Chapter 3: Analyzing Indian Science and Technology Indicators Using Data Science: A Global Perspective

An upsurge in evidence-based policy formulation has led to profound roadmap formulation and effective policy formulation internationally. Significantly, the prevalent national practices in the R&D policy formulation demands painstaking analysis and accountability in investments. Although diverse methodology trends extend feasibility to derive inferences from the figurative assessments of the investments, overall economy and salient growth reports, it is crucial to contemplate the direct and indirect influence of numbers in an eclectic landscape. Mainly, the science, technology, and innovation (STI) indicators are extensively being used to comprehend the evolution of R&D activities. Quantitative science and technology (S&T) data analysis provides valuable and strategic insights for effective policy formulation with effective assimilation of S&T activities, which otherwise is a complex and dreary affair. This paper deliberates on a “Scientometric” approach with deep data science analytics to analyze Indian indicators in consonance with national objectives and vision. We present a detailed analysis of the Indian S&T indicators derived from the published data by credible International/federal agencies compared to the global R&D statistics. The latter part is aimed to curl out the Indian GDP and S&T indicators' pattern and infer the non-quantifiable insights (derived from the dominant indicators) to highlight the effectiveness of the government plans. Since figurative indicators fail to capture process and grey zones, we summarize the salient points that merit attention for robust planning and evaluating socio-economic progress in the Indian context. We focus on contributing towards the indispensable R&D policy foundation, considering a broader, global socio-economic canvas.