On February 28, 2019, the University of California (UC) announced that it would not renew its subscriptions to Elsevier journals. UC is a public research university in California, USA, with 10 campuses across the state.

Researcher responses to the survey on the Swedish Elsevier cancellation

Introduction

Folder structure

data

documentation

experiments

How to run the benchmarks?

Requirements

Scopus API usage

License

This dataset contains links to ThermoML files, which represent experimental thermophysical and thermochemical property data reported in the corresponding articles published by major journals in the field. These files are posted here through cooperation between the Thermodynamics Research Center (TRC) at the National Institute of Standards and Technology (NIST) and Elsevier. The ThermoML files corresponding to articles in the journals are available here with permission of the journal publishers.

Background This bibliometric analysis examines the top 50 most-cited articles on COVID-19 complications, offering insights into the multifaceted impact of the virus. Since its emergence in Wuhan in December 2019, COVID-19 has evolved into a global health crisis, with over 770 million confirmed cases and 6.9 million deaths as of September 2023. Initially recognized as a respiratory illness causing pneumonia and ARDS, its diverse complications extend to cardiovascular, gastrointestinal, renal, hematological, neurological, endocrinological, ophthalmological, hepatobiliary, and dermatological systems. Methods Identifying the top 50 articles from a pool of 5940 in Scopus, the analysis spans November 2019 to July 2021, employing terms related to COVID-19 and complications. Rigorous review criteria excluded non-relevant studies, basic science research, and animal models. The authors independently reviewed articles, considering factors like title, citations, publication year, journal, impact factor, authors, study details, and patient demographics. Results The focus is primarily on 2020 publications (96%), with all articles being open-access. Leading journals include The Lancet, NEJM, and JAMA, with prominent contributions from Internal Medicine (46.9%) and Pulmonary Medicine (14.5%). China played a major role (34.9%), followed by France and Belgium. Clinical features were the primary study topic (68%), often utilizing retrospective designs (24%). Among 22,477 patients analyzed, 54.8% were male, with the most common age group being 26–65 years (63.2%). Complications affected 13.9% of patients, with a recovery rate of 57.8%. Conclusion Analyzing these top-cited articles offers clinicians and researchers a comprehensive, timely understanding of influential COVID-19 literature. This approach uncovers attributes contributing to high citations and provides authors with valuable insights for crafting impactful research. As a strategic tool, this analysis facilitates staying updated and making meaningful contributions to the dynamic field of COVID-19 research. Methods A bibliometric analysis of the most cited articles about COVID-19 complications was conducted in July 2021 using all journals indexed in Elsevier’s Scopus and Thomas Reuter’s Web of Science from November 1, 2019 to July 1, 2021. All journals were selected for inclusion regardless of country of origin, language, medical speciality, or electronic availability of articles or abstracts. The terms were combined as follows: (“COVID-19” OR “COVID19” OR “SARS-COV-2” OR “SARSCOV2” OR “SARS 2” OR “Novel coronavirus” OR “2019-nCov” OR “Coronavirus”) AND (“Complication” OR “Long Term Complication” OR “Post-Intensive Care Syndrome” OR “Venous Thromboembolism” OR “Acute Kidney Injury” OR “Acute Liver Injury” OR “Post COVID-19 Syndrome” OR “Acute Cardiac Injury” OR “Cardiac Arrest” OR “Stroke” OR “Embolism” OR “Septic Shock” OR “Disseminated Intravascular Coagulation” OR “Secondary Infection” OR “Blood Clots” OR “Cytokine Release Syndrome” OR “Paediatric Inflammatory Multisystem Syndrome” OR “Vaccine Induced Thrombosis with Thrombocytopenia Syndrome” OR “Aspergillosis” OR “Mucormycosis” OR “Autoimmune Thrombocytopenia Anaemia” OR “Immune Thrombocytopenia” OR “Subacute Thyroiditis” OR “Acute Respiratory Failure” OR “Acute Respiratory Distress Syndrome” OR “Pneumonia” OR “Subcutaneous Emphysema” OR “Pneumothorax” OR “Pneumomediastinum” OR “Encephalopathy” OR “Pancreatitis” OR “Chronic Fatigue” OR “Rhabdomyolysis” OR “Neurologic Complication” OR “Cardiovascular Complications” OR “Psychiatric Complication” OR “Respiratory Complication” OR “Cardiac Complication” OR “Vascular Complication” OR “Renal Complication” OR “Gastrointestinal Complication” OR “Haematological Complication” OR “Hepatobiliary Complication” OR “Musculoskeletal Complication” OR “Genitourinary Complication” OR “Otorhinolaryngology Complication” OR “Dermatological Complication” OR “Paediatric Complication” OR “Geriatric Complication” OR “Pregnancy Complication”) in the Title, Abstract or Keyword. A total of 5940 articles were accessed, of which the top 50 most cited articles about COVID-19 and Complications of COVID-19 were selected through Scopus. Each article was reviewed for its appropriateness for inclusion. The articles were independently reviewed by three researchers (JRP, MAM and TS) (Table 1). Differences in opinion with regard to article inclusion were resolved by consensus. The inclusion criteria specified articles that were focused on COVID-19 and Complications of COVID-19. Articles were excluded if they did not relate to COVID-19 and or complications of COVID-19, Basic Science Research and studies using animal models or phantoms. Review articles, Viewpoints, Guidelines, Perspectives and Meta-analysis were also excluded from the top 50 most-cited articles (Table 1). The top 50 most-cited articles were compiled in a single database and the relevant data was extracted. The database included: Article Title, Scopus Citations, Year of Publication, Journal, Journal Impact Factor, Authors, Number of Authors, Department Affiliation, Number of Institutions, Country of Origin, Study Topic, Study Design, Sample Size, Open Access, Non-Original Articles, Patient/Participants Age, Gender, Symptoms, Signs, Co-morbidities, Complications, Imaging Modalities Used and outcome.

The United Nations Sustainable Development Goals (SDGs) challenge the global community to build a world where no one is left behind.

Since 2018, Elsevier has generated SDG search queries to help researchers and institutions track and demonstrate progress toward the SDG targets. In the past 5 years, these queries, along with the university’s own data and evidence supporting progress and contributions to the particular SDG outside of research-based metrics, are used for the THE Impact Rankings.

For 2023, the SDGs use the exact same search query and ML algorithm as the Elsevier 2022 SDG mappings, with only minor modifications to five SDGs, namely SDG 1, 4, 5, 7 and 14. In these cases, the queries were shortened by removing exclusion lists based on journal identifiers. These exclusion lists often contained thousands of items to filter out content in journals that were not core to the SDGs.

To replicate the effect of these journal exclusions, sets of keywords were used to closely mimic the effects the journal exclusions had on the SDG content, while greatly reducing the overall query size and complexity. By following this approach, we were able to limit the changes to the publications in each SDG by less than 2 percent for most SDGs, while reducing the query size by 50 percent or more.

These shortened queries also have the added benefit of running faster in Scopus, allowing further analysis of the SDG data to be done more easily.

For each SDG, the full search query, along with further details about the top keyphrases, subfields, journals and keyphrases are available for download.

Coliphage and adenovirus concentrations per liter. This dataset is associated with the following publication: Gassie, L., J. Englehardt, J. Wang, N. Brinkman, J. Garland, P. Gardinali, and T. Guo. Mineralizing urban net-zero water treatment: Phase II field results and design recommendations. WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 105: 496-506, (2016).

Dataset of the research paper: Machine Learning for Software Engineering: A Tertiary Study

Machine learning (ML) techniques increase the effectiveness of software engineering (SE) lifecycle activities. We systematically collected, quality-assessed, summarized, and categorized 83 reviews in ML for SE published between 2009–2022, covering 6,117 primary studies. The SE areas most tackled with ML are software quality and testing, while human-centered areas appear more challenging for ML. We propose a number of ML for SE research challenges and actions including: conducting further empirical validation and industrial studies on ML; reconsidering deficient SE methods; documenting and automating data collection and pipeline processes; reexamining how industrial practitioners distribute their proprietary data; and implementing incremental ML approaches.

The following data and source files are included.

review-protocol.md: The protocol employed in this tertiary study

data/

dl-search/

input/

acm_comput_surveys_overviews.bib: Surveys of ACM Computing Surveys journal

acm_comput_surveys_overviews_titles.txt: Titles of surveys

acm_comput_ml_surveys.bib: Machine learning (ML)-related surveys of ACM Computing Surveys journal

acm_comput_ml_surveys_titles.txt: Titles of ML-related surveys

dl_search_queries.txt: Search queries applied to IEEE Xplore, ACM Digital Library, and Elsevier Scopus

ml_keywords.txt: ML-related keywords extracted from ML-related survey titles and used in the search queries

se_keywords.txt: Software Engineering (SE)-related keywords derived from the 15 SWEBOK Knowledge Areas (KAs—except for Computing Foundations, Mathematical Foundations, and Engineering Foundations) and used in the search queries

secondary_studies_keywords.txt: Survey-related keywords composed of the 15 keywords introduced in the tertiary study on SLRs in SE by Kitchenham et al. (2010), and the survey titles, and used in the search queries

output/

acm/

acm{1–9}.bib: Search results from ACM Digital Library

ieee.csv: Search results from IEEE Xplore

scopus_analyze_year.csv: Yearly distribution of ML and SE documents extracted from Scopus's Analyze search results page

scopus.csv: Search results from Scopus

study-selection/

backward_snowballing.csv: Additional secondary studies found through the backward snowballing process

backward_snowballing_references.csv: References of quality-accepted secondary studies

cohen_kappa_agreement.csv: Inter-rater reliability of reviewers in study selection

dl_search_results.csv: Aggregated search results of all three digital libraries

forward_snowballing_reviewer_{1,2}.csv: Divided forward snowballing citations of quality-accepted studies assessed by reviewer 1 and 2, correspondingly, based on IC/EC

study_selection_reviewer_{1,2}.csv: Divided search results assessed by reviewer 1 and 2, correspondingly, based on IC/EC

quality-assessment/

dare_assessment.csv: Quality assessment (QA) of selected secondary studies based on the Database of Abstracts of Reviews of Effects (DARE) criteria by York University, Centre for Reviews and Dissemination

quality_accepted_studies.csv: Details of quality-accepted studies

studies_for_review.bib: Bibliography details and QA scores of selected secondary studies

data-extraction/

further_research.csv: Recommendations for further research of quality-accepted studies

further_research_general.csv: The complete list of associated studies for each general recommendation

knowledge_areas.csv: Classification of quality-accepted studies using the SWEBOK KAs and subareas

ml_techniques.csv: Classification of the quality-accepted studies based on a four-axis ML classification scheme, along with extracted ML techniques employed in the studies

primary_studies.csv: Details of reviewed primary studies by the quality-accepted secondary

research_methods.csv: Citations of the research methods employed by the quality-accepted studies

research_types_methods.csv: Research types and methods employed by the quality-accepted studies

src/

data-analysis.ipynb: Analysis of data extraction results (data preprocessing, top authors and institutions, study types, yearly distribution of publishers, QA scores, and SWEBOK KAs) and creation of all figures included in the study

scopus-year-analysis.ipynb: Yearly distribution of ML and SE publications retrieved from Elsevier Scopus

study-selection-preprocessing.ipynb: Processing of digital library search results to conduct the inter-rater reliability estimation and study selection process

The global market for literature review tools is experiencing robust growth, driven by the increasing demand for efficient research methodologies across academia, corporations, and the public sector. The shift towards digital research workflows, coupled with the rising volume of published literature, necessitates sophisticated tools for managing, analyzing, and synthesizing information. Cloud-based solutions are gaining significant traction due to their accessibility, scalability, and collaborative features. While on-premise solutions retain a market share, particularly in organizations with stringent data security requirements, the trend clearly favors cloud adoption. Key players like Clarivate, Elsevier, and Digital Science dominate the market with established products like EndNote, Mendeley, and ReadCube respectively, but a competitive landscape also includes numerous niche players catering to specific research needs, such as Rayyan for systematic reviews or MAXQDA for qualitative analysis. The market is segmented by application (academic, corporate, public sector) and type (cloud-based, on-premise), allowing for targeted product development and market penetration strategies. Geographic distribution reveals North America and Europe as the leading regions, followed by Asia Pacific, with significant growth potential in emerging markets as research infrastructure improves and digital literacy expands. We project a CAGR of 15% for the period 2025-2033, leading to substantial market expansion. The restraints on market growth primarily involve factors such as the high cost of premium features in some tools, the learning curve associated with mastering complex software, and concerns regarding data privacy and security, particularly with cloud-based solutions. However, ongoing product innovation, including the integration of AI-powered features for literature discovery and analysis, is mitigating these limitations and driving market expansion. Furthermore, the increasing emphasis on evidence-based decision-making across various sectors fuels demand for tools facilitating efficient and rigorous literature reviews. The ongoing development of open-source alternatives also introduces a competitive dynamic, fostering innovation and affordability within the market. This dynamic interplay of technological advancements, evolving research practices, and competitive pressures positions the literature review tools market for continued growth and diversification throughout the forecast period.

The global language editing services market is experiencing robust growth, driven by the increasing volume of academic publications, a rising demand for high-quality research across various fields, and the expanding globalization of scientific collaborations. The market's size in 2025 is estimated to be $2.5 billion, reflecting a significant increase from previous years. This expansion is fueled by the ever-increasing need for researchers and authors to ensure their manuscripts meet the stringent language and stylistic requirements of international journals and publishers. Key trends include the growing adoption of technology-driven solutions such as AI-powered editing tools and the increasing demand for specialized services catering to specific subject areas like medicine, engineering, and social sciences. Competitive pressures are driving service providers to offer competitive pricing, faster turnaround times, and improved quality control measures. The market is highly fragmented, with numerous players ranging from large established companies like Elsevier and Wiley to smaller specialized providers. Continued growth is projected throughout the forecast period (2025-2033), with a Compound Annual Growth Rate (CAGR) estimated at 8%. This sustained expansion is anticipated due to factors such as increasing research funding, growing awareness of the importance of professional language editing, and continued globalization. However, challenges remain, including the potential for price wars, ensuring data security and confidentiality, and maintaining consistent quality standards across geographically dispersed teams. The market will likely see further consolidation, with larger companies acquiring smaller players to expand their market share and service offerings. Specialized services targeting niche markets, such as grant writing and translation services alongside editing, will likely gain increasing traction.

🇺🇸 미국 English Interview data from EPA researchers and partners involved with solutions-driven research pilots on nutrient management and wildland fire smoke. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Restricted access may be granted to authorized persons by contacting the party listed. Format: Confidential interview data contains identifiable information of interviewees, including identifiable experiences at or with EPA, position with EPA, and role within the projects studied. This dataset is associated with the following publication: Canfield, K.N., B. Hubbell, L. Rivers, B. Rodan, B. Hassett-Sipple, A. Rea, T. Gleason, A. Holder, C. Berg, C.D. Chatelain, S. Coefield, B. Schmidt, and B. McCaughey. Lessons learned and recommendations in conducting solutions-driven environmental and public health research. JOURNAL OF ENVIRONMENTAL MANAGEMENT. Elsevier Science Ltd, New York, NY, USA, 354(March 2024): 120270, (2024).

Academic journals indicators developed from the information contained in the Scopus database (Elsevier B.V.). These indicators can be used to assess and analyze scientific domains.

Experimental Dermatology CiteScore 2024-2025 - ResearchHelpDesk - Experimental Dermatology provides a vehicle for the rapid publication of innovative and definitive reports, letters to the editor and review articles covering all aspects of experimental dermatology. Preference is given to papers of immediate importance to other investigators, either by virtue of their new methodology, experimental data or new ideas. The essential criteria for publication are clarity, experimental soundness and novelty. Letters to the editor related to published reports may also be accepted, provided that they are short and scientifically relevant to the reports mentioned, in order to provide a continuing forum for discussion. Review articles represent a state-of-the-art overview and are invited by the editors. Keywords Experimental Dermatology, EXD, dermatology, skin disease, cutaneous, immunodermatology, Abstracting and Indexing Abstracts in Anthropology (Sage) Academic Search (EBSCO Publishing) Academic Search Alumni Edition (EBSCO Publishing) Academic Search Premier (EBSCO Publishing) BIOBASE: Current Awareness in Biological Sciences (Elsevier) Current Contents: Clinical Medicine (Clarivate Analytics) Embase (Elsevier) EORTC Database (European Organisation for Research & Treatment of Cancer) InfoTrac (GALE Cengage) Journal Citation Reports/Science Edition (Clarivate Analytics) MEDLINE/PubMed (NLM) PubMed Dietary Supplement Subset (NLM) Research Alert (Clarivate Analytics) Science Citation Index (Clarivate Analytics) Science Citation Index Expanded (Clarivate Analytics)

The Intelligent System Audit Software market is experiencing robust growth, driven by increasing regulatory compliance requirements, the need for enhanced data security, and the rising adoption of cloud-based solutions across various sectors. The market, estimated at $2.5 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching an estimated $7.8 billion by 2033. Key growth drivers include the escalating complexity of IT systems, the need for proactive risk management, and the demand for automated audit processes to improve efficiency and reduce human error. The increasing adoption of AI and machine learning in audit software further fuels market expansion. Segment-wise, the cloud-based segment dominates, favored for its scalability, accessibility, and cost-effectiveness. Among applications, the corporate sector holds the largest share, followed by the public sector and academia. North America currently leads the market, driven by strong regulatory frameworks and technological advancements, but the Asia-Pacific region is poised for significant growth due to increasing digitalization and investment in IT infrastructure. Major players like Clarivate, Elsevier, and Digital Science are aggressively competing through innovation and strategic acquisitions, consolidating their market positions and driving further market expansion. The restraints include the high initial investment cost of implementing such software, the need for specialized expertise to operate these systems, and concerns around data privacy and security. The competitive landscape is dynamic, characterized by both established players and emerging startups. Established vendors are focused on expanding their product portfolios to incorporate AI-powered functionalities and enhance user experience. New entrants are disrupting the market with innovative solutions tailored to specific industry needs. The market is expected to witness increased mergers and acquisitions as companies seek to expand their reach and enhance their technological capabilities. Future growth will depend on the continued adoption of cloud-based solutions, advancements in AI and machine learning, and the evolving regulatory landscape. The integration of these audit systems with other enterprise software solutions will also drive future market expansion. Further market segmentation based on specific industry verticals will likely occur, catering to the unique audit requirements of diverse sectors.

Experiments with faster dissemination of research began in the 1960s, and in the 1990s first preprint servers emerged and became widely used in Physical Sciences and Economics. Since 2010, more than 30 new preprint servers have emerged and the number of deposited preprints has grown exponentially, with numerous journals now supporting posting of preprints and accepting preprints as submissions for journal peer review and publication. Research on preprints is, however, still scarce.

The goals of this project are: 1) Study preprint policies, submission requirements and addressing of transparency in reporting and research integrity topics of all know preprint servers that allow deposit of preprints to researchers regardless of their institutional affiliation or funding.
2) Study comments deposited on preprint servers’ platforms and social media and their relation to peer review and information exchange. 3) Study differences between preprint version(s) and version of record. 4) Living review of manuscript changes

Team Members (by first name alphabetical order):

Ana Jerončić,1 Gerben ter Riet,2,3 IJsbrand Jan Aalbersberg,4 John P.A. Ioannidis,5-9 Joseph Costello,10 Juan Pablo Alperin,11,12 Lauren A. Maggio,10 Lex Bouter,13,14 Mario Malički,5 Steve Goodman5-7

1 Department of Research in Biomedicine and Health, University of Split School of Medicine, Split, Croatia 2 Urban Vitality Centre of Expertise, Amsterdam University of Applied Sciences, Amsterdam, The Netherlands 3 Amsterdam UMC, University of Amsterdam, Department of Cardiology, Amsterdam, The Netherlands 4 Elsevier, Amsterdam, The Netherlands 5 Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA, USA 6 Department of Medicine, Stanford University School of Medicine, Stanford, California, USA 7 Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, California, USA 8 Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, California, USA 9 Department of Statistics, Stanford University School of Humanities and Sciences, Stanford, California, USA 10 Uniformed Services University of the Health Sciences, Bethesda, Maryland, USA 11 Scholarly Communications Lab, Simon Fraser University, Vancouver, British Columbia, Canada 12 School of Publishing, Simon Fraser University, Vancouver, British Columbia, Canada 13 Department of Philosophy, Faculty of Humanities, Vrije Universiteit, Amsterdam, The Netherlands 14 Amsterdam UMC, Vrije Universiteit, Department of Epidemiology and Statistics, Amsterdam, The Netherlands

EPA Draft Method C QPCR cycle threshold (Ct) measurements of standardized reference materials as described in D-EMMD-MEB-025-QAPP-01 and Journal article.

This dataset is associated with the following publication: Sivaganesan, M., T. Aw, S. Briggs, E. Dreelin, A. Aslan, S. Dorevitch, A. Shrestha, N. Isaacs, J. Kinzelman, G. Kleinheinz, R. Noble, R. Rediske, B. Scull, S. Rosenberg, B. Weberman, T. Sivy, B. Southwell, S. Siefring, K. Oshima, and R. Haugland. Standardized data quality acceptance criteria for a rapid Escherichia coli qPCR method (Draft Method C) for water quality monitoring at recreational beaches. WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 156: 456-464, (2019).

Journal of Dermatological Science Abstract & Indexing - ResearchHelpDesk - The Journal of Dermatological Science accepts online submissions only. EES is a web-based submission and review system. Authors may submit manuscripts and track their progress through the system to publication. Reviewers can download manuscripts and submit their opinions to the editor. Editors can manage the whole submission/review/revise/publish process. The Journal of Dermatological Science publishes high quality peer-reviewed manuscripts covering the entire scope of dermatology, from molecular studies to clinical investigations. Laboratory and clinical studies which provide new information will be reviewed expeditiously and published in a timely manner. The Editor and his Editorial Board especially encourage the publication of research based on a process of bilateral feedback between the clinic and the laboratory, in which incompletely understood clinical phenomena are examined in the laboratory and the knowledge thus acquired is directly reapplied in the clinic. This continuous feedback will refine and expand our understanding of both clinical and scientific domains. Although the Journal is the official organ of the Japanese Society for Investigative Dermatology, it serves as an international forum for the work of all dermatological scientists. With an internationally renowned Editorial Board, the Journal maintains high scientific standards in the evaluation and publication of manuscripts. The Journal also publishes invited reviews, commentaries, meeting announcements and book reviews. Letters to the Editor reporting new results or even negative scientific data, if they contribute to advances in dermatology are encouraged. Letters to the Editor should be less than 1000 words with up to 2 figures or tables. Abstracting and Indexing Science Citation Index Web of Science Embase BIOSIS Citation Index PubMed/Medline Abstracts on Hygiene and Communicable Diseases Elsevier BIOBASE Biological Abstracts BIOSIS Previews Chemical Abstracts Current Awareness in Biological Sciences Current Contents Embase Index Veterinarius Inpharma Weekly Medical and Surgical Dermatology PharmacoEconomics and Outcomes News Protozoological Abstracts Reactions Weekly Review of Medical and Veterinary Entomology Review of Aromatic and Medicinal Plants Review of Medical and Veterinary Mycology Sugar Industry Abstracts Veterinary Bulletin Wheat, Barley and Triticale Abstracts Abstracts of Mycology Horticultural Science Abstracts Review of Agricultural Entomology CABI Information Cancerlit Global Health Inside Conferences ISI Science Citation Index MANTIS Social SciSearch TOXFILE BIOSIS Toxicology SIIC Data Bases Elsevier BIOBASE Current Contents - Clinical Medicine Scopus

This dataset contains one of the main outputs of a series of studies on international migration among German-affiliated researchers based on Scopus bibliometric data. The migration flows are inferred from the changes of affiliation addresses in Scopus publications from 1996-2020. Scopus data is owned and maintained by Elsevier.

This dataset is provided under a CC BY-NC-SA Creative Commons v 4.0 license (Attribution-NonCommercial-ShareAlike). This means that other individuals may remix, tweak, and build upon these data non-commercially, as long as they provide citations to this data repository (https://doi.org/10.6084/m9.figshare.18433139) and the two referenced articles listed below, and license the new creations under identical terms.

For more details about the study, please refer to the following two articles.

Zhao, X., Aref, S., Zagheni, E., & Stecklov, G., Return migration of German-affiliated researchers: analyzing departure and return by gender, cohort, and discipline using Scopus bibliometric data 1996–2020. Scientometrics (2022). https://doi.org/10.1007/s11192-022-04351-4

Zhao, X., Aref, S., Zagheni, E., & Stecklov, G., International migration in academia and citation performance: An analysis of German-affiliated researchers by gender and discipline using Scopus publications 1996-2020. In: Glänzel W, Heeffer S, Chi PS, et al (eds) Proceedings of the 18th International Conference on Scientometrics and Informetrics. ISSI, Leuven, p 1369–1380, (2021) https://arxiv.org/abs/2104.12380, https://kuleuven.app.box.com/s/kdhn54ndlmwtil3s4aaxmotl9fv9s329

The dataset is provided in a comma-separated values file (.csv file). Each row represents the international movement of a Scopus-published researcher from a country (Source) to another country (Target) in a specific year (move_year). The most likely gender and the most likely discipline for each researchers is inferred using data-driven methods as described in Zhao et al. (2022).

Description of variables (columns of the csv file): "Source": the country where the researcher has moved from "Target": the country where the researcher has moved to "move_year": inferred year of the move "gender": inferred gender "discipline": inferred discipline

The binary genders inferred and used in our analysis do not refer directly to the sex of the researchers, assigned at birth or self-chosen; nor do they refer to the socially assigned or self-chosen genders of the authors.

The data can be used to produce migration models or possibly other measures, estimates, and analyses.

PurposeThe aim of this scoping review was to explore current program evaluation practices across various medical schools.MethodsWe conducted searches in MEDLINE (Ovid), Embase (Elsevier) and ERIC (ed.gov) for original research and review articles related to medical education evaluation with key words evaluation, program, medical education, pre-registration, framework, curriculum, outcomes, evaluation, quality. We followed Arksey and O’Malley’s (2005) process for scoping reviews.ResultsThirty-two articles were included. Studies were primarily concerned with either proving (n = 21) or improving efficacy of their programs (n = 11). No studies aimed at comparing programs. Nine were literature reviews. Others aimed to develop a new evaluation model (n = 7) or apply (n = 12) or validate (n = 4) an existing model (or part thereof). Twenty-two studies explicitly identified an evaluation model they had used or would recommend. Most frequently used models for evaluation were: Context-Input-Process-Product, Kirkpatrick, World Federation Medical Education, and the Standards by Joint Committee on Standards for Educational Evaluation. Overall, evaluations were learner-focused and accreditation driven with a minority considering the broader influences of program success.ConclusionProgram evaluation is fundamental to driving the quality of education delivered to produce workforce-ready healthcare professionals. The focus of current evaluations is on student experience and content delivery with a significant gap in the existing literature on evaluation related to staff, learner/staff well-being, equity, diversity, and meta evaluation.