distribution & DS4 Floor planning for smart factories \\ \hline CO5 Cooperative in the context of supra-regional banking and finance & DS5 Optimizing plastic injection molding machines \\ \hline CO6 Cooperative in context of agar products and services & DS6 Port traffic management \\ \hline CO7 Cooperative in the context of open-source software development & DS7 Port traffic management \\ \hline CO8 Cooperative in the context of regional banking & DS8 Data analysis for smart factories and smart logistics in retail \\ \hline CO9 Cooperative in the context of regional banking & \\ \hline CO10 Cooperative in the context of regional banking & \\ \hline CO11 Cooperative in the context of regional banking & \\ \hline CO12 Cooperative in the context of logging and forest management & \\ \hline CO13 Cooperative in the context of wood wholesale & \\ \hline CO14 Cooperative in the context of specialized consulting & \\ \hline \end{tabular} Note: Due to the COVID-19 pandemic, all interviews of the second series were conducted in a virtual setting.  
\end{table} 
Table 1: Overview of the two interview series. Figure 5: Concept of a data cooperative and its building blocks. We consider these to be of specific relevance for data cooperatives, and therefore an answer to our second research question. Notably, each of these blocks comes with a set of sub-components for which we identify various design alternatives. Both interview series support the assumption that a cooperative can facilitate the sustainable provision of joint services based on shared resources, directed at a joint value proposition. First, a cooperative can act as a neutral and trustworthy intermediary that is obligated to work in the interests of the ecosystem (CO14). Second, by formally fixing the rights and responsibilities of the members, it provides an extrinsic obligation to cooperate (CO6, CO10, CO13). In fact, in the shared port management initiative discussed in DS6, the lack of a respective binding agreement with clear roles, rights, and responsibilities, as well as the absence of a central entity for enforcing them, were deemed to be the main reasons for the limited success of the solution. Despite being beneficial for all partners, most did not contribute their data even after agreeing informally to do so during project initiation. Third, as a cooperative has its own legal identity, it is capable of coordinating external suppliers and/or customers, which is crucial for resource pooling and sharing.