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552 results for “Literature review”
Methane concentrations and oxidation rates in land-terminating glacial runoff: measurements from three glacial rivers and a paraglacial lake in Iceland and a literature review
<div> <p>This dataset contains methane measurements from Icelandic lakes and rivers during the summer of 2018 and 2019. This includes data from net methane oxidation assays with sediment and overlying water from one paraglacial lake and one glacial river, and surface methane concentration data from grab samples in 3 glacial streams and 15 Icelandic lakes (1 of which is paraglacial). The dataset also contains methane concentration data from a synthesis of relevant aquatic ecosystems, used to compare against the original measurements collected. </p> </div> <div> <p>Data and Literature Review Synthesis is supplement to Strock et al. 2024 <em>Oxidation is a potentially significant methane sink in land-terminating glacial runoff</em> published in Nature Scientific Reports. </p> <div> <p>This study was funded by: National Geographic Society Changing Polar Systems grant (CP4-162R-18); In-kind support from the U.S. Geological Survey; Dickinson College Research and Development; Churchill Exploration Fund at Dickinson College </p> </div> </div>
IPBES Data Management Tutorials - Session 6.2: Literature review from the Global Assessment chapter 4
<p>The <em>IPBES data management tutorials</em> are short videos to help experts implement the IPBES data management Policy. They cover topics ranging from data management policy, reports, active research data, tools, and examples.</p> <p>The chapter on<em> Examples of implementing the IPBES data management Policy</em> contains examples of how certain data management tasks and workflows were implemented within IPBES so that they follow the data management policy. <strong>Currently, this chapter contains legacy videos and the most recent examples can be found within the IPBES technical guidelines here:</strong> <a href="https://ict.ipbes.net/ipbes-ict-guide/data-management/technical-guidelines">https://ict.ipbes.net/ipbes-ict-guide/data-management/technical-guidelines</a></p> <p>This session <em>Literature review from the Global Assessment chapter 4 </em>walks you through each step of the data management of the systematic literature review from the Chapter 4 of the Global Assessment. </p>
ZOOOM Literature Review Clean Dataset
<p>The csv file contains the dataset of literature search produced by the ZOOOM EU Funded Project on open software, open hardware, open data business models.</p>
Dataset for: A systematic literature review on user factors to support the sense of presence
<p>This dataset was created for a publication of Wiepke, Axel and Heinemann, Birte called "A systematic literature review on user factors to support the sense of presence". In this paper we used the PRISMA-method to collect Papers via Google Scholar on the third of April 2023 with the search term:<br>(framework OR model OR frameworks OR models OR processes OR ontologies) AND ((“personality traits” OR “personality variables” OR “personality factors”) AND “spatial presence”) AND (“virtual reality”) AND (learn OR edu\*)</p> <p>The results were pictured in "agreed" findings, where more than 50% of found studies supported a category of results and in "controversial", where there were significant findings, but less than 50% of the studies reported significance.</p> <p>This dataset contains:</p> <ul> <li>raw data for our literature review in .bib</li> <li>our main findings with categories in .csv</li> <li>a short Jupyter notebook script for one graphic in ipynb</li> <li>other graphics as .png</li> </ul>
Systematic Literature Review on Tourism Marketing in the Metaverse
<p>The aim of this research is to investigate tourist marketing within the embryonic context of the metaverse in order to comprehend the building blocks and the primary technologies employed in the sector. For this purpose, a systematic literature review is conducted. The references are extracted in January 2023. The data in this document correspond to the articles finally included in the systematic literature review after the article screening phase.</p> <p>Keywords: tourism marketing, metaverse, technologies, building blocks, SLR (Systematic Literature Review), PRISMA</p> <p> </p>
Automated Literature Screening for Systematic Reviews: Dataset for Evaluation Against Human Title and Abstract and Full-Text Screening Decisions
<p>This Zenodo entry contains the supplementary material associated with the manuscript titled <em>Automated Literature Screening for Systematic Reviews: A 5-Tier Prompting Approach Meeting Cochrane’s Sensitivity Requirement of Greater Than 0.99.</em> The paper will be presented at <a href="https://dbis.rwth-aachen.de/LLMs4MI2024/">LLMsMI 2024</a> in November 2024.</p> <p>A script is provided for replicating the executed experiments, along with a comprehensive evaluation file that reports all the experiment results. Provided data files represent an extension to the original datasets as provided by [1]. For associated systematic review manuscripts and eligibility criteria, please refer to [1] as well. </p> <p>[1] Guo, Eddie; Gupta, Mehul; Deng, Jiawen; Park, Ye-Jean; Paget, Mike; Naugler, Christopher (2023). "Automated Paper Screening for Clinical Reviews Using Large Language Models." <em>Mendeley Data</em>, V1, doi: 10.17632/np79tmhkh5.1. Accessed from: <a href="https://data.mendeley.com/datasets/np79tmhkh5/1" target="_new" rel="noopener">https://data.mendeley.com/datasets/np79tmhkh5/1</a>.</p>
Dataset for paper: A Systematic Literature Review and Recommendations for Ontology-based Support of Digital Forensics
<p>PLEASE, READ THE README.TXT FILE</p> <p>This document describes how to interpret the data and metadata files, and it is licensed under Creative Commons CC BY-NC-AS (https://creativecommons.org/licenses).</p> <p>The file "primary_studies_final_set-DATA.csv" is a CSV file format and contains the raw data extracted from our systematic literature review primary studies. Such data were extracted based on the research questions defined for our study.<br> The file "primary_studies_final_set-METADATA.csv" is a CSV file format and contains the following:<br> - the first row contains two pieces of information: the data type, which might be original or reused;<br> - the second row contains the reused data URL/DOI, which should inform the URL or DOI from which the data was reused, or n/a if the data is original;<br> - the third row contains the date of data generation in the format mm/dd/yyyy;<br> - the fourth row contains 11 elements describing each of the fields of the file "primary_studies_final_set-DATA.csv": the study ID, title, objective, six research questions, and an observation field; and<br> - the fifth row describes the data type of each field of the file "primary_studies_final_set-DATA.csv".<br> The .bib files contain the bibtex entry for the final set of studies.<br> The license.txt file describes the Creative Commons license for this material.</p> <p>We hope you have an excellent read!!</p> <p>Cheers!<br> Thiago, Edson, and Avelino</p>
Bots in Software Development: A Systematic Literature Review [Data Set]
<p>This repository contains al the artifacts of the research: Bots in Software Development: A Systematic Literature Review </p>
Reviewed literature on the state of conservation planning in Europe
<p><strong>Literature review of European conservation planning studies</strong></p> <p>The data table uploaded here contains reviewed literature as part of the manuscript "An assessment of the state of conservation planning in Europe” by Jung et al. that is currently in Review. In this work we reviewed all available scientific literature broadly dealing with conservation planning in various facets and across realms (terrestrial, freshwater, marine). The database provided here thus provides a comprehensive starting point of all scientific conservation planning studies conducted in Europe up until mid 2023.</p> <p>The dataset is derived from a Scopus literature query conducted on the 23th of September 2022, which resulted in an initial 1459 studies which were further refined and supplemented by evidence known to the authors.</p> <p>---</p> <p># <strong>Description of table columns</strong>:</p> <ul> <li>"ID" = Numeric Identifier of the study</li> <li>"Extent" = Scale the study was conducted, from local, regional, national to European wide</li> <li>"Region" = The broad region with regards to European country</li> <li>"Locality" = Additional detail on the locality of the study if easily available</li> <li>"Realm" = Which realm does the study cover (e.g. Terrestrial, Marine, ...)</li> <li>"Ecosystem.specificity" = Was the study conducted only for specific ecosystems (e.g. Forests)?</li> <li>"Period" = Over which period was the study conducted (Present only, future conditions, both)</li> <li>"Planning.purpose" = What was the purpose of the study?</li> <li>"Policy.relevance" = Specific policy directives or legal documents referred to in the study introduction.</li> <li>"Method" = Which method was used for the planning purpose (i.e., Zonation, Marxan, ...)</li> <li>"Biodiversity.type; = What type of Biodiversity data was included in the study?</li> <li>"Number.of.features" = How many number of features?</li> <li>"Multiple.objectives.or.constraints" = Did the study somehow account for multiple objectives or constraints?</li> <li>"Connectivity" = Was connectivity somehow considered and if so, how?</li> <li>"Costs" = Were socio-economic costs somehow considered?</li> <li>"Stakeholder.involvement" = Were stakeholders involved in the planning exercise at any point?</li> <li>"Authors" = Authors of the study</li> <li>"Title" = The title of the study</li> <li>"Year" = The year it was published</li> <li>"Journal" = The scientific journal were it was published</li> <li>"DOI" = A Digital Object identifier link (can sometimes be missing)</li> <li>"Link" = A link to the journal website (can be missing)</li> <li>"Author.Keywords" = Keywords by the authors given to the study (can be missing)</li> <li>"Index.Keywords" = Keywords captured by SCOPUS for the study (can be missing)</li> <li>"Document.Type" = Type of article</li> <li>"Source" = Derived from SCOPUS or manually added through a snowballing approach?</li> <li>"cite_scientific_May2023" = How often cited in the scientific literature by May 2023?</li> <li>"cite_policy_May2023" = How often cited in policy literatue by May 2023?</li> </ul> <p>---</p> <p>The analysis code supporting the manuscript and analysing the dataset presented here can be found <a href="https://github.com/Martin-Jung/Review_EuropeanConservationPlanning">here</a>. A preprint of the manuscript can be found <a href="http://dx.doi.org/10.31219/osf.io/8x2ug">here</a>.</p>
State-of-the-art review of near-term freshwater forecasting literature published between 2017 and 2022
This data publication includes code and results from a systematic literature review on the current state of near-term forecasting of freshwater quality. The review aimed to address the following questions: (1) Freshwater variables, scales, models, and skill: Which freshwater variables and temporal scales are most commonly targeted for near-term forecasts, and what modeling methods are most commonly employed to develop these forecasts? How is the accuracy of freshwater quality forecasts assessed, and how accurate are they? How is uncertainty typically incorporated into water quality forecast output? (2) Forecast infrastructure and workflows: Are iterative, automated workflows commonly employed in near-term freshwater quality forecasting? How are forecasts validated and archived? (3) Human dimensions: What is the stated motivation for development of most near-term freshwater quality forecasts, and who are the most common end users (if any)? How are end users engaged in forecast development? An initial search was conducted for published papers presenting freshwater quality forecasts from 1 January 2017 to 17 February 2022 in the Web of Science Core Collection. Results were subsequently analyzed in three stages. First, paper titles were screened for relevance. Second, an initial screen was conducted to assess whether each paper presented a near-term freshwater quality forecast. Third, papers that passed the initial screen were analyzed using a standardized matrix to assess the state of near-term freshwater quality forecasting and identify areas of recent progress and ongoing challenges. Additional details regarding the systematic literature search and review are presented in the Methods section of the metadata.
SHAPE-ID Literature Review dataset: bibliography on IDR/TDR
<p><strong>Background and methodology:</strong></p> <p>The dataset consists of 5040 records of publication metadata (author, abstract, title, keywords, tags etc.), produced for the purposes of the <a href="https://doi.org/10.5281/zenodo.3760417">systematic literature review</a> in the framework of the <a href="https://www.shapeid.eu/">SHAPE-ID</a> project. </p> <p>In the course of the review Project team queried Web of Science (WoS), Scopus and JSTOR databases for records on interdisciplinarity and transdisciplinarity (IDR/TDR). In the case of WoS and Scopus, <a href="https://doi.org/10.5281/zenodo.4034333">complex search strings</a> were created to reflect the main research questions of the Literature Review: different understandings of IDR/TDR and factors and indicators of success or failure of integration of IDR/TDR in research and research policy. JSTOR database offers less advanced data-analytical tools, but the project team decided to include items that have interdisciplinarity or transdisciplinarity in the title, to counterbalance the reported biases against Arts, Humanities and Social Sciences in Scopus and WoS. These three data sources were complemented with bibliographies prepared during the preliminary scoping analysis of IDR/TDR literature. The query results were compiled in reference managers Zotero and Endnote. During data processing the records were normalized and duplicates were removed. </p> <p>Based on systematic review, a sample of the literature had been selected for qualitative analysis. At the same time, the bibliographic metadata was analysed with computationally assisted quantitative methods.</p> <p><strong>Description of the file:</strong></p> <p>This is a csv file exported from the Zotero database, and formatted according to the <a href="https://www.zotero.org/support/kb/item_types_and_fields">Zotero metadata model</a>. It contains a collection of 5040 bibliographic records compiled for the purpose of the SHAPE-ID Literature Review.</p>
SHAPE-ID Literature Review dataset: journal occurrences with ASJC codes
<p><strong>Background and methodology:</strong></p> <p>The dataset consists of a list of 2202 journal titles represented in the <a href="https://doi.org/10.5281/zenodo.4034507">SHAPE-ID Literature Review bibliography</a>, prepared for the purposes of quantitative analysis.</p> <p>The list of journals is based on 3955 journal articles in the bibliography dataset that had an International Standard Serial Number (ISSN). To each journal title the project team attributed:</p> <p>- a weight factor based on how many articles from the given journal featured in bibliography dataset</p> <p>- at least one <a href="https://service.elsevier.com/app/answers/detail/a_id/15181/supporthub/scopus/">All Science Journal Classification</a> (ASJC) code, representing different scientific disciplines</p> <p>- a country of publication. </p> <p>In case of 1853 of those journal titles, the attribution was automatised (we matched the ISSNs of journal titles in our sample against the Scopus Sources list from February 2019). In case of the remaining 349 titles the attribution was accomplished manually, based on the information available in SCOPUS, Web of Science, JSTOR, Information Matrix for the Analysis of Journals (MIAR) and ISSN databases.</p> <p><strong>Description of the file:</strong></p> <p>This is a csv file containing a list of 2202 journal titles represented in the SHAPE-ID Literature Review bibliography, with country of publication and ASJC codes assigned. </p> <p>The file is formatted as follows:</p> <p>Column A: ISSN of the journal</p> <p>Column B: information on how country and ASJC codes were attributed. Value “N” indicates automatic attribution based on match with Scopus list of sources. Other values indicate manual attribution. Values WOS, SCOPUS, JSTOR indicate source of information. Valu “Y” indicates that information was compiled based on multiple sources. </p> <p>Column C: numeric values correspond to the weight factor, i.e. number of time articles from each journal featured in the SHAP-ID Literature Review bibliography. </p> <p>Column D: SHAPE-ID Zotero bibliography identifier.</p> <p>Column E: Journal title</p> <p>Column F: The country of publication</p> <p>Columns G-AD: ASJC codes (numeric and word values) associated with journal entries. </p>
Review of definitions of Open Peer Review in the scholarly literature 2016
<p>This data set contains:</p> <ul> <li>Full data files of a 2016 review of definitions of Open Peer Review in the scholarly literature in xls and csv formats</li> <li>Description of data collection methodology (txt)</li> <li>Readme file (txt)</li> </ul> <p>The term “open peer review” has neither a standardized definition nor an agreed schema of its features and implementations. Recognising the absence of a consensus view on what OPR is, OpenAIRE has undertaken a systematic review of definitions of “open peer review” or “open review”, to create a corpus of 122 definitions. These definitions have been systematically analysed to build a coherent typology of the many different innovations in peer review signified by the term and hence provide the precise technical definition currently lacking. This quantifiable data offers rich information on the range and extent of differing definitions over time and by broad subject area.</p> <p>Contact:</p> <p>Tony Ross-Hellauer: http://orcid.org/0000-0003-4470-7027 / ross-hellauer@sub.uni-goettingen.de</p>
Screened literature for mapping review of environmental problem shifting (EPS)
<p>Final literature sample used in manuscript. (506 publications). </p><p>Version 2 after revision. </p><p>Columns from the Scopus API:</p><ul><li>DOI, ISSN, ISBN</li><li>Subjabbr: Abbreviation of Scopus subject area</li><li>Publication year</li><li>Pubname: The name of the journal</li><li>Authkeywords: The article keywords</li><li>Title: The document title</li></ul><p> </p><p>Columns from our classification:</p><ul><li>Articletype: Classification into empirical, review and conceptual-theoretical.</li><li>Documenttype: The type of publication: journal article, book chapter, reports.</li><li>Counter: Marks the 13 studies that find no shifting or positive environmental impacts only.</li><li>Miti measures: The type of mitigation option.</li><li>Split measures: The subtype of mitigation. Only coded for <i>CDR</i>; <i>Solar, hydro and wind power</i> and <i>Other</i>.</li><li>Methods: The method(s) used in empirical papers</li><li>Impacts: The environmental impact.</li><li>Split impacts: The environmental impact specified for subtypes of mitigation.</li></ul>
Bibliographic Dataset for the Systematic Literature Review on Industry 5.0 Concepts and Enabling Technologies, Towards an Enhanced Conservation Practice
<p>This database contains all the bibliographic information found after applying the Search Strategy used for the Industry 5.0 Concepts and Enabling Technologies, Towards an Enhanced Conservation Practice: Systematic Literature Review. The following electronic databases were searched:</p> <ul> <li>Scopus.</li> </ul> <p>A total of 907 records were found. The search was conducted on 16/02/2024.</p> <p>The information is presented in .ris, .bib, and .csv format.</p>
Reproduction package for paper "How far are we from reproducible research on code smell detection? A systematic literature review"
<p>Checklist and data extracted from publications analyzed for "How far are we from reproducible research on code smell detection? A systematic literature review" paper, together with processing scripts and calculations of Cohen's Kappa.</p> <p>Paper that describes details of the data is available here: https://doi.org/10.1016/j.infsof.2021.106783</p>
Supplemental Material for a Systematic Literature Review on Benchmarks for Evaluating Debugging Approaches
<p>Bug benchmarks are used in development and evaluation of debugging approaches. Quantitative performance comparison of different debugging approaches is only possible when they have been evaluated on the same dataset or benchmark. However, benchmarks are often specialized towards usage for certain debugging approaches in their contained data, metrics, and artifacts. Such benchmarks can not be easily used on debugging approaches outside their scope as such approach may rely on specific data such as bug reports or code metrics not included in the dataset. Furthermore, benchmarks vary in their size w.r.t. the number of subject programs and the size of the individual subject programs. For these reasons, we have performed a systematic literature review where we have identified 73 benchmarks that can be used to evaluate debugging approaches.</p> <p>We compare the different benchmarks with respect to their size and the provided information such as bug reports, contained test cases, and other code metrics. Furthermore, we have investigated how well the benchmarks realize the <a href="https://www.go-fair.org/fair-principles/">FAIR guiding principles</a>. This comparison is intended to help researchers to quickly identify all suitable benchmarks for evaluating their specific debugging approaches. More information can be found in the publication:</p> <blockquote> <p>Thomas Hirsch and Birgit Hofer: "A Systematic Literature Review on Benchmarks for Evaluating Debugging Approaches", Journal of Systems and Software, in press, 2022.</p> </blockquote>
GERDAT011 Literature search for publication - Geriatric assessment in the management of older patients with cancer – a systematic review (update).xlsx
<p>Search data belonging to the publication Geriatric assessment in the management of older patients with cancer – a systematic review (update)</p>
Privacy-by-Design Maturity Model: literature review, coding, model creation and evaluation
<p>Results from two multivocal literature reviews (MLRs) and subsequent coding, formulation of capabilities and dependencies, creation of maturity matrix and evaluation results. Used in the creation of a PbD domain model and extraction of core activities for PbD in Information Systems design. Part of the <a href="https://www.privacymaturity.org/" target="_blank" rel="noopener">Privacy-by-Design Maturity</a> research project by the <a href="https://www.uu.nl/en/research/ai-labs/ai-lab-for-the-public-services" target="_blank" rel="noopener">AI Lab for Public Services</a>.</p>
Classification and frequency of climate change drivers and responses of small-scale fishers found in literature review
<p>Climate change hazards were classified into resource availability and fishing operations or both following the framework proposed by Cheung et al (2012). Response units were firstly classified into overarching responses and then categorized as suggested by the adaptive-transformative framework of Barnes et al.<sup> </sup>(2020). Adaptation units that did not represent an active adaptation response were classified as remaining. More than one hazard could be attributed to each fishers' response.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
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