Slide deck from our hands-on workshop hosted at the 4th Global Symposium on Health Systems Research, focused on basic design tips, tricks, and best practices to improve your charts and graphs.
A short workshop from MERL Tech 2016 on how we can think more purposefully about telling stories with our data and designing visualizations to bring those stories to life in global health and development.
Highlights from three different speakers on the actual use of dashboards for decisionmaking.
MEASURE Evaluation shares the results of a landscape analysis looking for specific examples of dashboards prompting action. BroadReach shares an example of how their Vantage platform is making HIV data accessible in South Africa. JSI shares an example of low-tech but high-impact dashboard development and coaching that has transformed districts in Zimbabwe.
Borrowing from the communications and media experts, storyboarding is one of my favorite approaches to work through a data visualization design with a team. First identify your audience & what your data story is, then map it out visually to come to a common understanding of what your team is designing.
Presented on May 7, 2015 to the TechChange Technology for M&E course. The aim of the presentation was to highlight key considerations in designing visualizations as part of international development programs, and includes both challenges of visualization in development programs and six things to consider when designing visualizations.
Understanding your audience and considering them in your design is essential for building great visualizations. This deck will walk you through the critical steps for identifying and understanding your audience, and developing a complex visualization storyboard to share your message.
A quick reference on designing data visualizations that delight and leverage best practices from the design world to ensure your data is presented in meaningful, usable, fun ways.
A short workshop from MERL Tech 2016 on how we can think more purposefully about telling stories with our data and designing visualizations to bring those stories to life in global health and development.
Highlights from three different speakers on the actual use of dashboards for decisionmaking.
MEASURE Evaluation shares the results of a landscape analysis looking for specific examples of dashboards prompting action. BroadReach shares an example of how their Vantage platform is making HIV data accessible in South Africa. JSI shares an example of low-tech but high-impact dashboard development and coaching that has transformed districts in Zimbabwe.
Borrowing from the communications and media experts, storyboarding is one of my favorite approaches to work through a data visualization design with a team. First identify your audience & what your data story is, then map it out visually to come to a common understanding of what your team is designing.
Presented on May 7, 2015 to the TechChange Technology for M&E course. The aim of the presentation was to highlight key considerations in designing visualizations as part of international development programs, and includes both challenges of visualization in development programs and six things to consider when designing visualizations.
Understanding your audience and considering them in your design is essential for building great visualizations. This deck will walk you through the critical steps for identifying and understanding your audience, and developing a complex visualization storyboard to share your message.
A quick reference on designing data visualizations that delight and leverage best practices from the design world to ensure your data is presented in meaningful, usable, fun ways.
August Designstorm: Alternative Reporting FormatsAmanda Makulec
Monthly brainstorm and idea sharing session at JSI around data visualization. The August deck focuses on alternative reporting formats and questions to think through to reach various audiences, including tools like interactive timelines, interactive graphics and dashboards (Tableau & others), scrolling/parallax webpages, and key design principles.
Data Visualization Design Best Practices WorkshopJSI
This introduction was presented as part of a workshop at the Measurement and Accountability for Results in Health Summit at the World Bank (June 2015). The workshop focused on simple ways anyone working with data can improve their presentations, and included visualization redesign activity to put these principles in practice.
Data visualization trends in Business Intelligence: Allison Sapka at Analytic...Fitzgerald Analytics, Inc.
Allison Sapka's presentation at the Analytics and Data in Financial Services Meetup in Dec 2012. Alison discusses trends in Data Visualization, including why visualization is so powerful when implemented well, and confusing or misleading when done badly
Data visualization is a complex set of processes which is like an umbrella that covers both information and scientific visualization simultaneously. We can’t ignore the benefits of data visualization for its accurate quantities, as it is easily comparable. It also lends valuable suggestion pertaining to the usage of its technique and tools. Scientifically its effectiveness lies in our brain's ability to maintain a proper balance between perception and cognition through visualization.
Data visualizations make huge amounts of data more accessible and understandable. Data visualization, or "data viz," is becoming largely important as the amount of data generated is increasing and big data tools are helping to create meaning behind all of that data.
This SlideShare presentation takes you through more details around data visualization and includes examples of some great data visualization pieces.
Why People are the Heart of Health Innovation. Keynote presentation at the Boston College Public Health Innovation Symposium (19 March 2016). Highlighting how starting with what people want is key to successful health innovation, and how human centered design can help us do just that.
The Future of Business Intelligence: Data VisualizationKristen Sosulski
Kristen Sosulski
The future of business intelligence: Data Visualization
How can data visualization be used as a platform to reveal intelligent insights and help business analysts make timely decisions? In this talk, Kristen Sosulski will discuss the opportunities for personalized, location aware, context relevant, and platform independent information visualizations as a toolkit for business analysts.
Online businesses are struggling to deal with ever increasing and complex amounts of information – from Google Analytics, to e-commerce to internal data. This presentation will highlight how data visualization can allow everyone within an organization to access and understand e-commerce data in order to gain actionable insights, make informed decisions, and drive better results.
Storyboarding for Data Visualization Designspatialhistory
This is derived from a lecture given by Frederico Freitas at the Spatial History Project / Center for Spatial and Textual Analysis at Stanford University. It describes how the process of storyboarding helps clarify design intent and facilitates design decision-making.
Beyond Data Visualization: What's next in communicating with data?Zach Gemignani
We've made great progress in learning how to visualize data, yet a gap still remains between the data experts and the data consumers who might take action on the data. This presentation, shared at the Nashville Analytics Summit, explains how we can bring people into the process of communicating data and guide them to informed actions.
Visualizations with Empathy: Developing Audience PersonasAmanda Makulec
Presentation from Evaluation 2016 featuring ideas for how evaluators (and other data viz designers) can use the develop of personas to segment and understand their audiences. Instead of thinking just of stakeholder groups and job titles, we approach understanding audiences by developing empathy, borrowing from human centered design.
Building your own skills is one step in strengthening how you use visualization in your work, but fostering organizational change can be hard. Here are a few quick considerations on how to nurture data visualization as a personal skill and as an organizational value, and tips for successful collaborations on data visualization activities.
Originally presented as part of the HC3 Innovation Webinar Series on March 8, 2017.
August Designstorm: Alternative Reporting FormatsAmanda Makulec
Monthly brainstorm and idea sharing session at JSI around data visualization. The August deck focuses on alternative reporting formats and questions to think through to reach various audiences, including tools like interactive timelines, interactive graphics and dashboards (Tableau & others), scrolling/parallax webpages, and key design principles.
Data Visualization Design Best Practices WorkshopJSI
This introduction was presented as part of a workshop at the Measurement and Accountability for Results in Health Summit at the World Bank (June 2015). The workshop focused on simple ways anyone working with data can improve their presentations, and included visualization redesign activity to put these principles in practice.
Data visualization trends in Business Intelligence: Allison Sapka at Analytic...Fitzgerald Analytics, Inc.
Allison Sapka's presentation at the Analytics and Data in Financial Services Meetup in Dec 2012. Alison discusses trends in Data Visualization, including why visualization is so powerful when implemented well, and confusing or misleading when done badly
Data visualization is a complex set of processes which is like an umbrella that covers both information and scientific visualization simultaneously. We can’t ignore the benefits of data visualization for its accurate quantities, as it is easily comparable. It also lends valuable suggestion pertaining to the usage of its technique and tools. Scientifically its effectiveness lies in our brain's ability to maintain a proper balance between perception and cognition through visualization.
Data visualizations make huge amounts of data more accessible and understandable. Data visualization, or "data viz," is becoming largely important as the amount of data generated is increasing and big data tools are helping to create meaning behind all of that data.
This SlideShare presentation takes you through more details around data visualization and includes examples of some great data visualization pieces.
Why People are the Heart of Health Innovation. Keynote presentation at the Boston College Public Health Innovation Symposium (19 March 2016). Highlighting how starting with what people want is key to successful health innovation, and how human centered design can help us do just that.
The Future of Business Intelligence: Data VisualizationKristen Sosulski
Kristen Sosulski
The future of business intelligence: Data Visualization
How can data visualization be used as a platform to reveal intelligent insights and help business analysts make timely decisions? In this talk, Kristen Sosulski will discuss the opportunities for personalized, location aware, context relevant, and platform independent information visualizations as a toolkit for business analysts.
Online businesses are struggling to deal with ever increasing and complex amounts of information – from Google Analytics, to e-commerce to internal data. This presentation will highlight how data visualization can allow everyone within an organization to access and understand e-commerce data in order to gain actionable insights, make informed decisions, and drive better results.
Storyboarding for Data Visualization Designspatialhistory
This is derived from a lecture given by Frederico Freitas at the Spatial History Project / Center for Spatial and Textual Analysis at Stanford University. It describes how the process of storyboarding helps clarify design intent and facilitates design decision-making.
Beyond Data Visualization: What's next in communicating with data?Zach Gemignani
We've made great progress in learning how to visualize data, yet a gap still remains between the data experts and the data consumers who might take action on the data. This presentation, shared at the Nashville Analytics Summit, explains how we can bring people into the process of communicating data and guide them to informed actions.
Visualizations with Empathy: Developing Audience PersonasAmanda Makulec
Presentation from Evaluation 2016 featuring ideas for how evaluators (and other data viz designers) can use the develop of personas to segment and understand their audiences. Instead of thinking just of stakeholder groups and job titles, we approach understanding audiences by developing empathy, borrowing from human centered design.
Building your own skills is one step in strengthening how you use visualization in your work, but fostering organizational change can be hard. Here are a few quick considerations on how to nurture data visualization as a personal skill and as an organizational value, and tips for successful collaborations on data visualization activities.
Originally presented as part of the HC3 Innovation Webinar Series on March 8, 2017.
Data Visualization Design Best Practices WorkshopAmanda Makulec
Presentation shared at the #MA4Health Data Visualization workshop cofacilitated with my colleague Tahmid Chowdhury. Our aim was to empower participants with simple principles they can apply to any graph or chart to improve its effectiveness in communicating information, and to share resources on viz design relevant to global health practitioners.
Designing Usage Dashboards for mHealth Program MonitoringAmanda Makulec
Presentation from the MERL Tech Panel on "Dashboards: Force for Good, Great, or Greater Confusion?" focused on the unique challenges of developing a dashboard of usage data from a mobile application.
Chart Makeover: A Women's Nutrition Bar ChartAmanda Makulec
One of the most common requests I receive is to review charts and graphs and provide insight around how to improve them by using the formatting tools available in Excel.
This example shows the process of redesigning the chart to better facilitate comparison within regions of the trend towards a greater percent of women falling into the overweight and obese categories (from 1980 to 2008).
Data visualization is about transforming numbers into knowledge, making information meaningful. I was one of 50 contributors to this free, Creative Commons licensed eBook, which provides a comprehensive overview of how to approach, develop, design, and publish great data visualizations.
Learn more about the project, interact with the eBook online, and get involved in future iterations at https://infoactive.co/data-design
Plano de marketing completo da Seja mais livre, uma empresa que vem mudando a vida de milhares de pessoas pelo Brasil a fora. Faça parte da equipe eliasfarias.com.br - Uma equipe forte que vai estar te dando todo suporte necessário para o seu crescimento dentro da empresa.
Talk at the Wellington Web Design Meetup on April 8, 2010. Data visualization is used to communicate : To make a point, to form a hypothesis, to help achieve a goal.
Overview of Data and Analytics Essentials and FoundationsNUS-ISS
As companies increasingly integrate data across functions, the boundaries between marketing, sales and operations have been blurring. This allows them to find new opportunities that arise by aligning and integrating the activities of supply and demand to improve commercial effectiveness. Instead of conducting post-hoc analyses that allow them to correct future actions, companies generate and analyze data in near real-time and adjust their operations processes dynamically. Transitioning from static analytics outputs to more dynamic contextualized insights means analytics can be delivered with increased relevance closer to the point of decision.
This talk will cover the analytics journey from descriptive, predictive and prescriptive analytics to derive actionable and timely insights to improve customer experience to drive marketing, salesforce and operations excellence.
Highlights and summary of long-running programmatic research on data science; practices, roles, tools, skills, organization models, workflow, outlook, etc. Profiles and persona definition for data scientist model. Landscape of org models for data science and drivers for capability planning. Secondary research materials.
I volunteered my time to share about big data to those looking to understand the space.
This was for Networking with Grace, a group that is focused on helping those get back to work. I put this presentation together to help people learn about big data and how to transition their skill sets to the space.
Presentation from WebDU 2008 in Sydney, where I attempt to give developers and designers some insight into what IA is and how it works, so they can integrate it into their own practices or just work more effectively with IA/UX practitioners
Design and Data Processes Unified - 3rd Corner ViewJulian Jordan
In this presentation (given in early 2020) I explain that to build digital products, data analysts/scientists and designers need to leverage each other’s processes and work as a unit.
I introduce the problem solving approach of data analysts/scientists and designers as well as how to combine these approaches. Additionally, I explain how mental models and algorithms, while associated with design and data science, respectively, are similar ways to represent phenomena and questions about them.
What is Data Science and How to Succeed in itKhosrow Hassibi
The use of machine learning and data mining to create value from corporate or public data is nothing new. It is not the first time that these technologies are in the spotlight. Many remember the late ‘80s and the early ‘90s when machine learning techniques—in particular neural networks—had become very popular. Data mining was at a rise. There were talks everywhere about advanced analysis of data for decision making. Even the popular android character in “Star Trek: The Next Generation” had been named appropriately as “Data.” Data science has been the cornerstone of many data products and applications for more than two decades, e.g., in finance, Telco, and retail. Credit scores have been in use for decades to assess credit worthiness of people when applying for credit or loan. Sophisticated real-time fraud scores based on individual’s transaction spending patterns have been used since early ‘90s to protect credit card holders from a variety of fraud schemes. However, the popularity of web products from the likes of Google, Linked-in, Amazon, and Facebook has helped analytics become a household name. Every new technology comes with lots of hype and many new buzzwords. Often, fact and fiction get mixed-up making it impossible for outsiders to assess the technology’s true relevance. Due to the exponential growth of data, today there is an ever increasing need to process and analyze big data which has required a rethinking of every aspect of the data science life cycle, from data management, to data mining and analysis, to deployment. The purpose of this talk is first to describe what data science is and how it has evolved historically. Second, I share my own experiences as a data scientist across different industries and through time with the audience emphasizing the challenges and rewards.
Analytics thought-leader Thomas Davenport and leading industry experts discuss how—and why—organizations like yours use business analytics to empower more timely and precise decisions by bringing new insights into daily operations.
Dashboards are Dumb Data - Why Smart Analytics Will Kill Your KPIsLuciano Pesci, PhD
Organizations of every size have access to data dashboard technology, yet none of the solutions have delivered on their hype and right now across the world executives and analysts are staring at a dashboard and thinking the same thing, ""so what?""
The failure of dashboards to deliver meaningful insights is inherent in their simplicity: they only show surface level information, and not the relationships between data points that really drive the fate of your organization.
But all is not lost! By combining the right mix of technology and human expertise in business strategy, research and data mining you can embrace the smart analytics movement, and start accessing insights that grow your company and your competitive position.
You can watch the accompanying webinar here: https://youtu.be/RdOcPxv9wLs
AMES 2016 - The Human Side of AnalyticsStephen Tracy
Last year the global analytics industry was estimated to be worth $125 billion in hardware, software and services revenue. Consequently the market has been flooded with more tools, platforms and tech than you can shake a calculator at. When it comes to data, the core challenge many businesses face today seems to have less to do with analytics technology and infrastructure and more to do with finding the right people, talent and skills. In this presentation Stephen will share 10 lessons for building a successful analytics program through a ‘people-first’ strategy.
Information design is both a technical skill and an art form. To design great visualizations requires a diverse range of skill sets and a keen ability to understand the decisions to be made, the data available, the tools and platforms available for visualization design, and how to apply design best practices to create effective visualizations that communicate clearly. Even the most robust routine health information systems face challenges around how to visualize data in a way that facilitates decision-making by key stakeholders.
Similar to Designing Data Visualizations to Strengthen Health Systems (20)
Breakout session at MERL Tech 2018.
Agile - commonly used in the tech community - offers a number of sticky ideas and principles we can adapt in international development and MERL to improve how we work and support adaptive management.
In this breakout, we focus on three sticky ideas: creating and being guided by user stories, prioritization, and limiting WIP.
Lightning talk presented at MERL Tech 2018.
Often we think of dashboards as interactive reports instead of being digital products.
By rethinking our criteria of success for launching a new dashboard and borrowing from UX design, we can think more meaningfully about how we build dashboards stakeholders actually want to use.
Developing Dashboards with User-Centered DesignAmanda Makulec
Design sprint session hosted at the TechLady Hackathon, focused on the basic principles and techniques for starting a design process with who will use the data, rather than the tables and tools.
Slides from an interactive workshop focused on exposing M&E practitioners to design thinking approaches to understand the needs and experiences of data users at MERL Tech 2017
A quick overview of two techniques from design thinking that can help us better tailor data visualizations to the needs of our audiences. Personas can be used to identify illustrative audience members who represent large groups within our target audience, and journey maps help us understand how an audience receives, interprets, and acts on information.
The illustrative example presented here is rooted in a real world experience, but is not an actual persona and journey used in that work.
A Data Viz Makeover: Approaches for Improving your VisualizationsAmanda Makulec
A joint presentation made at the 2015 USAID Global Health Mini University, introducing key data visualization concepts and setting the stage for two interactive activities on storyboarding for data visualizations and visual best practices for graph and chart design.
Thinking about how to communicate results from global health and development programs can be a challenge. By looking beyond long form, narrative, text reports, we can make our learning more accessible to wider audiences and promote the use of data for decision making by formatting our results in interesting, inviting ways. This deck includes a ideas, resources, and inspiration for great alternative reporting formats, including videos and SlideDocs.
An introduction to infographic design written for global health and development professionals, including ideas for storyboarding, design tools, and tips and tricks to create fun, meaningful infographics. Lots of links to free web-based tools and great resources.
Data Visualization Resource Guide (September 2014)Amanda Makulec
A summary guide to data visualization design, including key design principles, great resources, and tools (listed by category with short explanations) that you can use to help design elegant, effective data visualizations that help share your message & promote the use of your information.
Note that the tools & resources highlighted are suggested, and inclusion should not be considered as an endorsement from JSI.
Summary deck from our monthly JSI design-storm (design + brainstorm), highlighting the key features of Piktochart for designing visualizations to make information accessible.
Interactive, clickable session highlighting how to apply design principles to Excel graphs to make a data story sing. Originally hosted as a brown-bag lunch presentation at JSI. For more detailed resources on designing various chart types in Excel, check out Ann Emery's Excel series and slide decks http://www.slideshare.net/annkemery/presentations.
Summary deck from our monthly JSI design-storm (design + brainstorm), highlighting the amazing templates and design features from Nancy Duarte's Slidedocs. The highlights features here only hit on a small section of her overall approach - check out the complete package at http://www.duarte.com/slidedocs
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
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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.
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
10. What is data visualisation?
• A way of visually conveying information – often
quantitative in nature – in an accurate, compelling
format.
• Usually makes relationships more apparent (e.g. by
clustering, color coding and by putting items in scale).
• Can be static or interactive.
19. Each persona represents a significant
portion of people in the real world
and enables the designer to focus on a
manageable and memorable cast of
characters, instead of focusing on
thousands of individuals.”
persona, n.
“A persona is depicted as a specific
person but is not a real individual;
rather, it is synthesized from observations
of many people.
From:
https://www.smashingmagazine.com/201
4/08/a-closer-look-at-personas-part-1/
28. Factual, analytical Feeling, intuitive Personal gain System gains
External recognition Internal reward Simplicity Complexity
Complacent Driver of change Debilitated by chaos Thrives on chaos
Team oriented Individual/loaner Problem solver Defeatist
Black and white Compromise Receptive Rigid
Team leader Team member Carrot eater Stick driven
Short term focus Long term vision Self accountable Cheater
Internal motive External motive Technical Political
Needs clarification Self-motivated Empowerer Underminer
Works better in group Works better alone Data driven Story motivated
Values independence Values collaboration Head Heart
Personas on Continuums
Much like the Myers-Briggs personality scale, personas can be ranked along continuums of
characteristics that may impact their use of data for decisionmaking.Some examples of different
“poles” identified in workshops are below.
51. Who makes a good
visualisation?
Communication
Research
Design
Technology
From: https://onthinktanks.org/art
icles/visualising-data-both-a-
science-and-an-art/
52. • Data literacy – merging and tidying datasets
• Statistical competencies – mean v median,
ordinal versus scalar
• Research methods - sampling
• Research context
Research
53. • For data collection – e.g. web scrapers
• For data storage – e.g. database and SQL
• For data manipulation – e.g. SPSS, R
• For data visualisation – e.g. coding, like jQuery,
HTML5
Technology
85. Quick colour aside
Analogous (similar
colours)
monochromatic
complementary
From: Data visualisation: a practical guide to producingeffective visualisations for research communication
http://resyst.lshtm.ac.uk/resources/data-visualisation-practical-guide-producing-effective-visualisations-research
86. Not remembering the objective
Team 1
Team 2
Person A
Person B
Person C
Person D
Person E
Person F
Person
G
Person
H
vs
87. Not thinking about order
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
A B C D
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
D A C B
vs
88. Not scaling to zero
11.5
12
12.5
13
13.5
14
14.5
15
Category
1
Category
2
Category
3
Category
4
0
2
4
6
8
10
12
14
16
Category
1
Category
2
Category
3
Category
4
vs
90. Not labelling directly
Series 1
Series 2
Series 3
0
1
2
3
4
5
6
1990 1995 2000 2005
0
1
2
3
4
5
6
1990 1995 2000 2005
Series 1 Series 2 Series 3
vs
96. Seven deadly sins
of
data visualisation
https://onthinktanks.org/articles/on-datavis-judging-jeff-knezovichs-advice/
From: https://onthinktanks.org/articles/on-
datavis-judging-jeff-knezovichs-advice/
118. 0
1
2
3
4
5
6
Category 1 Category 2 Category 3 Category 4
Series 1 Series 2 Series 3
Super special brand-compliant graph!
Inspired by Cole Naussbaumer at Stanford’s Data on Purpose, February 2016
119. 4.3
2.5
3.5
4.5
Category 1 Category 2 Category 3 Category 4
Series 1 Series 2 Series 3
Easier to see a key data series graph!
Inspired by Cole Naussbaumer at Stanford’s Data on Purpose, February 2016
124. 0
10
20
30
40
50
Facility 1 Facility 2 Facility 3 Facility 4 Facility 5 Facility 6 Facility 7 Facility 8
Facility 4 showed the highest quality of care.
Despite scoring highest, its overall score was below 50%, indicating there is
work to be done to improve quality of care.
125. 38.9
Facility 1 Facility 2 Facility 3 Facility 4 Facility 5 Facility 6 Facility 7 Facility 8
Facility 4 showed the highest quality of care.
Despite scoring highest, its overall score was below 50%, indicating there is
work to be done to improve quality of care.