Jordan A. Comins

Compressing multiple scales of impact detection by Reference Publication Year Spectroscopy

Reference Publication Year Spectroscopy (RPYS) is a scientometric technique that effectively reveals punctuated peaks of historical scientific impact on a specified research field or technology. In many cases, a seminal discovery serves as the driving force underlying any given peak. Importantly, the results from a RPYS analyses are represented on their own distinct scales, the bounds of which vary considerably across analyses. This makes comparing years of punctuated impact across multiple RPYS analyses problematic. In this paper, we propose a data transformation and visualization technique that resolves this challenge. Specifically, using a rank-order normalization procedure, we compress the results of multiple RPYS analyses into a single, consistent rank scale that clearly highlights years of punctuated impact across RPYS analyses. We suggest that rank transformation increases the effectiveness of this scientometric technique to reveal the scope of historical impact of seminal works by allowing researchers to simultaneously consider results from multiple RPYS analyses.

Detecting seminal research contributions to the development and use of the global positioning system by reference publication year spectroscopy

The global positioning system (GPS) represents one of the most compelling success stories of technology transfer from defense laboratories and academia to the private sector. In this short report, we applied a quantitative analysis to identify landmark research contributions to GPS. This technique, reference publication year spectroscopy (RPYS), yielded key insights into early works that allowed for both the development and widespread use of GPS. In addition, using this approach to identify individual contributions of scientific excellence offers an opportunity to credit not only the research investigators, but also their corresponding affiliations and funding sources. Indeed, the findings from our analysis suggest that RPYS might serve as a powerful tool to substantiate the contribution of funding agencies, universities and institutes to research fields. We stress, however, that this method should not stand-alone for such purposes, but should be wedded with the knowledge and experience of subject matter experts.

Citations: Indicators of Quality? The Impact Fallacy

We argue that citation is a composed indicator: short-term citations can be considered as currency at the research front, whereas long-term citations can contribute to the codification of knowledge claims into concept symbols. Knowledge claims at the research front are more likely to be transitory and are therefore problematic as indicators of quality. Citation impact studies focus on short-term citation, and therefore tend to measure not epistemic quality, but involvement in current discourses in which contributions are positioned by referencing. We explore this argument using three case studies: (1) citations of the journal Soziale Welt as an example of a venue that tends not to publish papers at a research front, unlike, for example, JACS; (2) Robert Merton as a concept symbol across theories of citation; and (3) the Multi-RPYS (“Multi-Referenced Publication Year Spectroscopy”) of the journals Scientometrics, Gene, and Soziale Welt. We show empirically that the measurement of “quality” in terms of citations can further be qualified: short-term citation currency at the research front can be distinguished from longer-term processes of incorporation and codification of knowledge claims into bodies of knowledge. The recently introduced Multi-RPYS can be used to distinguish between short-term and long-term impacts.

RPYS i/o: software demonstration of a web-based tool for the historiography and visualization of citation classics, sleeping beauties and research fronts

Reference Publication Year Spectroscopy (RPYS) and Multi-RPYS provide algorithmic approaches to reconstructing the intellectual histories of scientific fields. With this brief communication, we describe a technical advancement for developing research historiographies by introducing RPYS i/o, an online tool for performing standard RPYS and Multi-RPYS analyses interactively (at http://comins.leydesdorff.net/). The tool enables users to explore seminal works underlying a research field and to plot the influence of these seminal works over time. This suite of visualizations offers the potential to analyze and visualize the myriad of temporal dynamics of scientific influence, such as citation classics, sleeping beauties and the dynamics of research fronts. We demonstrate the features of the tool by analyzing—as an example—the references in documents published in the journal Philosophy of Science.

Citation algorithms for identifying research milestones driving biomedical innovation

Scientific activity plays a major role in innovation for biomedicine and healthcare. For instance, fundamental research on disease pathologies and mechanisms can generate potential targets for drug therapy. This co-evolution is punctuated by papers which provide new perspectives and open new domains. Despite the relationship between scientific discovery and biomedical advancement, identifying these research milestones that truly impact biomedical innovation can be difficult and is largely based solely on the opinions of subject matter experts. Here, we consider whether a new class of citation algorithms that identify seminal scientific works in a field, Reference Publication Year Spectroscopy (RPYS) and multi-RPYS, can identify the connections between innovation (e.g., therapeutic treatments) and the foundational research underlying them. Specifically, we assess whether the results of these analytic techniques converge with expert opinions on research milestones driving biomedical innovation in the treatment of Basal Cell Carcinoma. Our results show that these algorithms successfully identify the majority of milestone papers detailed by experts (Wong and Dlugosz in J Investig Dermatol 134(e1):E18–E22, 2014)—thereby validating the power of these algorithms to converge on independent opinions of seminal scientific works derived by subject matter experts. These advances offer an opportunity to identify scientific activities enabling innovation in biomedicine.

Cited references and Medical Subject Headings (MeSH) as two different knowledge representations: clustering and mappings at the paper level

For the biomedical sciences, the Medical Subject Headings (MeSH) make available a rich feature which cannot currently be merged properly with widely used citing/cited data. Here, we provide methods and routines that make MeSH terms amenable to broader usage in the study of science indicators: using Web-of-Science (WoS) data, one can generate the matrix of citing versus cited documents; using PubMed/MEDLINE data, a matrix of the citing documents versus MeSH terms can be generated analogously. The two matrices can also be reorganized into a 2-mode matrix of MeSH terms versus cited references. Using the abbreviated journal names in the references, one can, for example, address the question whether MeSH terms can be used as an alternative to WoS Subject Categories for the purpose of normalizing citation data. We explore the applicability of the routines in the case of a research program about the amyloid cascade hypothesis in Alzheimer’s disease. One conclusion is that referenced journals provide archival structures, whereas MeSH terms indicate mainly variation (including novelty) at the research front. Furthermore, we explore the option of using the citing/cited matrix for main-path analysis as a by-product of the software.

Data-Mining the Foundational Patents of Photovoltaic Materials: An Application of Patent Citation Spectroscopy

We apply Patent Citation Spectroscopy (PCS)--originally developed as Reference Publication Year Spectroscopy for studying landmarks and milestones in scientific literature--to patent literature classified into the nine Y-subclasses of the Cooperative Patent Classification (CPC) that describe material photovoltaic technologies. For this study we extended the routine with the option to use the advanced search queries at PatentsView. On the basis of two normalizations of the longitudinal distribution of the publication years of the patents cited by the retrieved patents, the routine (at this http URL) provides a best guess of the foundational patent for the subject specified in the string. In five of the nine cases, we found corroborating evidence for the foundational character of the patent indicated by the routine.

Patent citation spectroscopy (PCS): Online retrieval of landmark patents based on an algorithmic approach

Abstract One essential component in the construction of patent landscapes in biomedical research and development (R&D) is identifying the most seminal patents. Hitherto, the identification of seminal patents required subject matter experts within biomedical areas. In this article, we report an analytical method and tool, Patent Citation Spectroscopy (PCS), for the online identification of landmark patents in user-specified areas of biomedical innovation. Using USPTO data, PCS mines the cited references within large sets of patents at the internet and provides an estimate of the historically most impactful prior work. We show the efficacy of PCS in three case studies of biomedical innovation with clinical relevance: (1) RNA interference (RNAi), (2) cholesterol and (3) cloning. PCS mined and analyzed cited references related to patents on RNA interference and correctly identified the foundational patent of this technology, as independently reported by subject matter experts on RNAi intellectual property. Secondly, we apply PCS to a broad set of patents dealing with cholesterol – a case study chosen to reflect a more general, as opposed to expert, patent search query. PCS mined through cited references and identified the seminal patent as that for Lipitor, the groundbreaking medication for treating high cholesterol as well as the pair of patents underlying Repatha. The final case study, cloning, highlights some of the advantages conferred by the PCS methodology in identifying seminal patents. These cases suggest that PCS provides a useful method for identifying seminal patents in areas of biomedical innovation and therapeutics. The interactive tool is free-to-use at: http://www.leydesdorff.net/comins/pcs/index.html .

Identification of long-term concept-symbols among citations: Do common intellectual histories structure citation behavior?

“Citation classics” are not only highly cited, but also cited during several decades. We explore whether the peaks in the spectrograms generated by Reference Publication Years Spectroscopy (RPYS) indicate such long‐term impact by comparing across RPYS for subsequent time intervals. Multi‐RPYS enables us to distinguish between short‐term citation peaks at the research front that decay within 10 years versus historically constitutive (long‐term) citations that function as concept symbols. Using these constitutive citations, one is able to cluster document sets (e.g., journals) in terms of intellectually shared histories. We test this premise by clustering 40 journals in the Web of Science Category of Information and Library Science using multi‐RPYS. It follows that RPYS can not only be used for retrieving roots of sets under study (cited), but also for algorithmic historiography of the citing sets. Significant references are historically rooted symbols among other citations that function as currency.