Library Help: Office For Open Research

Understanding research classification 

Research outputs are classified in different ways across platforms, helping to organise scholarly work and identify trends. These classification systems range from broad subject categories to fine-grained topics, and are useful for analysis, benchmarking, and strategic decision-making.

Major classification systems 
 

Web of Science categories 

• Hierarchical structure with 254 subject categories

• Based on journal-level classification

• Supports disciplinary analysis at both broad and narrow levels

• Particularly useful for evaluating traditional subject areas
   

OpenAlex Research Topics 

• Uses machine learning to classify research

• Based on concepts, not journal categories

• Offers multiple classification levels

• More granular and flexible than traditional systems

• Supports cross-disciplinary discovery and trend analysis
   

ANZSRC Fields of Research (FoR)

• Developed by the Australian Bureau of Statistics and Statistics New Zealand

• Uses a hierarchical code system (2-, 4-, and 6-digit codes)

• Widely used in research assessment and funding

• Valuable for international benchmarking

• University of Manchester outputs are classified under ANZSRC in Altmetric Explorer and SciVal platforms 

SciVal Topics and Topic Clusters 

SciVal offers a dynamic classification system using citation and textual analysis to identify research topics and broader themes.

SciVal Topics (~94,000)

• Smallest unit of analysis

• Defined using citation patterns and natural language processing

• Continuously updated to reflect emerging areas

• Each topic includes a group of papers sharing closely related themes

Topic Clusters (~1,500)

• Groups of related Topics

• Provide a higher-level view of research fields

• Useful for spotting strategic trends and thematic overlaps

👉 Read Elsevier's guide to Topics and Topic Clusters
 

Additional Features in SciVal

• Topic Prominence
  Measures momentum in a topic using a mix of citations and usage metrics—helpful for identifying "hot" or emerging areas.

• Keyphrase Analysis
  Powered by Elsevier’s Fingerprint technology, this extracts key concepts from entities like Topics or institutions. Visualisations (e.g., word clouds) are available to support interpretation.

Practical Applications

You can use these classification systems to:

• Inform research strategy
  Identify emerging fields, monitor topic growth, and detect underexplored areas.

• Find collaboration opportunities
  Spot leading institutions, map collaboration networks, and discover interdisciplinary connections.

The Research Indicators team can help you navigate these systems and create custom reports and visualisations to support strategic planning.

👉 We’ve successfully used SciVal Topic Clusters to map research across AI and health equity—identifying researchers across different schools with overlapping interests.

Important limitations to consider

While classification systems and topic analyses are powerful tools, it's important to be aware of their limitations:

• Methodological differences: Each platform uses different algorithms and data sources. The same publication may be classified differently depending on the system used.

• Automated categorisation: Many systems (like OpenAlex and SciVal Topics) use machine learning, which can introduce classification errors or misrepresent interdisciplinary work.

• Journal-based biases: Systems that rely on journal categories (e.g. Web of Science) may overlook or misclassify research published in multidisciplinary or newer venues.

• Granularity and overlap: Some topics may be overly broad or narrowly defined, while others may overlap—making comparisons across systems challenging.

• Data access and updates: Not all platforms are open-access, and some update classification schemes more frequently than others.

These systems are best used as complementary tools—not definitive labels. Our team can help interpret them appropriately within your context.

Need support?

Contact us to learn more about research classification tools or request tailored topic analyses and collaboration maps.