Analyzing and Assessing a Library Collection Using Faculty Citations Via OpenAlex and R

With the primary goal of exploring whether citation analysis using scientific papers found on the Web as a data source is a worthwhile means of studying scholarly communication in the new digital environment, the present case study examines the scholarly communication patterns in XML research revealed by citation analysis of ResearchIndex data and SCI data. Results suggest that citation analysis using scientific papers found on the Web as a data source has both advantages and disadvantages when compared with citation analysis of SCI data, but is nonetheless a valid method for evaluating scholarly contributions and for studying the intellectual structure in XML research.

This investigation seeks to study the publication and citation activity of faculty at research universities, as defined by membership in the Association of Research Libraries (ARL). It constitutes the fourth iteration in a study of publishing behaviors, conducted over more than twenty years. The present data indicate a substantial rise in publications, both in total and as measured on a per capita basis. These data are compared with those of the previous three studies. In addition, and for the first time, citation data are also examined. The reason for the addition of citations is that there is cause to believe that citations are becoming common evaluative criteria for individuals, academic programs, and departments. There are implications for academic libraries with regard to all these data.

Event Abstract Back to Event Neuroimaging Data Access and Query through a Common Application Programming Interface B. Nolan Nichols1*, Christian Haselgrove2, Jean-Baptiste Poline3 and Satrajit S. Ghosh4 1 Integrated Brain Imaging Center, University of Washington, Seattle, WA, United States 2 University of Massachusetts Medical School, Worcester, MA, United States 3 Neurospin-I2BM-CEA, Gif sur Yvette, France 4 McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, United States A large number of databases are developed to store and manage human neuroimaging data. While individual neuroscience databases provide mechanisms to query and download information within a given framework (e.g., Allen Institute, COINS, HID, IDA, LORIS, NIMS, XNAT), there is no standardized way to programmatically access related information stored in these heterogeneous systems. Creating a data exchange layer with a common interface to access and query shared brain imaging data will enable the development of interoperable client applications capable of consuming resources available across disparate brain imaging data management systems. We present a preliminary application programming interface (API) for providing uniform access to neuroimaging databases. Conceptually, the API is a service for accessing common entities (e.g., project, subject) and their relationships (e.g., subject wasAssociatedWith project) specified by the XCEDE data model [1] and defined in a lexicon [2]. Neuroimaging databases conforming to the API implement a mapping of their local resources to XCEDE entities and provide a mechanism to request resources. The API is not tied to a specific language or technology, but for web-accessible databases, REST is a natural fit. For example, a REST implementation of the API would respond to an HTTP request for a Subject URI (e.g., www.example.com/xcede_query/subject?uri={uri}) by listing the relationship and URI of related entiies (e.g, {wasAssociatedWith: projectURI} ). The response to an API request can return XCEDE XML or another format (e.g., JSON, RDF) conforming to the XCEDE data model [1]. Discussions with the developers of many neuroimaging databases are helping to refine this specification, and existing tools will speed the first implementation of the API [3]. Our goal is that in the near future, existing databases and those under development will implement this protocol and expose existing and newly acquired datasets in a common data access framework. This work was conducted with the Neuroimaging Task Force of the INCF Program on Standards for Datasharing.

Hospital adoption of API-enabled patient data access

Providing access to observational climate data and its metadata has been important for climatology. Historically, climate data has been made available by some national data platforms or through the European Climate Assessment and Database (ECA&D). Users often had to pay for data access and output was provided in different formats. The newly in force EU open Data Directive 2019/1024 requires National Meteorological and Hydrological Services (NMHSs) to make their High Value Datasets, including meteorological datasets, available through machine readable application programming interfaces (APIs). RODEO work package 5 (WP5) aims to unite ten NMHSs that are developing APIs for their climate databases. Afterwards, an API aggregator service unifies the individual APIs, so that the clients can use all APIs with only one request.  In this presentation we will report on progress made in RODEO WP5.   WP5 worked on uniforming climate datasets, including its metadata. A group of experts decided on the choice of variable to include, granularity of daily and hourly observations, and preferred controlled vocabularies. Metadata guidance from WMO, Copernicus and ESIP are incorporated to adhere to the FAIR principles.  The API recommendations for NMHS data providers will follow the Environmental Data Retrieval (EDR) API specification. Using an EDR API it is possible to perform geospatial and temporal filterable queries of climate data. The EDR specification, published by Open Geospatial Consortium (OGC) in 2016, has, over recent years, gained traction as an ideal method to distribute meteorological data over the internet.   The OGC has adopted CoverageJSON as data format standard alongside the EDR API. This format will be the preferred output format for an NMHS climate data API.  The EDR aggregator service will facilitate the unification of individual NMHS APIs to one central EDR API. The aggregator service can add caching, output format conversion from CoverageJSON to NetCDF or CSV and support queries across collections.  To aid in the development of NMHS climate data EDR APIs, a workshop “Build an EDR API in a day” is being prepared to run in June 2024. A spin-off of this event is being planned in Spring 2025 for non-RODEO partners. 

Increased pace of Application Programming interfaces (APIs) and third party data feeds have altered the game of cyber threat intelligence, by facilitating automated data exchange and situational awareness. Nevertheless, such external data sources have new vulnerabilities because of the inconsistent quality, unchecked authenticity, and different levels of trustworthiness. Conventional one-dimensional risk appraisals are not usually effective in capturing interchangeable character of threat posed by current data being consumed, leading to incomplete or obsolete security knowledge bases. This paper suggests a risk scoring system that is dynamical to determine the security and reliability of third-party data feeds and APIs in a threat intelligence system. The framework constantly changes risk scores by combining machine learning classifiers, feature detection based on API request metadata, and variable weighting of key risk factors to adapt to changing risk conditions. The validation of the methodology occurs in simulated enterprise settings whereby numerous API feeds are consumed, evaluated and compared with the benchmark of fixed mode models. The findings reveal that dynamic risk scoring methodology enhances much higher predictive accuracy, responsiveness, and operational relevance of cyber threat intelligence dashboards. The study is significant to cybersecurity practice because it provides a model that organizations can use to determine which sources of threat data to prioritize, reduce exposure and increase resilience, which is scalable and adjustable.

A Web-Based Perioperative Dashboard as a Platform for Anesthesia Informatics Innovation.

The results of a survey on evidence-based surgery (EBS) among members of the American Academy of Orthopedic Surgeons (AAOS) and the British Orthopaedic Association (BOA) are presented. The study also analyzes the citations earned by articles with different levels of evidence (LOE) to see if LOE have any bearing on the importance attached to the articles by authors and contributors to the journals. The questionnaire was e-mailed to 1000 randomly chosen consultant orthopaedic surgeons who were members of either the AAOS or the BOA. Participants were provided with the option of responding through web-based entry. For citation analysis, citation data were gathered from the Journal of Bone and Joint Surgery (American volume) between the years 2003 and 2007 (5-year period). The survey showed that awareness and access to EBS have improved greatly over the years. At the present time, these factors are not important barriers to the implementation of EBS in clinical practice in developed countries. There was a statistically significant difference in those with and without additional qualifications with regard to the approach to EBS. However, an equal percentage of surgeons with and without additional qualifications felt that it was difficult to adhere to EBS guidelines in daily clinical practice. Citation analysis showed that readers of professional journals attach importance to LOE category of the article and tend to cite level-I evidence articles more than other articles.

The updated version of the International Association of Dental Traumatology (IADT) guidelines was published online in May 2020 in the form of four papers. They are extensively used in dental trauma education in textbooks, undergraduate and postgraduate programs, and clinical workshops. Hence, this study aimed to assess the impact, global scientific reach, and utilization of these guidelines through altmetric and citation analysis. The protocol was prepared after an expert group discussion. Dimensions database was used to derive the altmetric and citation data on April 10th, 2023. The data was extracted by using a self-designed pre-piloted form by two authors independently. The citing articles were further categorized into the type of study and the domains and subdomains of dental traumatology. The VOSviewer program was utilized to explore the correlation between the subdomains and the overlap of citations was assessed by creating a citation matrix. A total of 552 citations had been collectively received by the four papers. The highest was seen for the guidelines for fracture and luxation in permanent teeth (FL), avulsion in permanent teeth (AV), general introduction (GI), and primary teeth (PT). Dental Traumatology had the maximum number of citing papers for each guideline. They were from 52 countries with English being the commonest language. Overall, the maximum number of citations had been received in narrative reviews (n = 104) and the majority of cited papers were categorized in the therapeutic domains. The most common subdomain for the papers that cited GI, FL, and AV was "treatment protocols in permanent teeth", while it was "awareness of prevention and emergency management of traumatic dental injuries" for the papers that had cited PT. This analysis highlighted that the IADT 2020 guidelines are globally popular resources, which are widely used by the researchers across specialities and are intended towards clinical application.

Expectations and patterns of publication have changed markedly with evolving online availability and associated development of new citation gathering databases. Perhaps the most vulnerable components of the scientific literature to ongoing change are books and book chapters, given their elongated publication timelines and generally more limited online availability. To test this, we applied citation analyses and assessments of library holdings to determine the use of the natural history books published by Surrey Beatty & Sons between 1987 and 2010. We (i) evaluated the relative use of book chapters and journal papers by comparing citations to chapters in the five books of the Nature Conservation series by Surrey Beatty & Sons to citations of journal chapters in four Australian journals published in the same years, (ii) determined the efficacy of four different databases in retrieving citations to book chapters by comparing their recovery of citations to the five books of the Nature Conservation series, and (iii) quantified noncitation measures related to library holdings to evaluate the use of the books on the entire Surrey Beatty & Sons list. Mean citations/chapter to the first three books in the Nature Conservation series were similar to the mean citations/ paper in four Australian journals published in the same years. However, the mean citations/chapter of the last two books declined relative to citations/paper for the journals, suggesting a fall in book use evident by early this century. Citation retrieval varied across databases; Google Scholar retrieved most citations, followed by Scopus, Web of Science (Cited Reference Search) and Web of Knowledge. Contrary to published concerns, no citations retrieved by Google Scholar were in questionable sources such as contents pages - many were from highly ranked journals. Each book in the full Surrey Beatty & Sons list was held by an average of 45.3 libraries in Australia and 36.1 in the USA, and less than five in each of the UK, New Zealand, Hong Kong, Canada, Germany and South Africa. This was a similar coverage to another Australian publisher, the Royal Zoological Society of New South Wales, and indicated strong markets in Australia and the USA. It was less, though, than the number of libraries with current or past subscriptions to five Australian journals publishing nature conservation content. We conclude that citation data for books and book chapters are available and that library holdings provide another measure of use. The online ‘visibility’ of books may be a problem, but can be improved through better marketing and improved author search techniques.

Neuroscientists routinely perform experiments aimed at recording or manipulating neural activity, uncovering physiological processes underlying brain function or elucidating aspects of brain anatomy. Understanding how the brain generates behaviour ultimately depends on merging the results of these experiments into a unified picture of brain anatomy and function. Brain atlases are crucial in this endeavour: by outlining the organization of brain regions they provide a reference upon which our understanding of brain function can be anchored. More recently, digital high-resolution 3d atlases have been produced for several model organisms providing an invaluable resource for the research community. Effective use of these atlases depends on the availability of an application programming interface (API) that enables researchers to develop software to access and query atlas data. However, while some atlases come with an API, these are generally specific for individual atlases, and this hinders the development and adoption of open-source neuroanatomy software. The BrainGlobe atlas API (BG-Atlas API) overcomes this problem by providing a common interface for programmers to download and process data across a variety of model organisms. By adopting the BG-Atlas API, software can then be developed agnostic to the atlas, increasing adoption and interoperability of packages in neuroscience and enabling direct integration of different experimental modalities and even comparisons across model organisms.

A new object-oriented interface to MDSplus

The core of blockchain smart contracts is the execution of business logic code in a decentralized architecture with all executing nodes trusting and agreeing on the results. Smart contracts are unable to get data from the outside world on their own. Smart contracts communicate with oracles, which are off-chain data sources whose primary function is to collect and give data feeds to smart contracts. The usage of oracle returns the blockchain to its centralization problem and also exposes the blockchain to the possibility of introducing corrupt, malicious and erroneous data. This problem is called ‘Oracle problem’. This paper presents an investigation of this problem. To demonstrate this, we have considered the price oracle problem using chainlink’s decentralized network of nodes that connects off-chain data to on-chain smart contracts through oracles. Finally, we performed an analysis and comparison on retrieving external off-chain data through external APIs (Application Programming Interfaces) and through decentralized oracles. This would be helpful in determining how decentralization (through oracles) may result in performance constraints in contrast to fetching data through our own built APIs where data source APIs of blockchain are not connected to the decentralized nodes of network. The results have shown the increase in transaction throughput of the overall system.

Marketing scholars increasingly use web scraping and application programming interfaces (APIs) to collect data from the internet. Yet, despite the widespread use of such web data, the idiosyncratic and sometimes insidious challenges in its collection have received limited attention. How can researchers ensure that the data sets generated via web scraping and APIs are valid? While existing resources emphasize technical details of extracting web data, the authors propose a novel methodological framework focused on enhancing its validity. In particular, the framework highlights how addressing validity concerns requires the joint consideration of idiosyncratic technical and legal/ethical questions along the three stages of collecting web data: selecting data sources, designing the data collection, and extracting the data. The authors further review more than 300 articles using web data published in the top five marketing journals and offer a typology of how web data have advanced marketing thought. The article concludes with directions for future research to identify promising web data sources and embrace novel approaches for using web data to capture and describe evolving marketplace realities.

The explosion in availability and variety of data requires learning experiences that reveal more of the data world faster and develop practical skills with digital technologies. Key high‐level goals of the International Data Science in Schools Project (IDSSP) include having students continually immersed in the cycle of learning from data, and data science being fun to teach and fun to learn. We advocate curiosity‐driven, exploratory learning for pursuing these goals. Our illustrations use tasks embedded in contexts that teenagers can relate to, provide visual rewards for computational actions, use rich data‐contexts, and integrate statistical and computational thinking. They provide engaging introductions to modern data sourced from databases via Application Programming Interfaces (APIs) that are accessible to a broad range of students and facilitate student personalization for investigation. We provide in‐depth discussion of teaching strategies that heavily involve questioning and student tinkering supported by graphical‐user interfaces that enable students to interact with the data sources rapidly in multiple ways.