# Collaborative Networks: A Pillar of Digital Transformation
## 7 Discussion of New Research Challenges
#### 3.3.1.1 Smartness and data-richness  
* **Dealing with data-rich environments*
* _Context_: An important vector of the digital transformation are the fast-increasing volumes of data resulting from the large usage of sensors and smart objects/smart devices, as well as the hyper-connectivity of people, organizations, and (smart) systems. These new data-rich environments enable better decision-making and the development of systems but also challenge the collaborative networks design and management. Since previous frameworks were constrained by data scarcity, existing models need to be reconsidered, possibly giving birth to new system architectures, principles, mechanisms, and processes. _Further research_: Developing new \"collaborative business services\" that reveal and explore the value of \"data-rich environments\" and \"big data\" as well as new decision-making support mechanisms. A vast array of sub-topics become relevant here, including:
* Adoption of proper data analytics and machine-learning tools. * Value of data and ownership. * Traceability and transparency along the whole value chain and whole lifecycle of products/services. * Cybersecurity and data protection in collaborative environments. * Facing increasing uncertainties, fake data/data quality, and complexity. * **Further development of the smartness and sensing dimensions** _Context_: Innovative products, processes, infrastructures, organizations, and business communities are increasingly being designed to be \"sensing, smart, and sustainable (S3)\", i.e., further extending the notion of the \"S3 enterprise\" [66]. Inter-connected smart devices and sensor networks enable new levels of context awareness. Increased computational power, combined with the application of learning algorithms to data-rich environments, allows the smartness and self-adaptability and evolutionary capabilities of systems, components, and products (smart products) to be increased, giving rise to a combination of distributed intelligence with CNs. _Further research_: Developing cognitive collaborative networks with evolving capabilities. In other words, leveraging the capabilities of AI and machine learning to bring collaborative systems to a form of collective intelligence and shared situation awareness (a form of what is called \"distributed cognition\" in cognitive sciences). Through learning, such systems shall be able to not only acquire new knowledge, but also adapt to changing environments, which is particularly relevant to contexts of market turbulence. * **Further exploitation of open \"linked data\" and interlinking of open ontologies** _Context_: As the availability of heterogeneous data and knowledge sources increases in hyper-connected contexts, interlinking those data and that knowledge is important to enhance collaboration among participating actors in industry environments. Such interlinking is crucial namely in the context of the vertical and horizontal integration dimensions. _Further research_: Experiment and assess methods for \"open linked data\", visualization techniques, and collaborative interlinking of and refinement of ontologies. _New business models and strategies_  
**New collaborative business models:**  
_Context_: Synergies created by the convergence of multiple technologies involved in Industry 4.0 and related digital transformation are triggering and inspiring new value co-creation mechanisms and collaborative business models. Organizations (public, private, or hybrid) are challenged to redesign their strategies, their collaboration rules, and processes, as well as their interactions with the surrounding environment (e.g., with the regulatory systems). _Further research_: Developing and evaluating new collaborative business models considering new organizational structures and the possibilities offered by new technologies. Examples of associated topics include:  
* Keeping a radar on emerging business models and experiences and assessment of lessons learned.