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Big Data (BD) is not only a quintessential part of many economic activities but also has evolved into a veritable business ecosystem. However, most Big Data ecosystem (BDE) models have a technical, bottom-up focus and mostly lack the capability for a broad socioeconomic analysis. This paper identifies the Millennium Ecosystem Assessment (MA) as a useful, operational framework and uses a metaphorical analogy to adapt it for the BDE. The top-down approach adopted here allows for seeing the big picture of the BD ecosystem. Meeting “end-user needs” is the main objective of the proposed BDE framework.

The methodology of this paper consists of two parts. First, the MA is adapted for the BDE through a metaphorical analogy. Then, to operationalize and validate the proposed framework, it is applied to an emerging BD ecosystem.

In total, four types of services are offered in the BD ecosystem: provisioning information and products; regulating; cultural and supporting services. Direct and indirect drivers of change impact ecosystem processes such as BD service provision. Based on the assessment results, interventions can be devised to remedy problems, sustain the ecosystem or accelerate growth. The proposed BDE assessment framework is applied to an emerging BDE as an example of operationalization and validation of the proposed BDE framework.

The strengths of the proposed BDE framework is that, in contrast to existing frameworks that are technical and bottom-up, it is constructed top-down by a metaphorical analogy from the proven MA framework. It is a generic framework with the ultimate objective of meeting the “end-user needs” and does not focus on a single sector or firm. Also, the proposed BDE framework is multi-faceted and considers broad socioeconomic issues such as regulating, cultural and supporting services and drivers of change.

This study aims to develop and apply a process model for prioritizing and selecting basic research projects in developing countries.

Basic research is mainly funded by governments and since, unlike technological research, it does not have clear business goals, its prioritization is one of the complicated issues in formulating science and technology policy. Adopting a design science research methodology, the authors chose a general framework for project portfolio selection as an appropriate artifact for solving this problem. By customizing it for two specific features of this study, i.e. national scale of the problem and the basic nature of research proposals, the authors developed the proposed framework for solving the problem of priority setting.

The process for selecting basic research proposals consists of several steps, which can be categorized into eight steps including strategic decisions, preparation, pre-screening, evaluating individual proposals, screening, portfolio selection and monitoring. This study emphasizes the necessity of defining goals that can be evaluated for the national basic research portfolio, as a key strategic decision. Evaluating individual proposals is a peer-review-based process. In contrast, portfolio selection is done through a zero-one linear programming model. The validity of the proposed framework has been confirmed based on the data obtained from the Iran National Science Foundation.

To the best of the authors’ knowledge, in this research, for the first time, a mathematical model for prioritizing basic research at the national level has been presented, which effectively contributes to policymaking regarding the development of an optimum national research portfolio.