The 2022 Florida Data Science for Social Good (FL-DSSG) Big Reveal event was held on August 23 at the WJCT Studios, Jacksonville, FL. The DSSG interns presented findings from the Cathedral Arts Project, League of Women Voters of Florida, and GameFace 4:13 Training Academy projects.
The 2023 Florida Data Science for Social Good (FL-DSSG) Big Reveal event was held on August 23 at the WJCT Studios, Jacksonville, FL. The DSSG interns presented findings from the Cathedral Arts Project, GrowFL, and Florida Philanthropic Network projects.
At the event, DSSG interns presented findings and revealed insights gained from the Center for Children’s Rights, Episcopal Children’s Services, and Literacy Alliance of Northeast Florida projects.
The big data hype has been gaining momentum over the past several years. Although a lot of it is hype and buzzwords, what is undeniable is that the use of data to improve decision-making can improve a lot of organizations. Despite this potential, most of the examples we hear about the use of data is in the corporate world, especially in finance, internet search, and advertising. In this talk, I’ll talk about the potential of using data for social good. I’ll give several examples from the Data Science for Social Good Summer Fellowship at the University of Chicago that highlight how data science can be used to solve large-scale problems with social impact in areas such as education, healthcare, sustainability, community development, and disaster relief. I’ll highlight some of the projects related to education and discuss how data scientists have the potential some of these most challenging problems.
2018 Florida Data Science for Social Good (FL-DSSG) Big Reveal PresentationKarthikeyan Umapathy
At the 2018 Big Reveal event, FL-DSSG interns presented findings and revealed insights gained from the Baptist Health, Family Support Services, Girls Inc. of Jacksonville, and Performers Academy projects. 2018 FL-DSSG Internship program was funded by the Nonprofit Center for Northeast Florida and the University of North Florida. 2018 Big Reveal event was sponsored by AgileThought, Tampa based software consulting firm. Big Reveal presentations were held at the WJCT Studio A, 100 Festival Park Ave., Jacksonville, FL - 32202. For more information about the 2018 FL-DSSG program visit http://dssg.unf.edu/2018program.html.
FL-DSSG Big Reveal Event was held on August 17th, 2021, from 4:30 PM to 6:30 PM as a Zoom webinar event. At the event, DSSG interns presented findings and revealed insights gained from the Barnabas Center, League of Women Voters of Florida, and Jewish Family and Community Services data science projects.
Invited speech at the Hearing of the European Parliament on "Promoting online education and research across national borders" in Paris on 5th of Decmber 2022 by Dr. Christian M. Stracke
2019 Florida Data Science for Social Good (FL-DSSG) Big RevealKarthikeyan Umapathy
At the 2019 Big Reveal event, FL-DSSG interns presented findings and revealed insights gained from the Cathedral Arts Project, Children's Services Council, Feeding Northeast Florida, GTM Research Reserve, and Starting Point Behavioral Healthcare projects. The UNF Foundation funded 2019 FL-DSSG Internship program. Big Reveal presentations were held at the WJCT Studio A, 100 Festival Park Ave., Jacksonville, FL - 32202. For more information about the 2019 FL-DSSG program visit http://dssg.unf.edu/2019program.html.
The 2023 Florida Data Science for Social Good (FL-DSSG) Big Reveal event was held on August 23 at the WJCT Studios, Jacksonville, FL. The DSSG interns presented findings from the Cathedral Arts Project, GrowFL, and Florida Philanthropic Network projects.
At the event, DSSG interns presented findings and revealed insights gained from the Center for Children’s Rights, Episcopal Children’s Services, and Literacy Alliance of Northeast Florida projects.
The big data hype has been gaining momentum over the past several years. Although a lot of it is hype and buzzwords, what is undeniable is that the use of data to improve decision-making can improve a lot of organizations. Despite this potential, most of the examples we hear about the use of data is in the corporate world, especially in finance, internet search, and advertising. In this talk, I’ll talk about the potential of using data for social good. I’ll give several examples from the Data Science for Social Good Summer Fellowship at the University of Chicago that highlight how data science can be used to solve large-scale problems with social impact in areas such as education, healthcare, sustainability, community development, and disaster relief. I’ll highlight some of the projects related to education and discuss how data scientists have the potential some of these most challenging problems.
2018 Florida Data Science for Social Good (FL-DSSG) Big Reveal PresentationKarthikeyan Umapathy
At the 2018 Big Reveal event, FL-DSSG interns presented findings and revealed insights gained from the Baptist Health, Family Support Services, Girls Inc. of Jacksonville, and Performers Academy projects. 2018 FL-DSSG Internship program was funded by the Nonprofit Center for Northeast Florida and the University of North Florida. 2018 Big Reveal event was sponsored by AgileThought, Tampa based software consulting firm. Big Reveal presentations were held at the WJCT Studio A, 100 Festival Park Ave., Jacksonville, FL - 32202. For more information about the 2018 FL-DSSG program visit http://dssg.unf.edu/2018program.html.
FL-DSSG Big Reveal Event was held on August 17th, 2021, from 4:30 PM to 6:30 PM as a Zoom webinar event. At the event, DSSG interns presented findings and revealed insights gained from the Barnabas Center, League of Women Voters of Florida, and Jewish Family and Community Services data science projects.
Invited speech at the Hearing of the European Parliament on "Promoting online education and research across national borders" in Paris on 5th of Decmber 2022 by Dr. Christian M. Stracke
2019 Florida Data Science for Social Good (FL-DSSG) Big RevealKarthikeyan Umapathy
At the 2019 Big Reveal event, FL-DSSG interns presented findings and revealed insights gained from the Cathedral Arts Project, Children's Services Council, Feeding Northeast Florida, GTM Research Reserve, and Starting Point Behavioral Healthcare projects. The UNF Foundation funded 2019 FL-DSSG Internship program. Big Reveal presentations were held at the WJCT Studio A, 100 Festival Park Ave., Jacksonville, FL - 32202. For more information about the 2019 FL-DSSG program visit http://dssg.unf.edu/2019program.html.
Research is My Right: Building a Nation of Knowledge | Ar. Balaji Venkatachar...Archiloop India Foundation
Archiloop India Foundation | June 21, 2020
"Ar. Balaji Venkatachary serves as an Associate Professor at Mysore School of Architecture in Karnataka. He is trained as an Architect and Conservator from Anna University and School of Planning and Architecture, New Delhi respectively. His research interests include Cultural landscapes and Traditional Knowledge Systems.
He has contributed as a freelance consultant to various projects in the interest of heritage such as Heritage Impact Assessment for Hyderabad Golf Course at Golconda, Listing and documentation of Historic buildings in Chennai, Energy Audit studies for traditional bangle industry in Firozabad to mention a few. His prior assignments include his involvement in design projects such as resorts, commercial complexes and office spaces in Delhi and the Kingdom of Bahrain.
Prior to the current assignment, he has taught in reputed schools of Architecture in Tamil Nadu and has served a term as the Head of the Department of Architecture in GIA, Kerala. As part of his fellowship at SPA, Bhopal, he has taught postgraduate courses in the Department of Conservation and has contributed to the conservation and research projects at the Centre for Cultural Knowledge system (CCKS).
His published works include papers on Cultural Landscapes, Use of GIS for landscape analysis and Discourse on Aesthetics in Architecture. He has been developing and conducting workshops on subjects such as ‘Site Design’, ‘Climatology’ and ‘Heritage Documentation’ for university teachers and students through various regional and national forums including for the Training and Research Centre, Council of Architecture. He is currently working on the research, “Role of Music in shaping Cultural Landscapes: Case of Kaveri basin” towards his PhD from the School of Planning and Architecture, Bhopal."
Webinar Video:- https://youtu.be/ydsVPGTpBcA
Presentation: - https://bit.ly/3debzjO
Get Connected
Instagram:- https://bit.ly/2PBEGEm
YouTube:- https://bit.ly/2ZD3y1o
Facebook:- https://bit.ly/3jnwP7Q
LinkedIn:- https://bit.ly/3u0VbsO
Twitter:- https://bit.ly/3curGtf
Our Global network of attendees:- https://bit.ly/31rZHnK
#stayintheloop #archiloopindia #AIF
Archiloop India Foundation
contactus@archiloopindia.in
www.archiloopindia.in
This presentation was provided by Martha Kyrillidou of QualityMetrics LLC and served as the full slide deck throughout the course of our Fall training series "Research Methods and Tools." The program was held from October 11, 2022 - December 13, 2022.
Global Smart Education (GSE) Conference 2022 in Beijing, China: Invited Keynote on "Learning Quality, Artificial Intelligence and Ethics" hold by Christian M. Stracke (Germany), live streamed online and in the national TV programme in China
California ZTC Degrees Panel: Past, Present, and FutureUna Daly
Online Teaching Conference 2020: Twenty-six California Community Colleges embarked on a journey to create thirty-four Zero Textbook Cost (ZTC) Degrees to dramatically reduce the financial burden of earning an associate degree or career technical education certificate. More than 20,000 students over three years would benefit from this approach to eliminating the barrier of textbook costs. Data collected from participating colleges show that all students in ZTC pathways did better than those in non-ZTC courses, and that traditionally underserved populations did even better.
With proven results of reducing equity gaps, the Governor has proposed doubling the initial $5 million ZTC program to $10 million in FY21, opening this opportunity to more colleges wishing to leverage ZTCs to increase student achievement and reduce equity gaps. Join us to hear from ZTC champions who led the initiative, supporting the faculty who transformed their courses to lower barriers and improve students learning, and ensuring the sustainability of the program. Consider how to integrate a ZTC approach with your distance education, equity, pathways and other student success-centered initiatives. Learn about how students and librarians are poised to play an essential role in the proposed $10 million grant. Finally, learn the critical steps for success and how to assess your college’s readiness for developing ZTC degrees.
Data Management and Broader Impacts: a holistic approachMegan O'Donnell
[please download to view at full resolution]
The National Science Foundation’s (NSF) Broader Impacts Criterion asks scientists to frame their research beyond “science for science’s sake.” Examining data and data management through a Broader Impacts lens highlights the benefits of good data management, data management plans (DMPs), and strengthens the argument for better Data Information Literacy (DIL) in the sciences.
Promising Developments in Edtech for ScienceJohn Terada
We are releasing “Promising Developments in Edtech for Science”, a summary report of our findings and the lessons learned from the Science Learning Challenge market research and cohort experience. The report compiles the key insights we’ve gleaned, and presents them in three sections: why science education matters, challenges facing K-12 science learning, and opportunities for edtech to support science learning.
We analyzed voter registration and elections data released by the Florida Division of Elections to investigate the profile of Florida voter participation. We utilized data associated with general elections from 2012 to 2020. We merged an individual’s January 2021 voter registration data with elections data for above listed years. Several data preparation issues were resolved during the data merging process, including exact duplicates, multiple associated vote types, and misclassified vote types. The merged data consisted of the following columns: voter ID, registration county code, zip code, sex, ethnicity, age, [2012 to 2020] vote type, [2012 to 2020] voting indicator, and [2012 to 2020] county code. As it is computationally intensive to process data of entire Florida voters, county-wise data were merged into associated metropolitan, micropolitan, and rural areas (MSA). Based on voter eligibility and total vote counts on each general election held between 2012 and 2020, voters were classified into the following profile categories: always-voted (participated in all elections), increasing-in-voting (participated in recent elections but not in the past elections), intermittent-in-voting (participated in some elections but not all), decreasing-in-voting (participated past elections but not recently), never-voted (didn’t participate in the elections), and not-eligible (registered but under 18 years of age). Our analysis indicates that there is a considerable number of never-voted individuals regardless of MSA regions. Profile analysis reveals that metropolitan and micropolitan regions tend to have more individuals categorized as increasing-in-voting than always-voted. In contrast, rural regions tend to have more individuals categorized as always-voted than increasing-in-voting.
This workshop will introduce some of the main principles and techniques of Social Network Analysis (SNA). We will use examples from organizational and social media-based networks to understand concepts such as network density, diameter, centrality measures, community detection algorithms, etc. The session will also introduce Gephi, a popular program for SNA. Gephi is a free and open-source tool that is available for both Mac and PC computers.
By the end of the session, you will develop a general understanding of what SNA is, what research questions it can help you answer, and how it can be applied to your own research. You will also learn how to use Gephi to visualize and examine networks using various layout and community detection algorithms.
Instructor’s Bio: Dr. Anatoliy Gruzd is a Canada Research Chair in Social Media Data Stewardship, Associate Professor at the Ted Rogers School of Management at Ryerson University, and Director of Research at the Social Media Lab. Anatoliy is also a Member of the Royal Society of Canada’s College of New Scholars, Artists and Scientists; a co-editor of a multidisciplinary journal on Big Data and Society; and a founding co-chair of the International Conference on Social Media and Society. His research initiatives explore how social media platforms are changing the ways in which people and organizations communicate, collaborate and disseminate information and how these changes impact the norms and structures of modern society.
Layering Common Sense on Top of all that Rocket Science by Prof. Sharon Dunwoodywkwsci-research
Presented during the WKWSCI Symposium 2014
21 March 2014
Marina Bay Sands Expo and Convention Centre
Organized by the Wee Kim Wee School of Communication and Information at Nanyang Technological University
A Systematic Review of Affordable Homeownership using Data Science MethodsKarthikeyan Umapathy
Interest in the global unaffordable housing dilemma is manifest in its growing publications. However, there is a limited systematic review of the literature concerning data science approaches to address the social issues of owning affordable homes through Housing and Urban Development (HUD) programs. The systematic literature review was performed using Google Scholar and followed the phases prescribed in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). This study synthesizes data sources, tools, analytical approaches, and theoretical frameworks from the literature on affordable housing issues using data science methods. Our findings indicate that researchers have approached the issue completely differently from each other, with census data and usage of mapping visualizations as being a common trend.
This webinar will discuss the special needs of digital humanities researchers and help you learn how to talk them about their information management needs.
Topics that will be covered:
What is humanities data?
What special considerations are involved in creating DMPs for humanities data?
Where can you store humanities data?
What will humanities funding agencies be looking for? What regulations apply to humanities data (e.g., data sharing, data management, data availability)?
What librarians should know before meeting with a humanist; how humanists differ from other researchers in the way they think about their version of data.
Cross Pollination: Sharing Ideas and Information Across InstitutionsESD UNU-IAS
Cross Pollination: Sharing Ideas and Information Across Institutions
Aditya G. Desai and Audrey Anne Rader (RCE Greater Atlanta)
11th Americas Regional RCE Meeting
4 October, 2022
Introduction to NSF-sponsored Big Data Education ProjectBig Data Education
Date: 2015-12-11
Presenter: Eun-Kyeong Kim (eun-kyeong.kim@psu.edu)
Symposium: The 17th KOCSEA (Korean Computer Scientists and Engineers Association in America) Technical Symposium 2015
Systematic Literature Review and Research Model to Examine Data Analytics Ado...Karthikeyan Umapathy
Data analytics offers a wide variety of opportunities across all industries enabling improvements in all business operations. Data analytics adoption has several associated complexities making it cumbersome and challenging for organizations. In particular, small and medium businesses (SMB) and nonprofit organizations lag behind data analytics adoption, even though they are crucial for the economy and would benefit most from data-driven decisions. This paper aims to identify factors that influence data analytics adoption by organizations. We conduct a systematic literature review to identify articles relevant to data analytics adoption studies performed using survey methodology. We synthesize literature review results to propose a research model to investigate data analytics adoption in small & medium businesses and nonprofit organizations. The proposed research model was developed primarily based on Technology Organization Environment (TOE) framework, combined with other factors relevant to data analytics adoption found in the literature. The research model investigates the influences of data analytics, organization, and environment characteristics on data analytics adoption by SMBs and nonprofits. We hope that further progress with this research will provide insights into helping SMBs and nonprofits adopt data analytics technologies.
In this research, we analyzed voter registration and elections data re-leased by the Florida Division of Elections to investigate the profile of Florida voter participation. The utilized data was associated with federal general elec-tions from 2014 to 2020. Data preparation issues were resolved during the data merging, including exact duplicates, multiple associated vote types, and misclas-sified vote types. The merged data consisted of voter ID, registration county code, zip code, sex, ethnicity, age, vote type for each general election year, voting in-dicator for each general election year, and county code. Boosted Tree model (with a misclassification rate of 0.22) identified zip code, age, and voter status are key factors that influence voter participation. Based on voter eligibility and total vote counts in each general election held between 2014 and 2020, voters were classi-fied into the following profile categories: always-voted (participated in all elec-tions), increasing-in-voting (participated in recent elections but not in the past elections), intermittent-in-voting (participated in some elections but not all), de-creasing-in-voting (participated past elections but not recently), never-voted (didn’t participate in the elections), and not-eligible (registered but under 18 years of age). Voter profile counts information was merged with Census demo-graphic information at the zip code level. To find insights into the voter profiles, we created Tableau dashboards to view voter profiles, voting methods, and the effect of census variables on voter turnout at the zip code level. We hope this dashboard helps organizations like the League of Women Voters of Florida target their voter participation and engagement activities at the zip code level.
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Research is My Right: Building a Nation of Knowledge | Ar. Balaji Venkatachar...Archiloop India Foundation
Archiloop India Foundation | June 21, 2020
"Ar. Balaji Venkatachary serves as an Associate Professor at Mysore School of Architecture in Karnataka. He is trained as an Architect and Conservator from Anna University and School of Planning and Architecture, New Delhi respectively. His research interests include Cultural landscapes and Traditional Knowledge Systems.
He has contributed as a freelance consultant to various projects in the interest of heritage such as Heritage Impact Assessment for Hyderabad Golf Course at Golconda, Listing and documentation of Historic buildings in Chennai, Energy Audit studies for traditional bangle industry in Firozabad to mention a few. His prior assignments include his involvement in design projects such as resorts, commercial complexes and office spaces in Delhi and the Kingdom of Bahrain.
Prior to the current assignment, he has taught in reputed schools of Architecture in Tamil Nadu and has served a term as the Head of the Department of Architecture in GIA, Kerala. As part of his fellowship at SPA, Bhopal, he has taught postgraduate courses in the Department of Conservation and has contributed to the conservation and research projects at the Centre for Cultural Knowledge system (CCKS).
His published works include papers on Cultural Landscapes, Use of GIS for landscape analysis and Discourse on Aesthetics in Architecture. He has been developing and conducting workshops on subjects such as ‘Site Design’, ‘Climatology’ and ‘Heritage Documentation’ for university teachers and students through various regional and national forums including for the Training and Research Centre, Council of Architecture. He is currently working on the research, “Role of Music in shaping Cultural Landscapes: Case of Kaveri basin” towards his PhD from the School of Planning and Architecture, Bhopal."
Webinar Video:- https://youtu.be/ydsVPGTpBcA
Presentation: - https://bit.ly/3debzjO
Get Connected
Instagram:- https://bit.ly/2PBEGEm
YouTube:- https://bit.ly/2ZD3y1o
Facebook:- https://bit.ly/3jnwP7Q
LinkedIn:- https://bit.ly/3u0VbsO
Twitter:- https://bit.ly/3curGtf
Our Global network of attendees:- https://bit.ly/31rZHnK
#stayintheloop #archiloopindia #AIF
Archiloop India Foundation
contactus@archiloopindia.in
www.archiloopindia.in
This presentation was provided by Martha Kyrillidou of QualityMetrics LLC and served as the full slide deck throughout the course of our Fall training series "Research Methods and Tools." The program was held from October 11, 2022 - December 13, 2022.
Global Smart Education (GSE) Conference 2022 in Beijing, China: Invited Keynote on "Learning Quality, Artificial Intelligence and Ethics" hold by Christian M. Stracke (Germany), live streamed online and in the national TV programme in China
California ZTC Degrees Panel: Past, Present, and FutureUna Daly
Online Teaching Conference 2020: Twenty-six California Community Colleges embarked on a journey to create thirty-four Zero Textbook Cost (ZTC) Degrees to dramatically reduce the financial burden of earning an associate degree or career technical education certificate. More than 20,000 students over three years would benefit from this approach to eliminating the barrier of textbook costs. Data collected from participating colleges show that all students in ZTC pathways did better than those in non-ZTC courses, and that traditionally underserved populations did even better.
With proven results of reducing equity gaps, the Governor has proposed doubling the initial $5 million ZTC program to $10 million in FY21, opening this opportunity to more colleges wishing to leverage ZTCs to increase student achievement and reduce equity gaps. Join us to hear from ZTC champions who led the initiative, supporting the faculty who transformed their courses to lower barriers and improve students learning, and ensuring the sustainability of the program. Consider how to integrate a ZTC approach with your distance education, equity, pathways and other student success-centered initiatives. Learn about how students and librarians are poised to play an essential role in the proposed $10 million grant. Finally, learn the critical steps for success and how to assess your college’s readiness for developing ZTC degrees.
Data Management and Broader Impacts: a holistic approachMegan O'Donnell
[please download to view at full resolution]
The National Science Foundation’s (NSF) Broader Impacts Criterion asks scientists to frame their research beyond “science for science’s sake.” Examining data and data management through a Broader Impacts lens highlights the benefits of good data management, data management plans (DMPs), and strengthens the argument for better Data Information Literacy (DIL) in the sciences.
Promising Developments in Edtech for ScienceJohn Terada
We are releasing “Promising Developments in Edtech for Science”, a summary report of our findings and the lessons learned from the Science Learning Challenge market research and cohort experience. The report compiles the key insights we’ve gleaned, and presents them in three sections: why science education matters, challenges facing K-12 science learning, and opportunities for edtech to support science learning.
We analyzed voter registration and elections data released by the Florida Division of Elections to investigate the profile of Florida voter participation. We utilized data associated with general elections from 2012 to 2020. We merged an individual’s January 2021 voter registration data with elections data for above listed years. Several data preparation issues were resolved during the data merging process, including exact duplicates, multiple associated vote types, and misclassified vote types. The merged data consisted of the following columns: voter ID, registration county code, zip code, sex, ethnicity, age, [2012 to 2020] vote type, [2012 to 2020] voting indicator, and [2012 to 2020] county code. As it is computationally intensive to process data of entire Florida voters, county-wise data were merged into associated metropolitan, micropolitan, and rural areas (MSA). Based on voter eligibility and total vote counts on each general election held between 2012 and 2020, voters were classified into the following profile categories: always-voted (participated in all elections), increasing-in-voting (participated in recent elections but not in the past elections), intermittent-in-voting (participated in some elections but not all), decreasing-in-voting (participated past elections but not recently), never-voted (didn’t participate in the elections), and not-eligible (registered but under 18 years of age). Our analysis indicates that there is a considerable number of never-voted individuals regardless of MSA regions. Profile analysis reveals that metropolitan and micropolitan regions tend to have more individuals categorized as increasing-in-voting than always-voted. In contrast, rural regions tend to have more individuals categorized as always-voted than increasing-in-voting.
This workshop will introduce some of the main principles and techniques of Social Network Analysis (SNA). We will use examples from organizational and social media-based networks to understand concepts such as network density, diameter, centrality measures, community detection algorithms, etc. The session will also introduce Gephi, a popular program for SNA. Gephi is a free and open-source tool that is available for both Mac and PC computers.
By the end of the session, you will develop a general understanding of what SNA is, what research questions it can help you answer, and how it can be applied to your own research. You will also learn how to use Gephi to visualize and examine networks using various layout and community detection algorithms.
Instructor’s Bio: Dr. Anatoliy Gruzd is a Canada Research Chair in Social Media Data Stewardship, Associate Professor at the Ted Rogers School of Management at Ryerson University, and Director of Research at the Social Media Lab. Anatoliy is also a Member of the Royal Society of Canada’s College of New Scholars, Artists and Scientists; a co-editor of a multidisciplinary journal on Big Data and Society; and a founding co-chair of the International Conference on Social Media and Society. His research initiatives explore how social media platforms are changing the ways in which people and organizations communicate, collaborate and disseminate information and how these changes impact the norms and structures of modern society.
Layering Common Sense on Top of all that Rocket Science by Prof. Sharon Dunwoodywkwsci-research
Presented during the WKWSCI Symposium 2014
21 March 2014
Marina Bay Sands Expo and Convention Centre
Organized by the Wee Kim Wee School of Communication and Information at Nanyang Technological University
A Systematic Review of Affordable Homeownership using Data Science MethodsKarthikeyan Umapathy
Interest in the global unaffordable housing dilemma is manifest in its growing publications. However, there is a limited systematic review of the literature concerning data science approaches to address the social issues of owning affordable homes through Housing and Urban Development (HUD) programs. The systematic literature review was performed using Google Scholar and followed the phases prescribed in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). This study synthesizes data sources, tools, analytical approaches, and theoretical frameworks from the literature on affordable housing issues using data science methods. Our findings indicate that researchers have approached the issue completely differently from each other, with census data and usage of mapping visualizations as being a common trend.
This webinar will discuss the special needs of digital humanities researchers and help you learn how to talk them about their information management needs.
Topics that will be covered:
What is humanities data?
What special considerations are involved in creating DMPs for humanities data?
Where can you store humanities data?
What will humanities funding agencies be looking for? What regulations apply to humanities data (e.g., data sharing, data management, data availability)?
What librarians should know before meeting with a humanist; how humanists differ from other researchers in the way they think about their version of data.
Cross Pollination: Sharing Ideas and Information Across InstitutionsESD UNU-IAS
Cross Pollination: Sharing Ideas and Information Across Institutions
Aditya G. Desai and Audrey Anne Rader (RCE Greater Atlanta)
11th Americas Regional RCE Meeting
4 October, 2022
Introduction to NSF-sponsored Big Data Education ProjectBig Data Education
Date: 2015-12-11
Presenter: Eun-Kyeong Kim (eun-kyeong.kim@psu.edu)
Symposium: The 17th KOCSEA (Korean Computer Scientists and Engineers Association in America) Technical Symposium 2015
Systematic Literature Review and Research Model to Examine Data Analytics Ado...Karthikeyan Umapathy
Data analytics offers a wide variety of opportunities across all industries enabling improvements in all business operations. Data analytics adoption has several associated complexities making it cumbersome and challenging for organizations. In particular, small and medium businesses (SMB) and nonprofit organizations lag behind data analytics adoption, even though they are crucial for the economy and would benefit most from data-driven decisions. This paper aims to identify factors that influence data analytics adoption by organizations. We conduct a systematic literature review to identify articles relevant to data analytics adoption studies performed using survey methodology. We synthesize literature review results to propose a research model to investigate data analytics adoption in small & medium businesses and nonprofit organizations. The proposed research model was developed primarily based on Technology Organization Environment (TOE) framework, combined with other factors relevant to data analytics adoption found in the literature. The research model investigates the influences of data analytics, organization, and environment characteristics on data analytics adoption by SMBs and nonprofits. We hope that further progress with this research will provide insights into helping SMBs and nonprofits adopt data analytics technologies.
In this research, we analyzed voter registration and elections data re-leased by the Florida Division of Elections to investigate the profile of Florida voter participation. The utilized data was associated with federal general elec-tions from 2014 to 2020. Data preparation issues were resolved during the data merging, including exact duplicates, multiple associated vote types, and misclas-sified vote types. The merged data consisted of voter ID, registration county code, zip code, sex, ethnicity, age, vote type for each general election year, voting in-dicator for each general election year, and county code. Boosted Tree model (with a misclassification rate of 0.22) identified zip code, age, and voter status are key factors that influence voter participation. Based on voter eligibility and total vote counts in each general election held between 2014 and 2020, voters were classi-fied into the following profile categories: always-voted (participated in all elec-tions), increasing-in-voting (participated in recent elections but not in the past elections), intermittent-in-voting (participated in some elections but not all), de-creasing-in-voting (participated past elections but not recently), never-voted (didn’t participate in the elections), and not-eligible (registered but under 18 years of age). Voter profile counts information was merged with Census demo-graphic information at the zip code level. To find insights into the voter profiles, we created Tableau dashboards to view voter profiles, voting methods, and the effect of census variables on voter turnout at the zip code level. We hope this dashboard helps organizations like the League of Women Voters of Florida target their voter participation and engagement activities at the zip code level.
Identifying Communities with Opportunities for Positive Youth DevelopmentKarthikeyan Umapathy
Game Face 4:13 Training Academy is a strategic camp developed by Mrs. Ashanti Jackson that exists to develop basketball skills, academic excellence, and ethical character within young people in the Jacksonville community. To identify the areas where GameFace can offer its programs, we collected data from the Census, Florida Department of Juvenile Justice, Florida Department of Health, Duval County Public Schools, Food Deserts, and Churches with Food Banks. We performed Factor Analysis and Correlation Analysis on the gathered data. We utilized the statistical analysis results to create a geographic information systems decision tool using Tableau.
Based on our analysis, we understand that youths are facing major issues in Duval County are Juvenile Arrests and Disciplinary Actions within schools. Zip Codes 32210, 32209, and 32208 have a higher number of all the issues analyzed. Game Face is on the right track to providing Physical, Mental, and Spiritual Training to youth in Duval County as these would help tackle these issues and create a positive impact on the lives of youth. We recommend Game Face collaborate with schools and churches in these communities to set up their training camp. We recommend Game Face gather data on youth involvement in training, leadership coaching, and healthy habits programs. We recommend Game Face to gather data related to student academic outcomes beyond Game Face training, such as college scholarships and high school graduations.
Longitudinal Study on the Generational Impacts of Habitat for Humanity: A Res...Karthikeyan Umapathy
Habitat for Humanity addresses the challenging social issue of providing affordable housing to income-constrained families. There isn’t much research on the generational impact of affordable homeownership on the families served by Habitat. In this research, we propose a longitudinal research design that will collect and analyze data gathered from families who received affordable housing. This study will be performed as a collaborative inquiry with a partnership from HabiJax, Jacksonville, FL, affiliated with Habitat for Humanity. We will be conducting semi-structured interviews focused on education, employment, wealth building, safety, neighborhood, health, and critical life-changing impacts. We will be collecting data every 5 years over the next 30 years. Collected data would be analyzed to identify the generational impacts of affordable housing. We will be sharing the findings with HabiJax decision-makers who could improve program strategies.
Dashboard for Extracting Regional Insights and Ranking Food Deserts in Northe...Karthikeyan Umapathy
2019 Florida Data Science for Social Good (FL-DSSG) Feeding Northeast Florida project results presented as a poster at the University of North Florida (UNF) Digital Humanities Initiative (DHI) Digital Projects Showcase event on November, 15, 2019.
Developing a GIS Dashboard Tool to Inform Non-Profit Hospitals of Community H...Karthikeyan Umapathy
Slide deck for the paper presented at the 2019 Conference on Information Systems Applied Research (CONISAR), Cleveland, OH, on November 8, 2019.
The objective of this paper is to describe the methods used to develop geographic information systems (GIS) dashboard tool and explain how it can assist nonprofit hospitals to identify priority neighborhoods. Multiple data sources from the 500 Cities Project databases were analyzed, and two online dashboards were created. The first dashboard is a hospital-specific composite dashboard, and the second is a comparison dashboard of health outcomes identified by both the hospital and the county’s community health needs assessment focused on neighborhood-level disparities. Hospital-specific health outcomes were Stroke, Diabetes, and Coronary Heart Disease. County-specific health outcomes were Obesity, Dental, and Mental Health. All of the six health outcomes were standardized, rescaled, and weighted within the final composite score. Tableau was used for developing the dashboards and geographically mapping the analyzed data. The maps were developed specifically for a large hospital in Florida; however, this methodology can be utilized by other hospitals across the US. City-specific data is essential to ensure the accuracy of community health needs. The development of an interactive, comprehensive map using Tableau is a useful tool for visualizing target neighborhoods for community health outreach. The integration of community needs assessment findings into the development of composite scores allows hospitals in the US to use this tool to inform community health outreach strategy adequately.
Collaborative Community Engagement: Bringing Data Science to Societal Challen...Karthikeyan Umapathy
The collaborative community engagement triad model involves a partnership between the university, private, and nonprofit sectors to enhance the student learning experience while creating community impacts. This talk will introduce the triad model, and describe how it was implemented at the College of Computing at the University of North Florida under the Data Science for the Social Good (DSSG) umbrella. The talk will describe the challenges faced, how they were addressed, and the solutions developed in response. The triad model and the outcomes from the model will be demonstrated with example implementations from a capstone that leads to students producing software and other artifacts incorporating data science techniques in response to important societal problems. The talk will also discuss questions of scaling such efforts, and the next steps in the journey at the University of North Florida.
Security and User Experience: A Holistic Model for CAPTCHA Usability IssuesKarthikeyan Umapathy
CAPTCHA is a widely adopted security measure on the Web and is designed to effectively distinguish humans and bots by exploiting human’s ability to recognize patterns that an automated bot is incapable of. To counter this, bots are being designed to recognize patterns in CAPTCHAs. As a result, CAPTCHAs are now being designed to maximize the difficulty for bots to pass human interaction proof tests, while making it quite an arduous task even for humans as well. The approachability of CAPTCHA is increasingly being questioned because of the inconvenience it causes to legitimate users. Irrespective of the popularity, CAPTCHA is indispensable if one wants to avoid potential security threats. We investigated the usability issues associated with CAPTCHA. We built a holistic model by identifying the important concepts associated with CAPTCHAs and its usability. This model can be used as a guide for the design and evaluation of CAPTCHAs.
Florida Data Science for Social Good (FL-DSSG) Big Reveal event was held on August 7 (Monday) from 4:30 PM to 6:30 PM at the Nonprofit Center (40 E Adams St., Jacksonville). At the event, FL-DSSG interns presented findings and revealed insights gained from the Mayo Clinic, Changing Homelessness, and Yoga 4 Change projects.
A Research Plan to Study Impact of a Collaborative Web Search Tool on Novice'...Karthikeyan Umapathy
In the past decade, research efforts dedicated to studying the process of collaborative web search have been on the rise. Yet, limited number of studies have examined the impact of collaborative information search process on novice’s query behaviors. Studying and analyzing factors that influence web search behaviors, specifically users’ patterns of queries when using collaborative search systems can help with making query suggestions for group users. Improvements in user query behaviors and system query suggestions help in reducing search time and increasing query success rates for novices. In this paper, we present an empirical study plan designed to investigate the influence of collaboration between experts and novices as well as use of a collaborative web search tool on novice’s query behavior. In this research-in-progress study, we intend to use SearchTeam as our collaborative search tool. The results of this study are expected to provide information that could help collaborative web search tool designers to find ways to improve the query suggestions feature for group users. Additionally, this study will test the hypothesis that – having domain experts working with non-experts using collaborative search systems would immensely increase the query success rates for non-expert users, and help them learn querying strategies over the course of time. If the above hypothesis is proven, then use of collaborative web search tools during training of interns would be highly recommended.
Leveraging Service Computing and Big Data Analytics for E-CommerceKarthikeyan Umapathy
Panel discussions on Leveraging Service Computing and Big Data Analytics for E-Commerce at the Workshop on e-Business (WeB) 2015 held on December 12, 2015 at Fort Worth, Texas, USA.
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
StarCompliance is a leading firm specializing in the recovery of stolen cryptocurrency. Our comprehensive services are designed to assist individuals and organizations in navigating the complex process of fraud reporting, investigation, and fund recovery. We combine cutting-edge technology with expert legal support to provide a robust solution for victims of crypto theft.
Our Services Include:
Reporting to Tracking Authorities:
We immediately notify all relevant centralized exchanges (CEX), decentralized exchanges (DEX), and wallet providers about the stolen cryptocurrency. This ensures that the stolen assets are flagged as scam transactions, making it impossible for the thief to use them.
Assistance with Filing Police Reports:
We guide you through the process of filing a valid police report. Our support team provides detailed instructions on which police department to contact and helps you complete the necessary paperwork within the critical 72-hour window.
Launching the Refund Process:
Our team of experienced lawyers can initiate lawsuits on your behalf and represent you in various jurisdictions around the world. They work diligently to recover your stolen funds and ensure that justice is served.
At StarCompliance, we understand the urgency and stress involved in dealing with cryptocurrency theft. Our dedicated team works quickly and efficiently to provide you with the support and expertise needed to recover your assets. Trust us to be your partner in navigating the complexities of the crypto world and safeguarding your investments.
tapal brand analysis PPT slide for comptetive data
2022 Florida Data Science for Social Good (FL-DSSG) Big Reveal Slides
1. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
1
Data Science Meets Community
Impact
2. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
2
FL-DSSG Team
Program Directors
Dr. Dan Richard
Associate Professor of Psychology,
University of North Florida (UNF)
Dr. Karthikeyan Umapathy
Associate Professor of Computing,
University of North Florida (UNF)
Advisory Board Members
Arri Landsman-Roos
Vice President of Decision Science
Jacksonville Jaguars
Matt Berseth
Co-Founder and
Chief Information Officer
NLP Logix
3. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
3
Katie Bakewell
Modeling and Analytics Team Lead
NLP Logix
Victor C. Li
Quantitative Research Manager
Jacksonville Jaguars
Andrew Pantazi
Founding Editor
The Tributary: A Northeast
Florida Journalism Collective
Chad Gardner
Data Engineer
BlocPower
Industry Sherpas
Mary Sheridan
Modeling & Analytics Team Lead
NLP Logix
Harsh Vora
Senior Data Scientist
Crowley
Jay Lewis
Director of Strategy and Analytics
Dictionary.com
Laurel Wainwright
Environmental Services,
JEA
4. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
4
Dr. Georgette Dumont
Political Science & Public
Administration, UNF
Dr. Beyza Aslan
Mathematics & Statistics, UNF
Dr. Gordon Ratika
Anthropology, UNF
Faculty Leads
Dr. Xudong Liu
Computing, UNF
Dr. Amanda Pascale
Higher Education Administration,
UNF
Dr. Sandeep Reddivari
Computing, UNF
Dr. Michelle DeDeo
Mathematics & Statistics, UNF
Special thanks to Dr. Mike Binder (Political
Science)
Dr. Kristi Sweeney
Sport Management,
UNF
Dr. Haiyan Huang
Computer Information Systems
Flagler College
Dr. Brian J. Fisak Jr.
Clinical Psychology, UCF
Dr. Lakshmi Goel
Information Systems and
Business Analytics, UNF
5. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
5
2022 FL-DSSG Interns
Mahmoud Elbatouty
Data Science,
Bachelor of Science,
UNF
Brian Ferdman
Data Science,
Master of Science Student,
UWF
Sara Milligan
Psychology
Doctor of Philosophy Student,
USF
Abhishek Pancholi
Business Analytics and Information Systems,
Master of Science Student,
USF
Adhithyan Rangarajan
Business Analytics and Information Systems,
Master of Science Student,
USF
Minakshi Sharma
Epidemiology,
Master of Public Health Student,
UNF
6. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
6
Summer
internship
program open to
all UNF students
(undergraduate
and graduate)
Social Sciences:
17
UNF: 30
Masters: 28
Duval: 16
Nassau: 2
Orange: 2
Palm Beach: 1
44 21
2017
Florida Data
Science for Social
Good
(FL-DSSG)
7. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
7
DSSG Project
during Academic
Semesters
30-Year Retrospective
Study
Generational Impact of the Affordable
Housing Program on Partner Families
Dr. Tes Tuason
UNF Public Health
Athlene Jones &
Bharani Kothareddy
Computing
Jacob Perez, Kelly Perniciaro, &
Darlene Ramirez
Public Health
Interviewing homeowners on education, employment,
wealth, and health impacts of owning a HabiJax home.
8. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
8
2022 FL-DSSG Summer Internship Projects
1. Cathedral Arts Project – An Analysis of Equity for DCPS Arts Programs
2. GameFace 4:13 Training Academy - Identifying Communities with Opportunities
for Positive Youth Development
3. League of Women Voters of Florida – Dashboard for Interacting with Florida
Voter Profile Classifications
9. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
9
Fuel of 21st
Century
Problem of
Demand & Supply
A Lucrative Career
Data Science is
Future
Data Science is
Changing the World
Data Science is Hard!
Why Learn
Data Science?
Source: https://data-flair.training/blogs/why-learn-data-science/
10. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
10
Identify a Nonprofit or
Public sector
organization with a
”Wicked Problem”
Gather Data and
Formulate a Plan
Analyze the
Data
Improve Decision
Making Process
for the Client
Data Science for Social Good (DSSG)
DSSG concept formed and started at the University of Chicago in 2013.
11. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
11
Gaining actionable
insights from data
Helping Public Sector
and Nonprofit
Organizations make
data-driven decisions
Training data scientists
with social conscious
Florida Data Science for Social Good (FL-DSSG)
“Social Trustees of
Knowledge”
12. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
12
Other DSSG Programs
13. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
13
NLP Logix
FIS Computing Distinguished Professorship Award
14. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
14
Dr. Sherif Elfayoumy
UNF School of Computing Director
Dr. Kaveri Subrahmanyam
UNF College of Arts & Sciences
(COAS) Dean
15. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
15
Deirdre Conner
Nonprofit Center Senior Director –
Strategic Initiatives and Evaluation
16. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
16
Arri Landsman-Roos
Vice President of Decision
Science, Jacksonville Jaguars
Advisory Board Member
of FL-DSSG
17. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
17
Matt Berseth
Co-Founder and CIO,
NLP Logix
Advisory Board Member
of FL-DSSG
18. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
18
Dr. John Kantner
UNF Associate Provost for Faculty and
Research
19. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
19
2022 FL-DSSG Projects
1. Cathedral Arts Project - An Analysis of Equity for DCPS Arts Programs
2. GameFace 4:13 Training Academy - Identifying Communities with Opportunities
for Positive Youth Development
3. League of Women Voters of Florida – Dashboard for Interacting with Florida Voter
Profile Classifications
20. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
20
An Analysis of Equity for DCPS Arts Programs
21. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
21
22. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
23. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
23
Cathedral Arts Project’s Mission
Elevate
Arts educators in their field
Empower
Every child's creative spirit.
Advocate
For access and equity in the arts
24. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
24
The Social issue
53% of arts programs spend between $0.01-3.99/student in Duval County
No minimum
standard for art
that must be met
Some schools have
greater access to
the arts than others
Art is not a core subject
in the state of Florida
25. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
25
CAP’s Opportunity to Make an Impact
Partnering with DCPS
100% response rate to
the LEAD survey
Design a data-informed
scoring system
Guide schools to make
positive changes in arts
program
26. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
26
Project Objectives
and Challenges
02
Understanding
CHARACTERISTICS
01
Assessing EQUITY
03
Summarizing HEALTH
of arts programs
04
Optimizing SURVEY
05
Recommendations
for SCORING
SYSTEM
27. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
The Data
v
v
School-level
Survey Data:
e.g., partnerships,
engagement, minutes
of instruction, arts
courses taken per
student
Demographics, test
scores, enrollment,
behavioral
incidents, poverty
28. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
v
v
School-level
Survey Data:
e.g., partnerships,
engagement, minutes of
instruction, arts courses taken
per student
Demographics, test
scores, enrollment,
behavioral incidents,
poverty
2020 – 2021
One row per school: 159
total (104 elementary, 21
high, 24 middle schools)
51 total measures
(columns)
29. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
29
Approach to the Data
2
1 3 4 5
Feature selection
and engineering
Verifying data
validity
Managing
missing data
Identifying
“special
case”
schools
Treating
elementary and
middle & high
schools differently
30. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
30
Our Analyses: Dimension Reduction
SCHOOLS
MEASURES
Factor Analysis – Finds commonality between the measures to help summarize data patterns
M1 M2 M3 M4 M5 M6
31. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
31
Our Analyses: Dimension Reduction
SCHOOLS
MEASURES
Factor Analysis – Finds commonality between the measures to help summarize data patterns
M1 M2 M3 M4 M5 M6
32. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
32
Our Analyses: Dimension Reduction
SCHOOLS
MEASURES
Factor Analysis – Finds commonality between the measures to help summarize data patterns
M1 M2 M3 M4 M5 M6
Factor 1
33. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
33
Our Analyses: Dimension Reduction
SCHOOLS
MEASURES
Factor Analysis – Finds commonality between the measures to help summarize data patterns
M1 M2 M3 M4 M5 M6
Factor 2
Factor 1
34. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
34
Our Analyses: Dimension Reduction
SCHOOLS
MEASURES
Latent Class Analysis – Finds commonality between rows (schools) and places them in distinct categories (classes)
M1 M2 M3 M4 M5 M6
35. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
35
Our Analyses: Dimension Reduction
SCHOOLS
MEASURES
Latent Class Analysis – Finds commonality between rows (schools) and places them in distinct categories (classes)
M1 M2 M3 M4 M5 M6
36. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
36
Our Analyses: Dimension Reduction
SCHOOLS
MEASURES
Latent Class Analysis – Finds commonality between rows (schools) and places them in distinct categories (classes)
M1 M2 M3 M4 M5 M6
Class 1
Class 2
Class 3
37. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
37
Factor Analysis Results: Middle & High Schools
Factor
Correlations
Internal Arts
Education
Student Focused
Opportunities
External Art
Engagement
Factor 1
Factor 2
Factor 2
Factor 3
.0
8
.2
9
-
.19
Arts Classes Taken per Student
Percent Access
Standardized Test Scores
Community Engagement
Total Arts Programs
Student to Teacher Ratio
Arts Spaces
Attendance
Governance
Discipline Incidents
Funding Sources
District Arts Budget
Field Trips
Partnerships
Professional Development
Measure
Loading Strength
38. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
38
Factor Analysis Results: Middle & High Schools
Factor
Correlations
Internal Arts
Education
Student
Focused
Opportuniti
es
External Art
Engagement
Factor 1
Factor 2
Factor 2
Factor 3
.0
8
.2
9
-.19
Arts Classes Taken per Student
Percent Access
Standardized Test Scores
Community Engagement
Total Arts Programs
Student to Teacher Ratio
Arts Spaces
Attendance
Governance
Discipline Incidents
Funding Sources
District Arts Budget
Field Trips
Partnerships
Professional Development
Measure
Loading Strength
39. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
Internal Art
Education
Scores and
Equity
Middle & High
Schools
40. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
Middle & High
Schools
Internal Art
Education
Scores and
Behavioral
Outcomes
41. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
Internal Arts
Education and
Achievement
Test Scores
Middle & High
Schools
42. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
Elementary Schools
Exposure to
Arts in the
Community
and
Achievement
Test Scores
43. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
43
LCA Results: Elementary Schools
44. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
44
Perspective
Characteristics that differentiate schools
Indicators
Show the health of an art program
Insight
Uncover areas for improvement
Recommendations
To improve the survey and scoring
system
Impact Towards the Problem
45. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
45
General Survey Recommendations
Data on funding
sources and
amounts
Encourage
fundraising
through principals,
teachers, parents
Know the
number of arts
classes taken
per student
46. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
46
On the horizon for Arts in Jacksonville
Equal access to
the Arts in DCPS
Year to year
improvement
Collect data
Optimize the
survey
Guide
schools
47. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
47
Identifying Communities with
Opportunities for Positive Youth
Development
48. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
48
About
GameFace
Mental Training Physical
Training
Spiritual Training
Before
49. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
49
Afte
r
Overall
Program
Outcomes
Take leadership role
Stay away from
bad influences
Attend
college
Improve mental health
Develop good
character
Achieve higher
grades
Have a higher self-
esteem
50. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
50
Social Issue: Closing The Gap
Juvenile
Crime and Violence
Physical Health
Character
Development
Identifying
Communities
51. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
51
v
COMBINE
all data sources
IDENTIFY areas
for GameFace to
make an Impact
DSSG’s Approach
v
FIND ALL
Zip codes
VISUALIZE
locations
COLLECT
public
data
52. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
52
DSSG Goal and Process
Develop a GIS (Geographic Information System)-based decision tool (dashboard) for identifying areas
where GameFace can make an impact
Data Collection 01
Data Merging 02
Analyses 03
Data Visualization 04
Factor Analysis,
Correlation
Tableau Dashboards
12 Datasets,
35 Zip Codes
Merging
Datasets
based on Zip
Codes
53. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
53
Canvassing Public Data
Census Juvenile Crime
Health
Schools
Churches Food Deserts
54. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
54
Factor Analysis Stressed
Neighborhood
Total Population
Total Crime %
Child Poverty %
Food Deserts
Poverty BIPOC %
Deaths (Diabetes)
Deaths
(Hypertension)
Juvenile Felony %
Urban
Population
Health Gap
55. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
55
Correlation
56. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
56
Tableau
Dashboard Demo
57. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
57
58. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
58
59. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
59
60. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
60
Juvenile Crime
Recommendations – Zip Codes with Impact Opportunities
Disciplinary Action
Health
32210
32208
32210
32218
32209
32210
32210
61. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
61
Recommended Plan of Action for GameFace
• Youth Involvement
• Youth Retention
Data within GameFace
Explore Collaborations
Data Beyond
GameFace
• Graduation
• College Scholarships
• Schools
• Churches
62. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
62
Finding Insights in Florida Voter Turnout
63. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
63
64. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
64
League of Women Voters of Florida (LWVFL)
Nonpartisan organization
encouraging informed and
active participation in
government
100+
Years of service
empowering
voters
29 Florida chapters
25+
Pieces of legislation
passed in 2021 relating
to key issues
65. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
65
From Wicked Problem to Opportunity
02
03
Voter Access and
Participation
Voters keeping registration
active and continuously
participating
Data Analysis
Manipulating and extracting
data points, allowing for
analysis and visualizations,
such as dashboards
Data Access
Public data available
regarding voting history,
voter registration, and
Census
Improvement
Create a plan of action to
address the problem
04
01
66. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
66
Project Focus
Analyze voter
registration and
turnout
Mapping results at the
zip code level
Empower Florida
chapters in
decision-making
67. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
67
Raw Data Source
Voter Registration
• 67 county files
• Rows– ranges from
30K-2M
• Columns – 38
• Name
• Voter ID
• Gender
• Race
• DOB
etc.
Voter History
• 67 county files
• Election info [2006-
2021]
• Rows – ranges from
100k-10M
• Columns – 5
• County Code
• Voter ID
• Election Date
• Election Type
• Voting Method
Census
• 8 files
• Available data from 2016,
2018, and 2020 Census
updates
• Rows - 983 Florida zip
codes
• Information on:
Children, Demographics,
Education, Foreign,
Household Type, Income,
Sex/Age, and Work
Status
Voting files received from Dr. Mike Binder
Census files obtained from census.gov
68. 2022 Florida Data Science for Social Good Big Reveal
August 23, 2022
68
Data Preparation -
Removed sensitive
information
• Voter’s name
• Districting
• Mailing Address etc.
Removed publicly
exempted records
Extracted important
variables for future
merging
• Voter ID
• County Code
• Residential Zip
code etc.
Data Cleaning Stage
1
Data Cleaning Stage
2
Data Extraction
Voter
Registration
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Data Preparation - Voter History
Data
Cleaning
Remove sensitive PI,
public exemptions,
perform feature
engineering
Data
Filtration
Based on federal
general elections
held in 2014 -
2020
Data
Extraction
Identified voting
methods used by
each voter for
general elections
Generate
Flat Files
Created flat files
using python
pandas to
aggregate voting
method at zip
code level.
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Voter Profile Generation
Classifying the Voter IDs based on the eligibility and total vote counts on each
general election held between 2014 – 2020
Profile Code Voter Profile Description
1 Always Eligible voters participated in all general elections
2 Increasing
Eligible voters participated recent in general elections but
not in the past elections
3 Intermittent Eligible voters participated in some elections but not all
4 Decreasing
Eligible voters participated past general elections but not
recently
5 Never Voted Eligible voters didn’t participate in the elections
6 Not Eligible Registered but under 18 years of age
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Data Preparation - Census
Data Cleaning 01
Removing zip codes
from Census that are
PO Boxes,
Correctional Facilities,
or Military Housing
Data
Extraction
02
Data Filtration 03
Data
Merging 04
Extracting necessary
variables [citizen
population, age %,
race %, etc.] Filtering out zip codes with
low total population counts
(<200)
Merging all the variable
files collected by zip code
using python pandas
framework
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Merge Voter Registration + Voter History
Generate Voter Profiles
Merge with
Census Data
Dashboard 1
Voter Profile Analysis
Observe voting increasing and
decreasing patterns across
demographics
Dashboard 2
Voting Method Analysis
Observe voting methods in 2020
Dashboard 3
Census Analysis
Observe voting percentage and
socio-demographic dimensions
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Dashboard 1 – Voter
Profile Analysis
Main Use Case-
Understand Voter
Profile behavior at the
Zip code level.
Dashboard 2 – Voting
Method Analysis
Main Use Case-
Understand Voting
Method behavior at the
Zip code level.
Dashboard 3 – Effect
of Census Socio-
Economic factors on
Voting Percentage
Main Use Case-
Understand effect of
Census variables on
Voter Turnout.
TABLEAU
DASHBOARDS
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Target specific zip codes, based
on filtering selections in
dashboards
Conduct data collection
about local chapter
activities
FL local chapters to collaborate
around mutual goals
Consider statewide
planning
Empowering
LWVFL
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What is the project’s big reveal from your perspective?
What will be the impact of the project for your organization?
What are the next steps for your organization?
1
2
3
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Cathedral Arts Project GameFace 4:13 Training Academy
Dr. Lucy Chen Ashanti Jackson
Vice President of Advocacy &
Community Engagement
Founder and CEO
League of Women Voters of Florida
Leah Nash
Executive Director
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Please note only in-person attendees can ask questions.
If you have a question, please keep your hand up, one of us will get to
you with a mic.
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FL-DSSG
is seeking
sponsorships
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Getting Ready for FL-DSSG 2023
Submit Proposal
Application in
January 2023
Identify Data
Sources and
associated
variables
Get Commitment
from everyone
involved
Identify a Wicked
Problem and its
Social Goodness
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