Search Engines and Discovery Systems

“Comparing Conventional and Alternative Mechanisms of Discovering and Accessing the Scientific Literature”

This study compares the bibliographic and full-text coverage of 15 conventional and alternative discovery/access mechanisms: two multidisciplinary library databases (Scopus and the Web of Science Core Collection), five single-subject databases, the integrated library search (ILS) mechanism of Manhattan University, a scholarly search engine (Google Scholar), two web-based scholarly databases (Dimensions and OpenAlex), two academic social networks (Academia.edu and ResearchGate), and two pirate sites (Anna’s Archive and Sci-Hub). The analysis is based on known-item searches for 875 target documents in chemistry, materials science, cardiology, public health, economics, education, and psychology. Overall, Google Scholar, OpenAlex, and the ILS are the most comprehensive sources of bibliographic records. Google Scholar’s coverage rate is higher than that of all the Manhattan University databases combined, and Scopus—the most comprehensive multidisciplinary library database—has a lower bibliographic coverage rate than Google Scholar, both of the web-based scholarly databases, one of the two ASNs, and one of the two pirate sites. In terms of full-text coverage, the best multidisciplinary options are the ILS, Google Scholar, and the two pirate sites. Although several of the alternative discovery/access mechanisms are deficient in terms of their user interfaces, search capabilities, and metadata, they nonetheless provide excellent bibliographic and full-text coverage of the scholarly literature. In contrast, many single-subject library databases provide very incomplete coverage of their own subject areas. These findings have implications for scholars and students as well as system-wide implications for the use, development, and evaluation of information resources.

https://www.pnas.org/doi/10.1073/pnas.2503051122

“Data Discovery using LLMs &emdash; A Study of Data User Behaviour”

Data search for scientific research is more complex than a simple web search. The emergence of large language models (LLMs) and their applicability for scientific tasks offers new opportunities for researchers who are looking for data, e.g., to freely express their data needs instead of fitting them into restrictions of data catalogues and portals. However, this also creates uncertainty about whether LLMs are suitable for this task. To answer this question, we conducted a user study with 32 researchers. We qualitatively and quantitively analysed participants’ information interaction behaviour while searching for data using LLMs in two data search tasks, one in which we prompted the LLM to behave as a persona. We found that participants interact with LLMs in natural language, but LLMs remain a tool for them rather than an equal conversational partner. This changes slightly when the LLM is prompted to behave as a persona, but the prompting only affects participants’ user experience when they are already experienced in LLM use.

https://arxiv.org/abs/2507.04444

Paywall: “AI and Systematic Reviews: Can AI Tools Replace Librarians in the Systematic Search Process?”

Focusing on the search stage of the systematic review process, the author examines the features and viability of select AI-based tools, evaluates their integration into existing systematic review workflows, and addresses issues related to transparency, reproducibility, and trustworthiness. The study also assesses whether these AI tools can be effectively and reliably incorporated into systematic review processes and discusses the evolving roles and responsibilities of librarians in using these technologies.

https://doi.org/10.1080/0194262X.2025.2521519

“From Building a First-Generation Digital Library Infrastructure to Reimagining Discovery”

Twenty-five years ago, Harvard University was in the early stages of a project to build a first-generation digital library infrastructure. The project was carefully named the Library Digital Initiative (LDI), signifying that ‘digital’ would be an integral and integrated aspect of ‘library’ and not a separate entity. The initiative aimed to develop knowledge and expertise relating to digital objects, as well as technical infrastructure to create, curate, access and preserve them, and to integrate the new digital collections with Harvard’s extensive tangible collections.

Today, we still benefit from the foresight of this first-generation development and the subsequent ones it spawned, but we are also at a pivotal point of reflecting on lessons learned and opportunities to be seized as we rebuild and reimagine our digital infrastructure and services in a vastly expanded data ecosystem. Predicting what libraries will look like two decades ahead is always conjecture. What we do know, however, is that while the themes and challenges from the past two decades endure, the way we are tackling them is different. This paper examines what has changed since early library digital initiatives, and the imperatives we see for the future.

https://doi.org/10.2218/ijdc.v19i1.1068

“Prospects of Retrieval Augmented Generation (RAG) for Academic Library Search and Retrieval”

This paper examines the integration of retrieval-augmented generation (RAG) systems within academic library environments, focusing on their potential to transform traditional search and retrieval mechanisms. RAG combines the natural language understanding capabilities of large language models with structured retrieval from verified knowledge bases, offering a novel approach to academic information discovery. The study analyzes the technical requirements for implementing RAG in library systems, including embedding pipelines, vector databases, and middleware architecture for integration with existing library infrastructure. We explore how RAG systems can enhance search precision through semantic indexing, real-time query processing, and contextual understanding while maintaining compliance with data privacy and copyright regulations. The research highlights RAG’s ability to improve user experience through personalized research assistance, conversational interfaces, and multimodal content integration. Critical considerations including ethical implications, copyright compliance, and system transparency are addressed. Our findings indicate that while RAG presents significant opportunities for advancing academic library services, successful implementation requires careful attention to technical architecture, data protection, and user trust. The study concludes that RAG integration holds promise for revolutionizing academic library services while emphasizing the need for continued research in areas of scalability, ethical compliance, and cost-effective implementation.

https://tinyurl.com/43d97fe5

“Clarivate Commits to ERIC, the World’s Most Widely Used Index of Education-Related Literature”

In response to customer feedback and widespread concern from libraries regarding the future of ERIC, Clarivate is launching the free ProQuest Education Research Index, which includes ERIC data. ProQuest Education Research Index includes ERIC alongside ProQuest Supplemental Education Index, a newly created index that covers the majority of scholarly journals currently indexed by ERIC. It is designed to ensure continued coverage of as many ERIC-indexed titles as possible and will grow over time.

The combined solution provides librarians, researchers and faculty with continued access to over two million bibliographic records of journal articles and other education-related materials, including research reports, curriculum and teaching guides, conference papers and books.

https://tinyurl.com/hf3zexet

From ERIC Index Coverage Reduction: Information & FAQ:

If you are not yet a ProQuest customer, please contact rachel.kessler@clarivate.com to request that an account be setup for you.

“Assessing the Performance of 8 AI Chatbots in Bibliographic Reference Retrieval: Grok and Deepseek Outperform ChatGPT, but None Are Fully Accurate”

This study analyzes the performance of eight generative artificial intelligence chatbots — ChatGPT, Claude, Copilot, DeepSeek, Gemini, Grok, Le Chat, and Perplexity — in their free versions, in the task of generating academic bibliographic references within the university context. A total of 400 references were evaluated across the five major areas of knowledge (Health, Engineering, Experimental Sciences, Social Sciences, and Humanities), based on a standardized prompt. Each reference was assessed according to five key components (authorship, year, title, source, and location), along with document type, publication age, and error count. The results show that only 26.5% of the references were fully correct, 33.8% partially correct, and 39.8% were either erroneous or entirely fabricated. Grok and DeepSeek stood out as the only chatbots that did not generate false references, while Copilot, Perplexity, and Claude exhibited the highest hallucination rates. Furthermore, the chatbots showed a greater tendency to generate book references over journal articles, although the latter had a significantly higher fabrication rate. A high degree of overlap was also detected among the sources provided by several models, particularly between DeepSeek, Grok, Gemini, and ChatGPT. These findings reveal structural limitations in current AI models, highlight the risks of uncritical use by students, and underscore the need to strengthen information and critical literacy regarding the use of AI tools in higher education.

https://arxiv.org/abs/2505.18059

“The Role of Online Search Platforms in Scientific Diffusion”

After the launch of Google Scholar older papers experienced an increase in their citations, a finding consistent with a reduction in search costs and introduction of ranking algorithms. I employ this observation to examine how recombination of science takes place in the era of online search platforms. The findings show that as papers become more discoverable, their knowledge is diffused beyond their own broad field. Results are mixed when examining knowledge diffusion within the same field. The results contribute to the ongoing debate of narrowing of science. While there might a general reduction in recombination of knowledge across distant fields over the last decades, online search platforms are not the culprits.

https://doi.org/10.1002/asi.24959

“Consensus: Using AI to Analyze Scientific Literature”

Consensus is an artificial intelligence–driven research assistant that helps users quickly discover the scientific consensus on research questions. It offers tools and options to help users further explore what the research says about topics of interest to them, pulling mainly from the Semantic Scholar database. Consensus performs best when users ask questions that can be answered with either yes or no. Its strength is in covering scientific research, while its coverage of social science or humanities topics is much more limited. This review looks at how Consensus works, issues related to searching, and other information that might help librarians decide whether to recommend Consensus to patrons.

https://dx.doi.org/10.1353/lib.2025.a961198

“OpenAlex now available on DSpace”

In partnership with the University of Cambridge, 4Science has enhanced interoperability in DSpace for a richer repository and better data quality: OpenAlex now available on DSpace! . . .

OpenAlex is an innovative platform that offers free access to millions of scientific publications, researchers, institutions, and academic sources. The integration simplifies and speeds up the entry of publications and other entities. This ensures a repository that is always up-to-date and comprehensive. By using the existing live import features, users will be able to import items complete with metadata both from MyDSpace and through the suggestions dedicated to those accessing the platform and administrators.

The import from external sources, accessible through MyDSpace, allows for direct searching in the OpenAlex database integrates the selected results into DSpace, automatically pre-filling the submission form with the imported metadata. The entities supported by the integration are Publications, Journals, People, and Organizational Units, providing advanced and more comprehensive content management.

https://librarytechnology.org/pr/31378

“Deep Dive into Three AI Academic Search Tools”

Web of Science Research Assistant offers high interpretability. It displays the generated Boolean query, and the search results are consistent with the standard Web of Science relevance ranking. . . . Reproducibility is medium. . . .

Primo Research Assistant offers medium interpretability. The initial Boolean generation is somewhat transparent, but the. . . reranking step makes the rest of the process opaque. Reproducibility is medium. . . .

Scopus AI has low interpretability. While a Boolean query is constructed and shown, the hybrid approach. . . makes it hard to understand why specific results are returned. Reproducibility is also very low. . . .

https://tinyurl.com/566cfv3w

“Enhancing Library Discovery: An Approach to Understanding User Access to Electronic Resources”

The exponential increase in electronic resources in parallel with the development of discovery systems has expanded the research environment for library users well beyond the traditional library catalog. In response, a large public university library grapples with the best ways to deploy research tools to provide access to the many electronic resources it licenses for its users. Library staff seek to direct users most efficiently to needed resources, to save staff time, and to contain costs. The authors used a variety of methods to gather data to support their decision making, including search log analysis, surveys of other institutions, interviews with students, and cross-departmental discussion within the institution. The library made improvements to the website and search tool interfaces as well as developed a new approach to loading MARC records for electronic resources to the library catalog, which resulted in a slimmed down catalog paired with a newly promoted discovery system. This analysis is intended to inspire other libraries to develop a more deliberate approach to providing access to electronic resources.

https://doi.org/10.1016/j.acalib.2025.103064

“Guest Post: Eight Hypotheses Why Librarians Don’t Like Retrieval Augmented Generation (RAG)”

Content providers are starting to silo their collections in order to restrict other RAG-based tools from accessing their content.

An example: in the case of Primo Research Assistant, collections from APA (and others such as Elsevier and JSTOR) are excluded from result generation. This would need to be explained to students and faculty using the tool, which adds considerably to the time and energy put into the communication needed to make these tools worth their licensing cost. It can reasonably be assumed that almost all content providers are going to invest in their own AI assistants or make licensing deals with existing ones. How many of these can and should we license and maintain? Librarians working on discovery layers should start making plans now for identifying the tools that best serve their community and how their workflows need to change.

https://tinyurl.com/2fe6hdnw

“Wiley and Perplexity Announce New AI Search Partnership”

This new collaboration will allow Perplexity users, including college students, educators and researchers at institutions that subscribe to Perplexity’s Enterprise Pro to access purchased Wiley educational collections and resources in areas such as nursing, business, and engineering. This includes streamlined access to specialized Wiley collections, giving users a new pathway to discover and interact with authoritative resources across many academic domains. Students will also gain tools for responsible AI usage, reinforcing Wiley’s commitment to supporting academic integrity. . . .

Perplexity provides live web access and Wiley collections content with sourced citations, ensuring users receive up-to-date information with proper attribution. Students, educators, and researchers can get answers sourced across Wiley and web sources, combining the authoritative nature of Wiley with the most recent developments from the web.

Among the pilot users of this new offering are Texas A&M and Texas State University, with several universities in the United Kingdom poised to start soon.

https://tinyurl.com/yc8xy5cf

“Wiley Announces Collaboration With Amazon Web Services (AWS) to Integrate Scientific Content into Life Sciences AI Agents”

The new Wiley literature search agent is available as part of an open source toolkit for healthcare and life sciences agents that has been assembled by AWS. The toolkit offers a catalog of starter agents and an orchestration framework for organizations to build and customize their agentic systems, supporting use cases from biomarker discovery to clinical trial protocol generation. The new AI agent currently includes AI searchable access to articles under the creative commons license, such as Cancer Medicine, delivering reliable and cited insights in minutes rather than the current hours- to days-long manual process of discovering and perusing dozens of articles for relevant information.

https://tinyurl.com/mr6t8fu2

Paywall: “AI-Integrated Literature Discovery Tools: A Guide to Reviewing for Institution Wide Use”

[The article] analyzes how AI-enabled tools are altering the ways researchers interact with scholarly literature, providing new approaches for discovery, analysis, and synthesis. The article outlines the advantages and limitations of various AI-integrated platforms. . . . The study offers insights into the evaluation and implementation of AI literature review tools within academic institutions. . . .

https://doi.org/10.1080/1941126X.2025.2497736

“Suspiciously Reliable: A Case Study of Students’ Perceptions of Open Access Searching”

This case study examines how undergraduate students perceive the search infrastructure involved in open access searching and the open access materials’ content. Thirty students across two semesters of a second-year library science course were given a research topic but asked to imagine themselves as lacking access to the university’s subscriptions—meaning they could only access open access content through search engines such as Google Scholar, repositories, and the Directory of Open Access Journals. They were then asked to complete a research log, an annotated bibliography, and a reflection paper. In reviewing their reflection papers, a dualistic theme of both valuing and distrusting open access research was identified. Most students felt it necessary to apply more rigorous evaluation to the content found through open access databases and even evaluated the databases themselves. Despite this and other reservations, many students commented on the value of open access, especially when it pertained to the free and open exchange of information. Based on this study, we have adapted the way we speak about open access in the classroom to preemptively address some of the concerns noted in the reflections. This case study can add to the body of literature that examines the value of introducing open access to students.

https://doi.org/10.31274/jlsc.18273

“Geographical and Disciplinary Coverage of Open Access Journals: OpenAlex, Scopus, and WoS”

This study aims to compare the geographical and disciplinary coverage of OA journals in three databases: OpenAlex, Scopus and the Web of Science (WoS). We used the Directory of Open Access Scholarly Resources (ROAD), provided by the ISSN International Centre, as a reference to identify OA active journals (as of May 2024). Among the 62,701 active OA journals listed in ROAD, the WoS indexes 6,157 journals, Scopus indexes 7,351, while OpenAlex indexes 34,217. A striking observation is the presence of 24,976 OA journals exclusively in OpenAlex, whereas only 182 journals are exclusively present in the WoS and 373 in Scopus. The geographical analysis focuses on two levels: continents and countries. As for disciplinary comparison, we use the ten disciplinary levels of the ROAD database. Moreover, our findings reveal a similarity in OA journal coverage between the WoS and Scopus. However, while OpenAlex offers better inclusivity and indexing, it is not without biases. The WoS and Scopus predictably favor journals from Europe, North America and Oceania. Although OpenAlex presents a much more balanced indexing, certain regions and countries remain relatively underrepresented. Typically, Africa is proportionally as under-represented in OpenAlex as it is in Scopus, and some emerging countries are proportionally less represented in OpenAlex than in the WoS and Scopus. These results underscore a marked similarity in OA journal indexing between WoS and Scopus, while OpenAlex aligns more closely with the distribution observed in the ROAD database, although it also exhibits some representational biases.

https://doi.org/10.1371/journal.pone.0320347

“Evaluating AI Language Models for Reference Services: A Comparative Study of ChatGPT, Gemini, and Copilot”

The descriptive statistics indicate that Google Gemini outperformed the other GenAI chatbots, by scoring high on “accuracy,” relevancy,” “friendliness” and “instruction” resulting in a higher mean score followed by public ChatGPT, commercial ChatGPT-4.0, and Microsoft Copilot.

https://doi.org/10.1080/10875301.2025.2478861

“Elsevier Launches ScienceDirect AI to Transform Research with Rapid Mission-Critical Insights from Trusted Content”

Researchers grapple with an ever-growing and overwhelming volume of information and need to quickly get accurate insights they can rely on. Studies show that they spend 25%-35% of their time sifting through literature. ScienceDirect AI helps address this challenge by drawing on the broadest and deepest content set of millions of peer-reviewed full-text research articles and book chapters to generate instant accurate summaries and highlight key findings, while providing references to support reproducibility and integrity of research.

https://tinyurl.com/2s3m2hwp

“Elsevier’s Pre-proof Policy Blocks Google Scholar Indexing”

Google Scholar is a vital tool for engineering scholars, enabling efficient literature searches and facilitating academic dissemination. Elsevier, as one of the largest publishers of engineering journals, produces essential research that scholars rely on. The pre-proof policy, adopted by Elsevier for certain journals, allows articles to be published online in their accepted draft form before final proofreading and formatting. However, this study empirically demonstrates that the pre-proof publication policy hinders comprehensive indexing by Google Scholar. Articles published under this policy are only partially indexed, often limited to titles and abstracts, while crucial sections such as introductions, methods, results, discussions, conclusions, appendices, and data availability statements remain unsearchable. This problem has persisted for years, resulting in reduced visibility and accessibility of certain Elsevier articles. To improve academic dissemination, both Elsevier and Google Scholar must address this problem by modifying publishing policies or enhancing indexing practices. Additionally, this paper explores strategies that authors can use to mitigate the issue and ensure broader discoverability of their research.

https://arxiv.org/abs/2503.05550

Ex Libris: “Summon Research Assistant Is Now Live”

Summon Research Assistant is a new AI-enhanced discovery tool that saves researchers time by summarizing the query response and citing the most relevant resources. Users will benefit from detailed, natural language search capabilities to uncover trusted library materials. Summon Research Assistant only offers content that is vetted by libraries and the Ex Libris via the Central Discovery Index. Searching the Summon Research Assistant generates in real-time a topical overview based on information from the CDI. The most significant resources are cited in the summary, enabling researchers to instantly view context. From here they can elect to explore more results, refine their original query, or pursue a suggested related research question.

https://tinyurl.com/43ast26b

“Opinion: A Librarian’s Summary Of, and Response to, the Clarivate Announcement”

Furthermore, the transition to subscription-only access represents more than a change in purchasing models – it fundamentally undermines the ability of academic libraries to build collections that serve their specific institutional needs. . . . As the existing ProQuest One collections have demonstrated (causing great frustration), content can be removed without library input or prior announcement. Clarivate states: “We will continue our bi-annual schedule of title removals from subscriptions in June and December. There may be occasional off-cycle removals due to legal reasons or loss of publisher rights.” . . . The loss of Evidence-Based Acquisition (EBA) and Demand-Driven Acquisition (DDA) is also likely to be another blow to institutions whose budgets do not allow for the up-front purchase of all texts on lists.

https://tinyurl.com/4wy3eyc9

“Academic Databases and the Art of the Overcharge”

To help libraries avoid price discrimination, we gathered research library pricing for three popular academic databases: SciFinder from Chemical Abstract Services (a division of the American Chemical Society); Scopus from Elsevier; and Clarivate’s Web of Science. . . .

Using this data, we will examine a selection of pricing that demonstrates the range of prices paid by libraries and compare pricing across different institutional factors. We will conclude with tips on how to use pricing data in your library’s next negotiation.

https://tinyurl.com/ycyyyhuf

Paywall: “OA Journals in Subscription-Based Full-Text Databases in 2024: An Analysis of EBSCO’s Academic Search Complete”

Two sets of samples from all the 3,481 peer-reviewed non-embargoed full-text journals in ASC were examined. One set is 10% random samples, and the other set is journals from major publishers excluding gold OA publishers. Both sets have similar results that over 70% are OA journals.

https://tinyurl.com/4t8u25yy

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