Clarivate report outlines practical use of societal impact data in research assessment
Clarivate has published the third report in its series on the societal impact of research, setting out how institutions can apply its Societal Impact Framework to support more responsible and reproducible analysis.
Produced by the Institute for Scientific Information (ISI), the report focuses on the practical application of the framework within Web of Science Research Intelligence. It provides guidance, examples and recommendations aimed at helping institutions and researchers make more effective use of societal impact data.
In a blog accompanying the report, Dmytro Filchenko Senior Director, Research & Analytics at the Institute for Scientific Information, explains: “Evaluating the societal impact of research poses many challenges: societal needs are diverse, there is no “one size fits all” approach, impacts often take years to emerge, and meaningful assessment requires balancing qualitative and quantitative data. These challenges make it difficult for institutions to move beyond relying on isolated metrics to using data-driven, comparable analyses that can credibly inform assessment, strategy and decision making.”
At its core, the framework is designed to balance structure with flexibility. It combines diverse, verifiable datasets from Clarivate with ISI guidance on responsible use, while allowing users to select indicators most relevant to their context. The result, according to the report, is a system capable of supporting meaningful assessment at multiple levels, from individual projects to institutions and national research systems.
A central component of the framework is its approach to categorising societal needs. By aligning with the United Nations Sustainable Development Goals (SDGs), it offers a transparent and reproducible method for linking research outputs to real-world challenges. This is achieved through the use of Citation Topics and Research Topics, which aim to capture both direct and less obvious forms of impact. While SDGs and PESTLE-based aggregation are used as defaults, institutions can apply alternative national or discipline-specific classifications.
The report also highlights the importance of careful indicator selection. Each group of indicators combines qualitative and quantitative measures, with access to underlying raw data intended to improve transparency and allow users to understand how metrics are constructed.
However, the report stresses that indicators must be interpreted in context. Absolute figures alone can be misleading, particularly when comparing institutions of different sizes or working with small or highly skewed datasets. Instead, the framework promotes the use of size-normalised data, benchmarking against national or global baselines, and an awareness of each indicator’s limitations.
To help users navigate complex datasets, the framework introduces “Societal Impact Profiles” – visual summaries of an institution’s observed and potential impact across different societal dimensions. These profiles are intended as a starting point for deeper analysis rather than definitive assessments.
As scrutiny of research value continues to increase, the report positions the Societal Impact Framework as a tool to support more transparent, contextualised and responsible evaluation practices across the sector.