In line with the guidelines of the Social Sciences and Humanities Research Council of Canada (SSHRC), the agency providing the funding for this research project , I endeavour to share publicly all my datasets. In addition to striving for transparency and accountability in research practices, providing my datasets in publicly accessible repositories enables me to disseminate the findings and share benefit of the accumulated knowledge with a larger audience.
This literature review database consists of five datasets (Datasets I through V) that are based on a systematic review of 115 literature sources on the daylighting of streams that were published between 1992 and 2018 whereby these sources combine both peer reviewed and grey literature sources. My research team and I combined this systematic review with content analysis. The combination of a systematic review and content analysis facilitated the extraction of two types of content from the 115 literature sources, namely: manifest (obvious, factual, and indisputable characteristics) and latent (less obvious characteristics and information that can be uncovered only by a thorough reading of each source’s text) (Khirfan, Peck, and Mohtat 2020b). Specifically, the ‘manifest data’ content obtained from each source includes: A) JR’s  disciplinary classification; B) the publication type (peer-reviewed versus grey literature; C) the publication date; and D) the geographic origin of the publication’s authorship (continent and, or country) (Khirfan, Peck, and Mohtat 2020a). As for the 'latent content' whose extraction entailed careful reading of each source. Accordingly, these data include: 1) the synonyms used to refer to stream daylighting (leading to a terminology analysis); 2) the characteristic(s) of stream daylighting definitions (leading to an identification of the definition tracks); and 3) specific daylighting case studies discussed in each source (leading to an analysis of the daylighting projects) (Khirfan, Mohtat, and Peck 2020).
Three of the datasets, Datasets I, II, and III, are available through Mendeley in the form of Microsoft Excel documents, while two are interactive and visual tools embedded within this website (the Tableau Dashboard and the Interactive Map). Specifically:
Dataset I consist of 19 variables ten of which are manifest variables while nine are latent content variables (see above for the distinctions). The manifest variables include, among others, the names and affiliations of the authors, the authorship location, and the publication year. The latent variables include: the literature sources’ underlying themes and their sub-themes (sub-categories), the geographic coverage or scope addressed, and the daylighting case studies/projects discussed in the literature sources.
Datasets II consist of data extracted from 16 literature sources on stream daylighting that also delve into the climate change adaptation and/or mitigation theme (whether directly or indirectly). In this dataset, we identify how stream daylighting is discussed vis-à-vis climate change adaptation and/or mitigation as well as the other nine themes and/or the 53 sub-themes.
Dataset III consist of detailed information on the 145 different daylighting stream daylighting case studies/projects that were mentioned in the literature’s sources. The variables include, among others, each project’s location, daylighted length, completion date, cost, and type of treatment.
Dataset IV is an interactive Tableau Dashboard. We reproduced our Database I in the form of a dashboard embedded within a Tableau (software) platform that enables visitors to the site to conduct their own analytical querying from our database (i.e., relational analyses and data visualization) .
Dataset V is an Interactive Map created in Google My Map that maps the 145 stream daylighting case studies/projects mentioned in the literature sources over and provides a synopsis on each based on the literature’s contents. The combination of these five datasets and their diversity in type and presentation yields a comprehensive, global, and unique repository of information on the daylighting of urban streams for all types of audiences (academic, professional, and laypeople).
- Khirfan, Luna, Niloofar Mohtat, and Megan Peck. 2020. "A systematic literature review and content analysis combination to “shed some light” on stream daylighting (Deculverting)." Water Security 10:100067. doi: https://doi.org/10.1016/j.wasec.2020.100067.
- Khirfan, Luna, Megan Leigh Peck, and Niloofar Mohtat. 2020a. "Digging for the truth: A combined method to analyze the literature on stream daylighting." Sustainable Cities and Society 59. doi: https://doi.org/10.1016/j.scs.2020.102225.
- Khirfan, Luna, Megan Peck, and Niloofar Mohtat. 2020b. "Systematic content analysis: A combined method to analyze the literature on the daylighting de-culverting) of urban streams." MethodsX 7 (100984). doi: https://doi.org/10.1016/j.mex.2020.100984.
 SJR is shorthand for Scopus’s SCImago Journal Ranking, an online bibliographic database operated by Elsevier that classifies the disciplinary ‘subject area’ and ‘category’ of peer-reviewed, academic journals. Scopus’s bibliographic database was used in favour of ISI’s Web of knowledge database due to its broader journal coverage. SJR’s disciplinary classifications are not mutually exclusive whereby one journal may be classified under one or more subject areas.
 Special thanks to Mr. Nathan Woodcock for his assistance with the interactive Tableau Dashboard. Dr. Luna Khirfan and the Research Team are grateful for Mr. Woodcock's continuous support.