# A Framework to Build a Big Data Ecosystem Oriented to the Collaborative Networked Organization
## 1 Introduction  
A Collaborative Networked Organization (CNO) is composed of companies and/or people in nonhomogeneous environments in terms of activities, culture, social capital and goals, independently governed and geographically distributed, where the participants share their competencies to collaboratively address a temporary or long-term common or compatible objective [1]. The goals of CNOs are: (1) to maximize the overall network profit; (2) to achieve the local objectives and develop the strategies of each member of the CNO; and (3) to withstand market fluctuations while minimizing the costs of the total network and each member of the CNO [2]. CNOs show high potential not only in terms of survival capability, but also value creation due to their ability to cope with innovation needs, uncertainty, mass customization and fierce competition [3]. It is expected that, by working together, companies can receive the following benefits: reaching (apparent) larger dimensions, through their access to new/wider markets and new knowledge; information sharing of risks and resources; creation of a collaborative environment for innovation, through the combination of synergy, competencies, culture and experiences; the smooth integration of customers in the product development and innovation process; and linking of complementary skills and capacities,which allows each entity to focus on its core competencies while retaining a high level of agility [1]. During their activities, CNOs generate and store large heterogeneous datasets [4], cataloged as big data [5]. Therefore, CNOs can increase their productivity and efficiency through a big data ecosystem, which allows them to collect, store and process data from different sources and in different formats, as well as visualize and disseminate information for decision making [6]. Building a big data ecosystem in a CNO is a technically challenging task [7] because it should offer the following capabilities: big data storage, big data processing, big data orchestration, big data assistance, big data interfacing and big data deployment [8]. In addition to this, a big data ecosystem can significantly alter the business processes of the CNO because it can lead to changes in the decision making of top management based on the insights obtained [9]. Consequently, the development and implementation of a big data ecosystem in a CNO is a very complex task that includes not only technological aspects, but also strategy, management, business process and human resources issues. To support practitioners, several frameworks have been proposed in the literature for big data ecosystems for the development and implementation of CNOs. These frameworks are mainly focused on addressing the terminology, characteristics and elements of big data ecosystems. Although, these frameworks are very interesting contributions, in their present state there are some issues that limit their effectiveness: (1) none of the existing frameworks consider all the necessary dimensions for the development of a big data ecosystem, and therefore none can provide holistic support; (2) their application is limited to a specific CNO manifestation, and therefore their scope is very restricted; (3) none consider certain important technical issues such as guides for data fusion, the combination of heterogeneous data, interoperability improvement or the selection of the appropriated big data analysis techniques; and (4) they are focused only on the technical issues of big data ecosystem development, without considering the impact on the CNO configuration, human resources and business processes. To overcome these issues, this paper proposes a new framework called the CNO-BD framework. This supports the development and implementation of a big data ecosystem in CNOs. Moreover, it takes into account the main characteristics of a big data ecosystem and avoids all the analyzed frameworks' weaknesses described above.