The Growing Need for Information Analysis and Synthesis in Research

Every research project begins with a search, and almost immediately it runs into a problem: there is simply too much to read. A single query in a scholarly database can return thousands of papers, reports, patents, and datasets. Sorting the useful from the redundant has become harder than finding material in the first place. This is the core problem that information analysis and synthesis sets out to solve. Rather than dumping more documents on a researcher’s desk, these processes filter, evaluate, and reorganise knowledge into a form that can actually be used. Understanding why this need arose, and why it keeps growing, tells us a great deal about how modern research works.

The information explosion and the overload that followed 🔗

The story really begins after the Second World War. Wartime research had shown governments what concentrated scientific effort could achieve, and peacetime investment in research and development surged across the world. The result was a steep, sustained rise in published literature. Studies of long-term publication data show that, since around 1952, science has grown exponentially with an annual growth rate of roughly 5 percent and a doubling time of about 14 years. In plain terms, the volume of scholarly output keeps doubling within a generation, and that pace has not slowed.

This phenomenon acquired a name. The phrase information explosion describes the rapid increase in the amount of published information and the effects of that abundance. The term entered wide public use in the mid-1960s, and dictionaries trace its first recorded appearances to articles in 1964. The phrase captured something researchers already felt: knowledge was arriving faster than anyone could absorb it.

The trouble is that more information does not automatically mean more understanding. When the supply of documents outpaces a person’s capacity to read and process them, the result is information overload. A researcher facing tens of thousands of potentially relevant papers cannot meaningfully evaluate them all. Decisions get delayed, important findings get missed, and effort is wasted on material that turns out to be irrelevant. The explosion of literature, in other words, created its own crisis.

Why volume alone created a retrieval problem 🔗

Part of the difficulty is structural. Literature does not grow in one place. It spreads across journals, conference proceedings, technical reports, theses, patents, and increasingly across open archives and web pages. A recent commentary on scholarly publishing notes that researchers now feel both the benefits of abundant scholarly information and the downsides of information overload, and that how well a researcher can access relevant material has become a real determinant of the quality of their work. The fragmentation means that no single search, and no single source, ever gives a complete picture. The researcher has to stitch coverage together, and the gaps are easy to miss.

Why existing indexing and abstracting services were not enough 🔗

For much of the twentieth century, the standard tools for coping with this flood were indexing and abstracting services. An indexing service points you to where a document lives by listing it under subjects, authors, or keywords. An abstracting service goes a step further and provides a short summary of each document so you can decide whether it is worth reading in full. Both were genuine advances. Abstracts were introduced precisely so that researchers could get a quick sense of an article’s contents without reading the whole thing.

But these services share a fundamental limitation. They work document by document. An abstract tells you what one paper says; it does not tell you how that paper relates to the dozens of others on the same question, which findings are confirmed, which are contradicted, or where the consensus actually lies. Indexing and abstracting help you locate items, yet they leave the hardest intellectual work untouched. The researcher still has to gather everything, read it, compare it, and form a judgement.

There is also the coverage problem. No index captures everything, and the gaps tend to be worst exactly where they hurt most. Analyses of major citation databases have shown that as scientific output grew, the proportion of literature covered by a single index actually declined, with coverage especially low in fast-growing fields like computer science and engineering. A tool that misses a large and rising share of a subject cannot give a comprehensive view of it. For a researcher trying to map the state of a field, partial coverage is a serious weakness.

The gap between locating and understanding 🔗

This is the crucial distinction. Traditional services solved the problem of access: helping people find documents. They did not solve the problem of comprehension: helping people understand a body of knowledge as a whole. A researcher could end up with a perfect list of two hundred relevant articles and still be no closer to answering the actual question. Closing that gap required a different kind of service, one that processed the content rather than just pointing to it.

The push for quality, reliability, and organisation 🔗

As literature multiplied, a second concern grew alongside sheer volume: not all of it is equally trustworthy. Some studies are rigorous and some are flawed. Findings conflict. Methods vary in quality. For a researcher, a policy maker, or a clinician making a decision, raw quantity is almost worthless without an assessment of reliability. What people increasingly needed was not more information but information that had been critically evaluated and well organised.

This is where the intellectual core of the discipline comes in. Library and information science is fundamentally about identifying information needs and then evaluating, filtering, extracting, analysing, summarising, synthesising, and packaging information for decision-making. The emphasis is on judgement. Information analysis means breaking a body of material into its components and assessing each part for value, context, and reliability. Information synthesis means making connections across those parts and drawing new, coherent conclusions from them. Together they turn a pile of documents into a usable understanding.

Both activities depend on strong critical reading. Within information work, classification, abstracting, and indexing are themselves understood as evaluative tasks that require understanding the content, not just describing it. The reason this matters is practical: decisions made on poorly evaluated information are poor decisions. The demand was for material that had already been checked, compared, and judged, so that the end user could trust it.

The rise of value-added and consolidated information 🔗

The response to all of this was the development of value-added information products. Instead of handing users raw documents, information units began producing material that was selected, analysed, evaluated, and repackaged for a specific audience. This idea was formalised under the term information consolidation. A UNESCO symposium held in Colombo in 1978 defined information consolidation as the work of evaluating and compressing relevant documents to give a defined user group a reliable and concise new body of knowledge. The phrase “new body of knowledge” is important: consolidation creates something that did not exist before, not just a copy of existing documents.

The information scientist Tefko Saracevic, who worked closely with UNESCO on information problems in developing countries, described consolidated information as public knowledge that is specifically selected, analysed, evaluated, and possibly restructured and repackaged to serve the decisions and information needs of a defined group who could not otherwise access and use that knowledge efficiently. Saracevic spent much of his career on the user-derived value of information services, and this definition reflects that focus: the value lies in what the user can actually do with the result.

What value-added products look like 🔗

These products take recognisable forms. A state-of-the-art report, for example, is a review that concentrates on the most up-to-date information and literature in a given subject. Saracevic and Wood judged such reports against criteria including completeness, perspective, synthesis, value addition, and utility. The synthesis criterion measures how well information from many sources has been compacted and consolidated; the value-addition criterion measures how well the report meets the needs of subject specialists. Other examples include trend reports, evaluative reviews, and analytical briefs prepared for managers or policy makers who have no time to read the underlying literature themselves.

Formal training for this work has existed for decades. A UNESCO-linked course handbook on information consolidation set out objectives covering the analysis, synthesis, and repackaging of information into products for professionals, policy makers, technicians, and community groups. The point of all this structure is efficiency. A researcher who is handed a well-synthesised review can build on an established base quickly, rather than spending weeks reconstructing it. In an environment where literature doubles within a working career, that saved time is the whole value proposition.

Why the need keeps growing 🔗

If anything, the case for analysis and synthesis has strengthened. Traditional literature reviews that rely on manual screening have proven inadequate for handling the overwhelming influx of scientific publications driven by digital technology and the internet. Rigorous methods such as systematic reviews and meta-analyses, which formally synthesise evidence across many studies, have become central to fields like medicine precisely because no individual can read everything. The skills of analysis and synthesis are no longer a convenience. They are a condition for doing credible research at all.

This is the throughline from the post-war explosion to the present. Each stage of the problem produced a more demanding solution. Volume created overload; overload exposed the limits of indexing and abstracting; those limits raised the question of quality and reliability; and that question produced the demand for synthesised, evaluated, value-added information. The discipline did not just keep adding documents to the pile. It developed the intellectual processes needed to make the pile usable.

What do you think? When you research a topic, do you spend more effort finding sources or making sense of how they fit together? And if a future research field grows so fast that even synthesised reviews fall behind, what new kind of information product might be needed to keep knowledge usable?

References

1. https://www.nature.com/articles/s41599-021-00903-w
2. https://en.wikipedia.org/wiki/Information_explosion
3. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9291810/
4. https://link.springer.com/article/10.1007/s11192-010-0202-z
5. https://www.sciencedirect.com/topics/computer-science/library-and-information-science
6. https://ebooks.inflibnet.ac.in/lisp12/chapter/information-analysis-repackaging-and-consolidation/
7. https://ebooks.inflibnet.ac.in/lisp4/chapter/information-products/
8. https://eric.ed.gov/?id=ED296728
9. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11019984/