Motivation is of great importance in the teaching-learning process, because motivated students seek out opportunities and show interest and enthusiasm in carrying out their tasks. The objective of this review is to identify and present the information available in the literature on the status quo of motivation among nursing program entrants. This is a qualitative scoping review study, a type of literature review designed to map out and find evidence to address a specific research objective, following the Joanna Briggs Institute methodology. The objective was outlined using the PCC (Population, Concept, Context) acronym. The protocol was developed and registered on the Open Science Framework (OSF) platform under DOI 10.17605/OSF.IO/EJNGY. The search strategy and database selection were defined by a library and information science professional together with the authors. The search will be carried out in the following databases: Cumulative Index to Nursing and Allied Health Literature, Literatura Latino Americana e do Caribe em Ciências da Saúde, Lilacs Esp, National Library of Medicine (PubMed), ScienceDirect, Scopus, and the Web of Science platform. The researchers will meet to discuss discrepancies and make decisions using a consensus model, and a third researcher will be tasked with independently resolving any conflicts. Data extraction will involve two independent researchers reviewing each article. Documents such as original articles; theoretical studies; experience reports; clinical study articles; case studies; normative, integrative, and systematic reviews; meta-analyses; meta-syntheses; monographs; theses; and dissertations in English, Portuguese, and Spanish from 2017 to 2023 were included. The results will be presented in tabular and/or diagrammatic format, along with a narrative summary.

List of Top Journals of Distributed Databases sorted by articles.

Research strategy equation to search for articles in databases to answer the question: What are the action mechanisms of anti-inflammatory agents in adipose tissue?.

Dataset for our study on the coverage of software engineering articles in open citation databases:

• a list of the 23 sampled venues with their respective CORE ranks and publishers,
  • 01-venues.csv,
• a list of the 204 sampled articles with their respective number of references/citations per citation database,
  • 02-articles.csv (articles with publication information),
  • 03-references-absolute.csv (number of references in published PDF & absolute numbers for reference coverage in databases),
  • 04-references-relative.csv (relative numbers for reference coverage in databases),
  • 05-citations-absolute.csv (absolute numbers for citation coverage in databases),
  • 06-citations relative.csv (relative numbers for citation coverage in databases),
• a list of the 8 articles analyzed in more detail with complete references data from the citation databases,
  • 07-selected-articles.csv (articles with publication information),
  • 08A–08H (comparison of references found in databases for each article),
• and additional statistical measures and plots
  • 09-Statistics.{pdf,xlsx} (statistical measures – i.e., minimum, maximum, median, average, variance – for the whole dataset and for subsets by publisher, CORE rank, or year of publication),
  • 10-Figures.zip (figures for references as shown in the study and additional figures for citations – each in EPS and PNG format).

Proposed RHIS data use terminology and definitions.

Journal based analysis of the OA-PMC articles. This file presents distribution of the articles as well as the publisher-annotated articles based on the journals in the OA-PMC set. (XLSX)

Citation metrics are widely used and misused. We have created a publicly available database of over 100,000 top-scientists that provides standardized information on citations, h-index, co-authorship adjusted hm-index, citations to papers in different authorship positions and a composite indicator. Separate data are shown for career-long and single year impact. Metrics with and without self-citations and ratio of citations to citing papers are given. Scientists are classified into 22 scientific fields and 176 sub-fields. Field- and subfield-specific percentiles are also provided for all scientists who have published at least 5 papers. Career-long data are updated to end-of-2020. The selection is based on the top 100,000 by c-score (with and without self-citations) or a percentile rank of 2% or above.

The dataset and code provides an update to previously released version 1 data under https://doi.org/10.17632/btchxktzyw.1; The version 2 dataset is based on the May 06, 2020 snapshot from Scopus and is updated to citation year 2019 available at https://doi.org/10.17632/btchxktzyw.2

This version (3) is based on the Aug 01, 2021 snapshot from Scopus and is updated to citation year 2020.

Background/Aims: We sought to describe pediatric “big data” publications since 2000, their statistical output, and clinical implications. Methods: We searched 4 major North American neurosurgical journals for articles utilizing non-neurosurgery-specific databases for clinical pediatric neurosurgery research. Articles were analyzed for descriptive and statistical information. We analyzed effect sizes (ESs), confidence intervals (CIs), and p values for clinical relevance. A bibliometric analysis was performed using several key citation metrics. Results: We identified 74 articles, which constituted 1.7% of all pediatric articles (n = 4,436) published, with an exponential increase after 2013 (53/74, 72%). The Healthcare Cost and Utilization Project (HCUP) databases were most frequently utilized (n = 33); hydrocephalus (n = 19) was the most common study topic. The statistical output (n = 49 studies with 464 ESs, 456 CIs, and 389 p values) demonstrated that the majority of the ESs (253/464, 55%) were categorized as small; half or more of the CI spread (CIS) values and p values were high (274/456, 60%) and very strong (195/389, 50%), respectively. Associations with a combination of medium-to-large ESs (i.e., magnitude of difference), medium-to-high CISs (i.e., precision), and strong-to-very strong p values comprised only 20% (75/381) of the reported ESs. The total number of citations for the 74 articles was 1,115 (range per article, 0–129), with the median number of citations per article being 8.5. Four studies had > 50 citations, and 2 of them had > 100 citations. The calculated h-index was 16, h-core citations were 718, the e-index was 21.5, and the Google i10-index was 34. Conclusions: There has been a dramatic increase in the use of “big data” in the pediatric neurosurgical literature. Reported associations that may, as a group, be of greatest interest to practitioners represented only 20% of the total output from these publications. Citations were weighted towards a few highly cited publications.

This description is part of the blog post "Systematic Literature Review of teaching Open Science" https://sozmethode.hypotheses.org/839

According to my opinion, we do not pay enough attention to teaching Open Science in higher education. Therefore, I designed a seminar to teach students the practices of Open Science by doing qualitative research.About this seminar, I wrote the article ”Teaching Open Science and qualitative methods“. For the article ”Teaching Open Science and qualitative methods“, I started to review the literature on ”Teaching Open Science“. The result of my literature review is that certain aspects of Open Science are used for teaching. However, Open Science with all its aspects (Open Access, Open Data, Open Methodology, Open Science Evaluation and Open Science Tools) is not an issue in publications about teaching.

Based on this insight, I have started a systematic literature review. I realized quickly that I need help to analyse and interpret the articles and to evaluate my preliminary findings. Especially different disciplinary cultures of teaching different aspects of Open Science are challenging, as I myself, as a social scientist, do not have enough insight to be able to interpret the results correctly. Therefore, I would like to invite you to participate in this research project!

I am now looking for people who would like to join a collaborative process to further explore and write the systematic literature review on “Teaching Open Science“. Because I want to turn this project into a Massive Open Online Paper (MOOP). According to the 10 rules of Tennant et al (2019) on MOOPs, it is crucial to find a core group that is enthusiastic about the topic. Therefore, I am looking for people who are interested in creating the structure of the paper and writing the paper together with me. I am also looking for people who want to search for and review literature or evaluate the literature I have already found. Together with the interested persons I would then define, the rules for the project (cf. Tennant et al. 2019). So if you are interested to contribute to the further search for articles and / or to enhance the interpretation and writing of results, please get in touch. For everyone interested to contribute, the list of articles collected so far is freely accessible at Zotero: https://www.zotero.org/groups/2359061/teaching_open_science. The figure shown below provides a first overview of my ongoing work. I created the figure with the free software yEd and uploaded the file to zenodo, so everyone can download and work with it:

To make transparent what I have done so far, I will first introduce what a systematic literature review is. Secondly, I describe the decisions I made to start with the systematic literature review. Third, I present the preliminary results.

Systematic literature review – an Introduction

Systematic literature reviews “are a method of mapping out areas of uncertainty, and identifying where little or no relevant research has been done.” (Petticrew/Roberts 2008: 2). Fink defines the systematic literature review as a “systemic, explicit, and reproducible method for identifying, evaluating, and synthesizing the existing body of completed and recorded work produced by researchers, scholars, and practitioners.” (Fink 2019: 6). The aim of a systematic literature reviews is to surpass the subjectivity of a researchers’ search for literature. However, there can never be an objective selection of articles. This is because the researcher has for example already made a preselection by deciding about search strings, for example “Teaching Open Science”. In this respect, transparency is the core criteria for a high-quality review.

In order to achieve high quality and transparency, Fink (2019: 6-7) proposes the following seven steps:

Selecting a research question.

Selecting the bibliographic database.

Choosing the search terms.

Applying practical screening criteria.

Applying methodological screening criteria.

Doing the review.

Synthesizing the results.

I have adapted these steps for the “Teaching Open Science” systematic literature review. In the following, I will present the decisions I have made.

Systematic literature review – decisions I made

Research question: I am interested in the following research questions: How is Open Science taught in higher education? Is Open Science taught in its full range with all aspects like Open Access, Open Data, Open Methodology, Open Science Evaluation and Open Science Tools? Which aspects are taught? Are there disciplinary differences as to which aspects are taught and, if so, why are there such differences?

Databases: I started my search at the Directory of Open Science (DOAJ). “DOAJ is a community-curated online directory that indexes and provides access to high quality, open access, peer-reviewed journals.” (https://doaj.org/) Secondly, I used the Bielefeld Academic Search Engine (base). Base is operated by Bielefeld University Library and “one of the world’s most voluminous search engines especially for academic web resources” (base-search.net). Both platforms are non-commercial and focus on Open Access publications and thus differ from the commercial publication databases, such as Web of Science and Scopus. For this project, I deliberately decided against commercial providers and the restriction of search in indexed journals. Thus, because my explicit aim was to find articles that are open in the context of Open Science.

Search terms: To identify articles about teaching Open Science I used the following search strings: “teaching open science” OR teaching “open science” OR teach „open science“. The topic search looked for the search strings in title, abstract and keywords of articles. Since these are very narrow search terms, I decided to broaden the method. I searched in the reference lists of all articles that appear from this search for further relevant literature. Using Google Scholar I checked which other authors cited the articles in the sample. If the so checked articles met my methodological criteria, I included them in the sample and looked through the reference lists and citations at Google Scholar. This process has not yet been completed.

Practical screening criteria: I have included English and German articles in the sample, as I speak these languages (articles in other languages are very welcome, if there are people who can interpret them!). In the sample only journal articles, articles in edited volumes, working papers and conference papers from proceedings were included. I checked whether the journals were predatory journals – such articles were not included. I did not include blogposts, books or articles from newspapers. I only included articles that fulltexts are accessible via my institution (University of Kassel). As a result, recently published articles at Elsevier could not be included because of the special situation in Germany regarding the Project DEAL (https://www.projekt-deal.de/about-deal/). For articles that are not freely accessible, I have checked whether there is an accessible version in a repository or whether preprint is available. If this was not the case, the article was not included. I started the analysis in May 2019.

Methodological criteria: The method described above to check the reference lists has the problem of subjectivity. Therefore, I hope that other people will be interested in this project and evaluate my decisions. I have used the following criteria as the basis for my decisions: First, the articles must focus on teaching. For example, this means that articles must describe how a course was designed and carried out. Second, at least one aspect of Open Science has to be addressed. The aspects can be very diverse (FOSS, repositories, wiki, data management, etc.) but have to comply with the principles of openness. This means, for example, I included an article when it deals with the use of FOSS in class and addresses the aspects of openness of FOSS. I did not include articles when the authors describe the use of a particular free and open source software for teaching but did not address the principles of openness or re-use.

Doing the review: Due to the methodical approach of going through the reference lists, it is possible to create a map of how the articles relate to each other. This results in thematic clusters and connections between clusters. The starting point for the map were four articles (Cook et al. 2018; Marsden, Thompson, and Plonsky 2017; Petras et al. 2015; Toelch and Ostwald 2018) that I found using the databases and criteria described above. I used yEd to generate the network. „yEd is a powerful desktop application that can be used to quickly and effectively generate high-quality diagrams.” (https://www.yworks.com/products/yed) In the network, arrows show, which articles are cited in an article and which articles are cited by others as well. In addition, I made an initial rough classification of the content using colours. This classification is based on the contents mentioned in the articles’ title and abstract. This rough content classification requires a more exact, i.e., content-based subdivision and evaluation by others, who are experts in the respective fields/disciplines.

IntroductionPrimary health care is a key element in the structuring and coordination of health systems, contributing to overall coverage and performance. PHC financing is therefore central in this context, with variations in sufficiency and regularity depending on the “political dimension” of health systems. Research that systematically examines the political factors and arrangements influencing PHC financing is justified from a global and multidisciplinary perspective. The scoping review proposed here aims to systematically map the evidence on this topic in the current literature, identifying groups, institutions, priorities and gaps in the research.Methods and analysisA scoping review will be conducted following the method proposed by Arksey and O’Malley to answer the following question: What is known from the literature about political factors and arrangements and their influence on and repercussions for primary health care financing and resource allocation models? The review will include peer-reviewed papers in Portuguese, English or Spanish published between 1978 and 2023. Searches will be performed of the following databases: Medline (PubMed), Embase, BVS Salud, Web of Science, Scopus and Science Direct. The review will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist. Inclusion and exclusion criteria will be used for literature screening and mapping. Screening and data charting will be conducted by a team of four reviewers.RegistrationThis protocol is registered on the Open Science Framework (OSF) platform, available at https://doi.org/10.17605/OSF.IO/Q9W3P

[NOTE: PLEXdb is no longer available online. Oct 2019.] PLEXdb (Plant Expression Database) is a unified gene expression resource for plants and plant pathogens. PLEXdb is a genotype to phenotype, hypothesis building information warehouse, leveraging highly parallel expression data with seamless portals to related genetic, physical, and pathway data. PLEXdb (http://www.plexdb.org), in partnership with community databases, supports comparisons of gene expression across multiple plant and pathogen species, promoting individuals and/or consortia to upload genome-scale data sets to contrast them to previously archived data. These analyses facilitate the interpretation of structure, function and regulation of genes in economically important plants. A list of Gene Atlas experiments highlights data sets that give responses across different developmental stages, conditions and tissues. Tools at PLEXdb allow users to perform complex analyses quickly and easily. The Model Genome Interrogator (MGI) tool supports mapping gene lists onto corresponding genes from model plant organisms, including rice and Arabidopsis. MGI predicts homologies, displays gene structures and supporting information for annotated genes and full-length cDNAs. The gene list-processing wizard guides users through PLEXdb functions for creating, analyzing, annotating and managing gene lists. Users can upload their own lists or create them from the output of PLEXdb tools, and then apply diverse higher level analyses, such as ANOVA and clustering. PLEXdb also provides methods for users to track how gene expression changes across many different experiments using the Gene OscilloScope. This tool can identify interesting expression patterns, such as up-regulation under diverse conditions or checking any gene’s suitability as a steady-state control. Resources in this dataset:Resource Title: Website Pointer for Plant Expression Database, Iowa State University. File Name: Web Page, url: https://www.bcb.iastate.edu/plant-expression-database [NOTE: PLEXdb is no longer available online. Oct 2019.] Project description for the Plant Expression Database (PLEXdb) and integrated tools.

Selection of databases commonly used in our workflows.

Dataset

This dataset was created by Hikmet Gumus

Released under Other (specified in description)

Contents

Abstract Background Studies on “Spirituality, religion and health” (R/S) have been increasing worldwide, including in Brazil. Mapping this production can help researchers to understand this field and also to identify gaps in the Brazilian R/S studies. Objective To analyze the Brazilian scientific articles on “Religion, Spirituality and Health” available on the main electronic databases using a bibliometric approach. Methods A comprehensive review of four major databases (PubMed, Scopus, BVS and Web of Science) was conducted. Three reviewers performed the data analysis. Off-topic articles, articles from Portugal, books and thesis were excluded. Articles were then classified by: Publication year, journal, Central focus in R/S, Academic Area, Main topic and Study Type. Results From 3,963 articles found, 686 studies were included in the final analysis (320 had central focus on R/S). There was an increase of articles in the last decade (most observational), with predominance of mental health issues, and from journals in the field of psychiatry, public health and nursing. Discussion This study enabled us to widen our understanding about how the field of “spirituality, religion and health” has been established and how this field is increasing in Brazil. These findings can help in the development of future Brazilian studies.

The Shared Socioeconomic Pathways (SSPs) Literature Database, v1, 2014-2019 consists of biographic information, abstracts, and analysis of 1,360 articles published from 2014 to 2019 that used the SSPs. The database was generated from a Google Scholar search, followed by a manual examination of the results for papers that made substantial use of the SSPs. Each paper was then coded along a number of different dimensions, including categories of types of papers or analysis, number of subcategories for SSP Applications and SSP Extensions, particular Shared Socioeconomic Pathways (SSPs) used, particular Representative Concentration Pathways (RCPs) used, and particular SSP-RCP combinations used. Over the past ten years, the climate change research commUnity developed a scenario framework combining alternative futures of climate and society to facilitate integrated research and consistent assessment to inform policy. This framework consists of Shared Socioeconomic Pathways (SSPs), Representative Concentration Pathways (RCPs), and Shared Policy Assumptions (SPAs), which together describe alternative visions of how society and climate may evolve over the coming decades, while providing a framework for combining these pathways in integrated studies. The tracking of the use of this framework in the literature allows for assessment of how it is being used, whether it is achieving its original goals, and what improvements to the framework would benefit future research.

Research dissemination and knowledge translation are imperative in social work. Methodological developments in data visualization techniques have improved the ability to convey meaning and reduce erroneous conclusions. The purpose of this project is to examine: (1) How are empirical results presented visually in social work research?; (2) To what extent do top social work journals vary in the publication of data visualization techniques?; (3) What is the predominant type of analysis presented in tables and graphs?; (4) How can current data visualization methods be improved to increase understanding of social work research? Method: A database was built from a systematic literature review of the four most recent issues of Social Work Research and 6 other highly ranked journals in social work based on the 2009 5-year impact factor (Thomson Reuters ISI Web of Knowledge). Overall, 294 articles were reviewed. Articles without any form of data visualization were not included in the final database. The number of articles reviewed by journal includes : Child Abuse & Neglect (38), Child Maltreatment (30), American Journal of Community Psychology (31), Family Relations (36), Social Work (29), Children and Youth Services Review (112), and Social Work Research (18). Articles with any type of data visualization (table, graph, other) were included in the database and coded sequentially by two reviewers based on the type of visualization method and type of analyses presented (descriptive, bivariate, measurement, estimate, predicted value, other). Additional revi ew was required from the entire research team for 68 articles. Codes were discussed until 100% agreement was reached. The final database includes 824 data visualization entries.

The Sub-global Scenarios that Extend the Global SSP Narratives: Literature Database, Version 1, 2014-2021 consists of 37 columns of bibliographic data, methodological and analytical insights, from 155 articles published from 2014 to 2021 that extended the narratives of global SSPs. Local and regional scale Shared Socioeconomic Pathways (SSPs) have grown largely in addressing Climate Change Impact, Adaptation, and Vulnerability (CCIAV) assessments at sub-global levels. Common elements of these studies, besides their focus on CCIAV, are the use of both quantitative and qualitative elements of the SSPs. To explore and learn from current literature on novel methods and insights on extending SSPs, the sub-global extended SSPs literature database is constructed in the research for analyses. The database was developed in four stages: searches; screening; data extraction; and coding. The search stage incorporated three approaches: using a search string in three academic databases (Scopus, Web of Science Core Collection, ScienceDirect); a targeted search of a specific relevant database (ICONICS); and a targeted selection in Google Scholar of all papers that cited the publication of the global SSP narratives. In the screening step, criteria were assessed for full-text papers for eligibility including relevant typologies, methodologies, and other criteria. Finally, data from eligible papers was extracted and entered in a coding framework in an Excel workbook spreadsheet. The coding framework resulted in 37 columns to systematize coding of data from the 155 papers selected along several different dimensions, including categories of papers or analysis, several subcategories for SSP Applications and SSP Extensions, specific SSPs used, specific Representative Concentration Pathways (RCPs) used, typologies of extensions of qualitative and quantitative SSPs, and the types of models and nature of the extended SSPs.

The CottonGen CottonCyc Pathways Database, part of CottonGen, supports searching and browsing the following CottonCyc databases: Cyc pathways for JGI v2.0 G. raimondii D5 genome assembly This Cyc database was constructed using PathwayTools version 20.0 using the gene models from the JGI v2.0 D5 genome assembly of Gossypium raimondii. There has been no manual curation of this Cyc database. Pathway predictions were made using PathwayTools and in-silico v2.1 annotations as provided by JGI. Cyc pathways for CGP-BGI v1.0 G. hirsutum AD1 genome assembly This Cyc database was constructed using PathwayTools version 20.0 using the gene models from the CGP-BGI v1.0 AD1 genome assembly of Gossypium hirsutum. There has been no manual curation of this Cyc database. Pathway predictions were made using PathwayTools and in-silico v1.0 annotations as provided by CGP-BGI. Search parameters include genes, proteins, RNAs, compounds, reactions, pathways, growth media, and BLAST search. Resources in this dataset:Resource Title: Website Pointer to CottonGen CottonCyc Pathways Database. File Name: Web Page, url: http://ptools.cottongen.org/

The Climate Change and Human Health Literature Portal is a bibliographic database created by the National Institute of Environmental Health Sciences(NIEHS) that contains a collection of scientific research on the health impacts of climate change. It compiles literature including studies on extreme weather events, heat waves, air pollution, infectious diseases and more. The mission of the NIEHS is "to discover how the environment affects people in order to promote healthier lives." The portal draws from biomedical and environmental databases like PubMed to compile studies and collect data across various aspects of the environment and population groups. The database includes citations and links to 22,695 studies published from 2007 to 2023, and users can filter studies to search based on exposure, health impact, geographic location, geographic feature, model/methodology, model timescale, special topic, resource type and year published. Citations with links to articles (not the articles themselves) are included in the database.The web portal was no longer available as of February 2025, and the bibliographic records in this dataset capture what was behind the portal. A copy of the portal is available in the Internet Archive.Data is provided in two formats:1. A JSONL file that captures the original structure of the records as they were published in the web portal. Also available from the Internet Archive at: https://archive.org/details/cchhl_2025-02-10.2. A CSV file that represents a flattened version of the JSON, with the removal of duplicate fields and renamed and reordered columns. Columns with the suffix "terms" contain lists of subject terms that are separated with a pipe character '|'.A README file with codebook is included.