Objective(s): Momentum for open access to research is growing. Funding agencies and publishers are increasingly requiring researchers make their data and research outputs open and publicly available. However, clinical researchers struggle to find real-world examples of Open Data sharing. The aim of this 1 hr virtual workshop is to provide real-world examples of Open Data sharing for both qualitative and quantitative data. Specifically, participants will learn: 1. Primary challenges and successes when sharing quantitative and qualitative clinical research data. 2. Platforms available for open data sharing. 3. Ways to troubleshoot data sharing and publish from open data. Workshop Agenda: 1. “Data sharing during the COVID-19 pandemic” - Speaker: Srinivas Murthy, Clinical Associate Professor, Department of Pediatrics, Faculty of Medicine, University of British Columbia. Investigator, BC Children's Hospital 2. “Our experience with Open Data for the 'Integrating a neonatal healthcare package for Malawi' project.” - Speaker: Maggie Woo Kinshella, Global Health Research Coordinator, Department of Obstetrics and Gynaecology, BC Children’s and Women’s Hospital and University of British Columbia This workshop draws on work supported by the Digital Research Alliance of Canada. Data Description: Presentation slides, Workshop Video, and Workshop Communication Srinivas Murthy: Data sharing during the COVID-19 pandemic presentation and accompanying PowerPoint slides. Maggie Woo Kinshella: Our experience with Open Data for the 'Integrating a neonatal healthcare package for Malawi' project presentation and accompanying Powerpoint slides. This workshop was developed as part of Dr. Ansermino's Data Champions Pilot Project supported by the Digital Research Alliance of Canada. NOTE for restricted files: If you are not yet a CoLab member, please complete our membership application survey to gain access to restricted files within 2 business days. Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator on this page under "collaborate with the pediatric sepsis colab."

Abstract copyright UK Data Service and data collection copyright owner. This project drew its inspiration from what was felt to be a growth in the number of investigations combining qualitative and quantitative research. Enthusiasm for and use of multi-strategy research was running ahead of what was known about how it is employed in practice and what its benefits might be. Thus, it was felt at the start of the project that the time was ripe for an examination of multi-strategy research in practice. The project's objectives were to: provide a comprehensive assessment of the state of the field with regard to the integration of qualitative and quantitative research; proffer recommendations with regard to good practice for the integration of qualitative and quantitative research; identify areas or contexts in which the integration of qualitative and quantitative research is not obviously beneficial; explore an area where qualitative and quantitative research co-exist as separate strategies or traditions and analyse the prospects for linking the two sets of findings; explore some of the discursive practices involved in the representation of research which integrates the two approaches. Main Topics: The dataset derives from a content analysis of case studies of the integration of qualitative and quantitative research across the social sciences. Whilst it is recognized that journal articles do not by any means encapsulate all possible contexts in which projects reporting multi-strategy research might be found, they are a major form of reporting findings and have the advantage that in the vast majority of cases, the peer review process provides some kind of quality control mechanism. Therefore, to construct the dataset, a content analysis of published journal articles combining qualitative and quantitative research in the following areas was conducted: sociology, social psychology, human, social and cultural geography, management and organisational behaviour, and media and cultural studies. Analysis was restricted to a ten year period, 1994-2003, and a total of 232 articles analysed. The articles were coded according to year of publication, research designs and methods used, whether qualitative/quantitative component was dominant or both methods had equal status, rationales employed for combining both types of method, actual uses of qualitative and quantitative research, country in which the research was conducted and first named author.

Description of qualitative and quantitative results related to theme 2: Modulation of treatment decisions by external influences.

Data represent information extracted from published literature meeting filtering criteria regarding quantification of among-individual variation in spatial behaviors. Information includes manuscript identifiers, descriptions of study design, as well as information directly input into a statistical meta-analysis regression framework.

Methods: This group consisted of 5 members, who split into two smaller groups to achieve the aims of the investigation in a more efficient manner. Dataset 2, involved the Pitfall trap. At the beginning of the lab, 10 plastic cups were buried in a woodlot, and 10 additional ones in highly disturbed grassland area. The design was decided by the investigators (i.e. disturbance, light, cover, and as blcoked or regression based). Upon completnig the lab, the number of insects captured in each cup were counted, and released. Finally, the number of different recognizable taxonomic units (rtus) per sample as well was calculated (i.e. flies, bees, spiders, etc). Outside Conditions: Outside Conditions: 90% shade cover, shards of sunlight coming through the spaces in the trees' canopy, slight breeze, little to no grass in the analyzed quadrats, dead maple leaves of varying colors, cool (lower than room temperature), occasional encounter of snails on plants, frequent observation of Purple Aster, and Canadian Goldenrod plants, maple leaf saplings varied in size from a bud, to a fully grown plant.

Data is included for two types of field surveys conducted for freshwater mussels in the mainstem of the middle and upper Delaware River in the Mid-Atlantic region of the United States from 2000-2002. Timed search (qualitative) surveys were conducted during 2000-2001 from a point at the confluence of the East and West Branches of the Delaware River near Hancock, NY continuously downstream to a point at the mouth of the Paulins Kill River near Columbia, NJ. In this qualitative survey, mussel species and counts were collected in the field catch-per-unit-effort (CPUE) data was determined for all mussel species within each of 1,095 consecutive stream sections ~200 m in length. Subsequent quantitative surveys were conducted in select 200-m sections of river using quadrats during 2002 in order to estimate abundance and density of mussel present in these sections. One Excel file contains data from qualitative surveys, and a second excel file contains data from quantitative quadrat surveys.

Materials from research project including transcriptions of interviews and survey data; in-depth interviews with 41 individuals from different occupations, including public sector administrators, university lecturers, social care workers, home-keepers, mature students and retirees. The semi-structured interviews consisted of two parts, lasting on average 2.25 hours. The first part asked the interviewees to recount their life history, describing the twists and turns in their lives, their personal goals and their everyday practices. In the second part, they recalled significant acts of giving and volunteering, describing their feelings and motivations. Every time interviewees mentioned emotions and morality, they were prompted to go on talking and to give illustrations. A picture emerged of how they have had to navigate their way through life, dovetailing and prioritising various moral concerns and commitments in an environment that they could not control. It is in this context that their charitable acts are understood and explained.This project is part of a programme of research being undertaken by the Centre for Giving and Philanthropy (CGAP) that seeks to investigate quantitative and qualitative perspectives of charity and social redistribution. It is the second of two, University of Southampton based projects exploring charitable redistribution in the UK. The first project comprised the building of an extensive database of UK charities to enable quantitative analysis of charities within the UK. This project takes a qualitative perspective to examine and explore, at a local level, some of the emerging themes from subsequent quantitative analysis of the Project 1 database relating to the distribution of charitable resources. (1) In-depth interviews with 41 individuals from different occupations, including public sector administrators, university lecturers, social care workers, home-keepers, mature students and retirees; (2) Focus groups and (3) Surveys.

This document contains the datasets and visualizations generated after the application of the methodology defined in our work: "A qualitative and quantitative citation analysis toward retracted articles: a case of study". The methodology defines a citation analysis of the Wakefield et al. [1] retracted article from a quantitative and qualitative point of view. The data contained in this repository are based on the first two steps of the methodology. The first step of the methodology (i.e. “Data gathering”) builds an annotated dataset of the citing entities, this step is largely discussed also in [2]. The second step (i.e. "Topic Modelling") runs a topic modeling analysis on the textual features contained in the dataset generated by the first step.

Note: the data are all contained inside the "method_data.zip" file. You need to unzip the file to get access to all the files and directories listed below.

Data gathering

The data generated by this step are stored in "data/":

"cits_features.csv": a dataset containing all the entities (rows in the CSV) which have cited the Wakefield et al. retracted article, and a set of features characterizing each citing entity (columns in the CSV). The features included are: DOI ("doi"), year of publication ("year"), the title ("title"), the venue identifier ("source_id"), the title of the venue ("source_title"), yes/no value in case the entity is retracted as well ("retracted"), the subject area ("area"), the subject category ("category"), the sections of the in-text citations ("intext_citation.section"), the value of the reference pointer ("intext_citation.pointer"), the in-text citation function ("intext_citation.intent"), the in-text citation perceived sentiment ("intext_citation.sentiment"), and a yes/no value to denote whether the in-text citation context mentions the retraction of the cited entity ("intext_citation.section.ret_mention"). Note: this dataset is licensed under a Creative Commons public domain dedication (CC0).

"cits_text.csv": this dataset stores the abstract ("abstract") and the in-text citations context ("intext_citation.context") for each citing entity identified using the DOI value ("doi"). Note: the data keep their original license (the one provided by their publisher). This dataset is provided in order to favor the reproducibility of the results obtained in our work.

Topic modeling We run a topic modeling analysis on the textual features gathered (i.e. abstracts and citation contexts). The results are stored inside the "topic_modeling/" directory. The topic modeling has been done using MITAO, a tool for mashing up automatic text analysis tools, and creating a completely customizable visual workflow [3]. The topic modeling results for each textual feature are separated into two different folders, "abstracts/" for the abstracts, and "intext_cit/" for the in-text citation contexts. Both the directories contain the following directories/files:

"mitao_workflows/": the workflows of MITAO. These are JSON files that could be reloaded in MITAO to reproduce the results following the same workflows.

"corpus_and_dictionary/": it contains the dictionary and the vectorized corpus given as inputs for the LDA topic modeling.

"coherence/coherence.csv": the coherence score of several topic models trained on a number of topics from 1 - 40.

"datasets_and_views/": the datasets and visualizations generated using MITAO.

References

Wakefield, A., Murch, S., Anthony, A., Linnell, J., Casson, D., Malik, M., Berelowitz, M., Dhillon, A., Thomson, M., Harvey, P., Valentine, A., Davies, S., & Walker-Smith, J. (1998). RETRACTED: Ileal-lymphoid-nodular hyperplasia, non-specific colitis, and pervasive developmental disorder in children. The Lancet, 351(9103), 637–641. https://doi.org/10.1016/S0140-6736(97)11096-0

Heibi, I., & Peroni, S. (2020). A methodology for gathering and annotating the raw-data/characteristics of the documents citing a retracted article v1 (protocols.io.bdc4i2yw) [Data set]. In protocols.io. ZappyLab, Inc. https://doi.org/10.17504/protocols.io.bdc4i2yw

Ferri, P., Heibi, I., Pareschi, L., & Peroni, S. (2020). MITAO: A User Friendly and Modular Software for Topic Modelling [JD]. PuntOorg International Journal, 5(2), 135–149. https://doi.org/10.19245/25.05.pij.5.2.3

The study is mixed methods research.Quantitative Data: Datasets are of sociodemographic data of women accessing cervical cancer screening at a woman's clinic. The datasets and do files can be opened in analytic software, STATA . Qualitative data: Qualitative data consists of preliminary analysis tables and reflective notes from in-depth interviews with female patients and healthcare providers. .

The quantitative data contains 1,228 conditions (rows) and 23 variables (columns). As described in the main article, some conditions are split into sub-conditions; each sub-condition is a separate line in the dataset. Detailed variable definitions are listed in the next section. Key variables of our analysis are policy areas (variable Policy) and ideological models (variable Model). The qualitative data is an Atlas.ti file. The qualitative analysis has been conducted in Atlas.ti version 7.5.18. The hermeneutic-unit (working space) has been bundled into the file IMF agriculture qualitative analysis-submission version.atlcb. See Read me file for further details.

The information in this data set are raw one on one interviews. Additionally, quantitative data output is included.

As Artificial Intelligence (AI) continues to advance and impact diverse fields, ensuring universal access to its abilities becomes increasingly crucial. To access various AI models, they must be deployed to process inference requests. We conducted qualitative and quantitative analyses of popular open-source serving frameworks by evaluating their performance on three common Machine Learning tasks. This research aims to shed more light on the frameworks’ respective strengths and weaknesses, consequently addressing the challenges posed by the process of selecting a method of serving the models. The qualitative comparison is carried out by taking into account the subjective characteristics of each framework and scoring them on a number scale. We then use Locust to run load-tests on these frameworks, log their quantitative results, and compare them with each other. Our results find that PyTorch TorchServe is the overall best-performing framework, consistently surpassing the other two in our performance test. We also found that some platforms had significant issues handling more complex models, showing incapabilities for handling specific Machine Learning tasks. Our findings show significant differences among the frameworks, contributing valuable insights for developers and researchers in selecting the most suitable framework serving Machine Learning models.

This repository contains the datasets and visualizations generated in our work: "A quantitative and qualitative citation analysis to retracted articles in the humanities domain".

Note: the data are all contained inside the data.zip file. You need to unzip the container to get access to all the files and directories listed below.

The data (citations) gathered accompanied by their annotated characteristics are stored in data/:

cits.csv: a dataset containing all the entities (rows in the CSV) which have cited a retracted article in the humanities domain. Each citing entity (row) is accompanied by a set of features (columns) that characterizes it. Note: this dataset is licensed under a Creative Commons public domain dedication (CC0).

content.csv: a dataset containing the abstracts and the in-text citation contexts of all the citing entities gathered. Note: the data keep their original license (the one provided by their publisher). This dataset is provided in order to favor the reproducibility of the results obtained in our work.

Topic modeling

We run a topic modeling analysis on the textual features gathered (i.e. abstracts and citation contexts). The results are stored inside the topic_model/ directory. The topic modeling has been done using MITAO, a tool for mashing up automatic text analysis tools and creating a completely customizable visual workflow [1]. The directory workflow/ contains the workflows used in MITAO. The topic modeling results for each textual feature are separated into two different folders, abstract/ for the abstracts, and cits_context/ for the in-text citation contexts. Both the directories contain the following directories/files:

datasets_and_views/: the datasets and visualizations generated using MITAO.

ldamodel_corpus_dict/: it contains the dictionary, the LDA topic model, and the tokenized and vectorized corpus.

rawdata/: the textual collection, metadata, and stopwords used as input in the workflow of MITAO

References

[1] Ferri, P., Heibi, I., Pareschi, L., & Peroni, S. (2020). MITAO: A User Friendly and Modular Software for Topic Modelling [JD]. PuntOorg International Journal, 5(2), 135–149. https://doi.org/10.19245/25.05.pij.5.2.3

Abstract of paper 1214 presented at the Digital Humanities Conference 2019 (DH2019), Utrecht , the Netherlands 9-12 July, 2019.

The dataset has three parts; quantitative data, transcripts of Online FGDs and Photovoice Group Discussions, and Photovoice Photographs. Quantitative data includes the outcome variable which consists of nine measures: 1) maintaining a 1-meter distance, 2) avoiding handshakes, 3) avoiding hugs, 4) avoiding public transportation, 5) working/studying from home, 6) avoiding gatherings and crowds, 7) postponing meetings, 8) avoiding visiting elderly people, and 9) praying at home. In addition, other variables in this data set are sociodemographic characteristics; COVID-19-related variables such as COVID-19 testing, knowledge of COVID-19, etc.; and religious and tradition-related activities such as breaking fast during Ramadan, joining Mudik tradition, etc. Qualitative data includes Online FGDs and Photovoice Group Discussions transcripts and Photovoice Photographs. Five Online FGDs transcripts and 10 transcripts for Photovoice. 29 Photographs of Photovoice are also available in a list.

Poster presentation at the 12th Annual Meeting of the Society for the Neurobiology of Language, 21–24 October 2020, Online, USA

From the standpoint of symbolic interactionism, human group life is a process in which objects are being created, affirmed, transformed, and cast aside. The life and action of people change in line with the changes taking place in their world of objects (Blumer, 2017). This issue is significant because when technology also includes a virtual workforce, the familiar objects in the internal environment; such as those related to job, work, and business processes, particularly standardized processes, are changed. For this paper, the focal point of the analysis will be the two schools of thought; the Chicago school and the Iowa school. The objective of the analytical paper** is to provide a brief overview of the findings from a variety of sources on symbolic interactionism; then, to identify the role, if any, of symbolic interactionism, in the hybrid (virtual offsite / traditional ‘brick and mortar’) workforce in the transnational model of organizations. The question is: Does symbolic interactionism have a role, if at all, in the hybrid (virtual offsite / traditional ‘brick and mortar’) workforce in the transnational organization? **Analytical papers “include information from a range of sources; the focus is on analyzing the different viewpoints represented from a factual rather than an opinionated standpoint” (Personal Writer, 2008). **In an analytical paper, the author poses a question, collects relevant data from other researchers, analyzes the data from their viewpoints, then concludes with a summation of findings and a suggested framework for further study (Paper Pile, 2020; Personal Writer, 2008). The author maintains a neutral position; the focus is “on the findings and conclusions of other researchers” (Paper Pile, 2020).

The file LWC.csv contains qualitative information on the presence (1) / absence (0) of Liquid water content. The file IWC.csv contains qualitative information on the presence (1) / absence (0) of Ice water content. The file LWC_values.csv contains quantitative information in gr/m3 of Liquid water content.

Socio-economic surveys, value chain analysis, system dynamics modelling. This dataset can be used in value chain analysis and for policy analysis of the cattle and beef sector in Nigeria.

This Data set including all the Variables (choice, college,hsg2, coml5, typez, fuelz, pricez, speedz, pollutionz, sizez) from 2016 to 2018.I scrapped this data from www.qed.econ.queensu.ca