The document discusses an introduction to research resources and data sources, including types of data, examples of data sources, and considerations for using different data. It also covers project management topics like defining project goals and scope, developing a schedule and products, and maintaining projects over their lifecycle. The workshop aims to provide planning staff with resources and skills for effective research and use of data in their work.
This half-day workshop was designed to give Product Managers, Designers and Engineers about what kinds of research are possible, when to do research, what goes into it, and ultimately how to conduct research and avoid making mistakes when moderating. You can also listen to Example #1 (http://www.designmap.com/audio/modCloth/bad.mp3), Example #2 (http://www.designmap.com/audio/modCloth/subtly_bad.mp3), and Example #3 (http://www.designmap.com/audio/modCloth/good.mp3).
This is a workshop we conducted for a consumer-facing web-based product company. They had a very talented internal design team, but found that they (happily!) had more demand for research than they could fill.
El documento presenta im叩genes y detalles sobre La Cumbrecita, una localidad cordobesa. Muestra fotos de paisajes de La Cumbrecita e informa que queda a 400 kil坦metros de Rosario. Tambi辿n anuncia un pr坦ximo viaje de estudiantes del 5to, 6to y 7mo grado a La Cumbrecita.
Research orientation nme ict kcg workshop presentationDilip Barad
油
This presentation was made by Dr. Dilip Barad in workshop organised by Knowledge Consortium of Gujarat (KCG). Venue: Dept. of Botany, School of Scienes, Gujarat University, Gujarat - India.
Higher Education Academy Research-Teaching Nexus Action Set Workshop held at University of Wales, Trinity St. David's, Carmarthen Campus, on Wednesday 15th September 2010. The workshop was convened by Professor Simon Haslett (University of Wales, Newport) and facilitated by Professor Stuart Hampton-Reeves (University of Central Lancashire).
The document discusses the use of bibliometric data and citation metrics to evaluate research performance and support decision making. It notes the increasing importance of demonstrating research impact and return on investment. Thomson Reuters products like the Journal Citation Reports and Web of Science are positioned as providing objective citation and bibliometric data to help with research assessment and evaluation exercises. The document also provides examples of how this data can be used to analyze the research performance of institutions and individuals.
The document discusses resources available through the Unisa Library to support applications for an NRF rating. It outlines 6 key resources: 1) Cited reference searching to measure impact and reputation, 2) Journal impact factors and rankings, 3) Citation alerts and tracking to discover influence on newer research, 4) Researcher profiles to build a public profile, 5) H-index to measure productivity and impact, and 6) Unisa's institutional repository to increase visibility and impact of scholarly output. The library provides databases, tools, and assistance to gather evidence of scholarly impact and reputation.
Este documento proporciona instrucciones para buscar informaci坦n sobre revistas de ortopedia en el Journal Citation Reports (JCR) del a単o 2014 utilizando la p叩gina web del ISI Web of Knowledge. Explica los pasos para acceder a la base de datos, buscar la categor鱈a de "Ortopedics", y encontrar que la revista con m叩s art鱈culos publicados ese a単o fue "J Arthroplasty" con 509 art鱈culos.
Este documento proporciona instrucciones para acceder y navegar en la base de datos ISI Web of Knowledge para buscar y analizar revistas cient鱈ficas. Explica c坦mo identificarse en la p叩gina de la Biblioteca de Centros de Salud de la Universidad de Sevilla, seleccionar la edici坦n 2014 de Ciencias JCR, ordenar los resultados por n炭mero de art鱈culos publicados, y ver el ranking y cuartil de una revista espec鱈fica.
This document provides an introduction to data visualization for analysis. It discusses exploring datasets that can include textual, numerical, and other data. The document outlines the data visualization process and mentions some common tools and methods used. It also discusses extending your toolset and provides an example exercise exploring a dataset and creating a visualization to gain insights. The objective is to appreciate the variety of techniques available to digital humanities scholars for data analysis and visualization.
Tips for Effective Data Science in the EnterpriseLisa Cohen
油
Data Science is an evolving field, that requires a diverse skill set. From Career Advice to steps for how to approach your Data Science Workflow, this talk is full of practical tips that you can apply immediately to your job.
Introduction to Self-Service Dashboarding and Report Authoring: Leveraging IB...Senturus
油
Learn to use report authoring tools such as: Workspace, Workspace Advanced, and Report Studio using Cognos BI. View the webinar video recording and download this deck: http://www.senturus.com/resource-video/introduction-self-service-dashboarding/?rId=3390.
We touch on the role of the advanced report author to illustrate the limitless potential of the IBM Cognos 10 platform for delivering professional reports. The following demo are featured: 1) Viewing and interacting with multiple data visualizations, 2) Simple filtering through self-selected values to focus on specific data and provide better insights, 3) Easy double-click functionalities to drill down into details on specific data points, 4) Self-managing desired changes from one chart type to another, including data point color schemes, 5) Analyzing data on a deeper level through improved Do More... actions with advanced feature options, 6) Dropping additional dimensions into dashboards, 7) Building a report from scratch as a business author, starting with Workspace Advanced (using a crosstab report as an example), 8) Ad-hoc experience that provides ability to see selected report dimensions and measures to build and visualize in real-time as one fluid experience, 9) Dragging and dropping columns of data, 10) Easy toolbar short cuts for quick data formatting, 11) Data exploration functionalities with Workspace and Workspace Advanced, such as drilling up, drilling down and replacing data, 12) Moving report draft from Workspace Advanced into Report Studio for additional content development with more sophisticated options, including visualizations within tables in Report Studio, 13) Adding value prompts through the Report Studio Prompt Wizard to drive context filtering, 14) Using padding within Report Studio to provide adequate spacing between objects and 15) Adding drilling up and drilling down options to reports.
Senturus, a business analytics consulting firm, has a resource library with hundreds of free recorded webinars, trainings, demos and unbiased product reviews. Take a look and share them with your colleagues and friends: http://www.senturus.com/resources/.
20140902 LinDa Workshop Semantincs2014 - LinDA Project OverviewLinDa_FP7
油
LinDa Project presentation - Challenges, tools, workplan and objectives
Presentation at LinDA Workshop on 2nd September 2014 at Semantics2014 by Spiros Mouzakitis
Tips and Tricks to be an Effective Data ScientistLisa Cohen
油
Data Science is an evolving field, that requires a diverse skill set. From Analytical Techniques to Career Advice, this talk is full of practical tips that you can apply immediately to your job.
This document discusses Hortonworks and big data. It provides an overview of Hortonworks' history and role in developing Apache Hadoop. Key points include: Hortonworks was created in 2011 to focus on enterprise Hadoop and started with 24 engineers from Yahoo; Hortonworks develops, distributes and supports the only 100% open source enterprise Hadoop distribution; and Hortonworks aims to drive innovation in Apache Hadoop projects and enable ecosystem interoperability.
The Softer Skills analysts need to succeed in their careersPaul Laughlin
油
A talk that I gave to the UK's Operational Research Society's annual Analytics & AI Summit 2021 (#AS21). Focusing on the Contracting & Delivering parts of this training model.
This document provides a brief guide for writing grant proposals, outlining the key sections and what they should contain. It discusses the format, including an introduction, problem statement, objectives, methods, evaluation, and sustainability. It also discusses researching funding databases, news/membership organizations, and developing a donor base. The guide emphasizes being clear, measurable, and data-driven while aligning with the funder's priorities.
This slideshow was used at a training session delivered at the Social Sciences Division, University of Oxford, on 2014-05-07. It provides some tips for keeping your research material under control.
Market Research Meets Big Data Analytics for Business Transformation Sally Sadosky
油
This document summarizes a presentation given by Al Nevarez and Sally Sadosky of LinkedIn on how the company uses market research and big data analytics. It discusses LinkedIn's business goals and vision, how it conducts market research through surveys, and how it analyzes massive amounts of member data using tools like Hadoop and Pig to gain insights at low cost. Integrating survey data with behavioral data through SQL joins allows answering questions about member segments and experiences.
40 属 advises and supports companies and institutions to generate real added value from data and to generate data-driven innovations and new business models. We help to reinvent your business with data. 40 属 is the expert for data driven business transformation
March Towards Big Data - Big Data Implementation, Migration, Ingestion, Manag...Experfy
油
Gartner, IBM, Accenture and many others have asserted that 80% or more of the worlds information is unstructured and inherently hard to analyze. What does that mean? And what is required to extract insight from unstructured data?
Unstructured data is infinitely variable in quality and format, because it is produced by humans who can be fastidious, unpredictable, ill-informed, or even cynical, but always unique, not standard in any way. Recent advances in natural language processing provides the notion that unstructured content can be included in data analysis.
Serious growth and value companies are committed to data. The exponential growth of Big Data has posed major challenges in data governance and data analysis. Good data governance is pivotal for business growth.
Therefore, it is of paramount importance to slice and dice Big Data that addresses data governance and data analysis issues. In order to support high quality business decision making, it is important to fully harness the potential of Big Data by implementing proper Data Migration, Data Ingestion, Data Management, Data Analysis, Data Visualization and Data Virtualization tools.
Check it out: https://www.experfy.com/training/courses/march-towards-big-data-big-data-implementation-migration-ingestion-management-visualization
This document provides an introduction to data science, including the main roles in data science, the data pipeline process (OSEMN), and steps within the process. It discusses obtaining data from various sources, cleaning data by examining for errors and missing values, exploring data through visualizations and statistics to find patterns, modeling data to create predictive algorithms, and interpreting results through data storytelling. The roles covered include data scientists, data analysts, data engineers, and business intelligence specialists.
Open Source Framework for Deploying Data Science Models and Cloud Based Appli...ETCenter
油
Next generation applications address more sophisticated questions that go beyond 'What happened?' by using Machine Learning/Statistical modelling to answer 'Why?' and 'What will happen next? Data insights can be easily deployed and rapidly delivered to the decision makers via cloud based applications. This framework focuses on technologies available for the entire data workflow from ingestion and modeling to cloud deployment; Hadoop, MADlib, Python, R, CloudFoundry, etc. This presentation will also include examples of how this framework and innovative Data Science techniques have been applied across diverse business units within Media, including pricing analyses for ad optimization and predicting viewership.
2nd Big Data Business Forum Nov 13th to 15th, 2013 in San FranciscoMario Faria
油
The 2nd Big Data Business Forum will happen from November 13th to 15th, 2013 in San Francisco. This is one of the top data and analytics conferences of the year.
Agile Data Science is a lean methodology that is adopted from Agile Software Development. At the core it centers around people, interactions, and building minimally viable products to ship fast and often to solicit customer feedback. In this presentation, I describe how this work was done in the past with examples. Get started today with our help by visiting http://www.alpinenow.com
Effective Commercial Underwriting using Big Data and Risk Analyticsintellectseec
油
How can property and casualty insurers effectively use Big Data and Risk Analytics to underwrite better? This presentation explains the role of Big Data in insurance, talks about how to use Big Data along with traditional data methods and presented information about the technology around Big Data and its use for commercial insurance.
Presentation to Analytics Network of the OR Society Nov 2020Paul Laughlin
油
Presentation on 'The Softer Skills that Analysts need' presented by Paul Laughlin at a virtual event run for the Analytics Network group within the UK OR Society. Exploring Paul's 9 Step Model for effective analysis & explaining how Softer Skills are essential throughout that workflow.
The document provides an economic development plan for the west side of Lake Helen, Florida. It defines the study area around an I-4 interchange and creates 3-mile and 5-mile market assessment areas. An analysis of existing conditions in the study area finds it includes 195 parcels totaling 471.57 acres, with the most common land uses being residential vacant land, commercial vacant land, residential single family, and store-office-single family residential. The plan will provide industry and use recommendations for the study area based on the existing conditions analysis and a market assessment of the surrounding region.
This document provides an introduction to data visualization for analysis. It discusses exploring datasets that can include textual, numerical, and other data. The document outlines the data visualization process and mentions some common tools and methods used. It also discusses extending your toolset and provides an example exercise exploring a dataset and creating a visualization to gain insights. The objective is to appreciate the variety of techniques available to digital humanities scholars for data analysis and visualization.
Tips for Effective Data Science in the EnterpriseLisa Cohen
油
Data Science is an evolving field, that requires a diverse skill set. From Career Advice to steps for how to approach your Data Science Workflow, this talk is full of practical tips that you can apply immediately to your job.
Introduction to Self-Service Dashboarding and Report Authoring: Leveraging IB...Senturus
油
Learn to use report authoring tools such as: Workspace, Workspace Advanced, and Report Studio using Cognos BI. View the webinar video recording and download this deck: http://www.senturus.com/resource-video/introduction-self-service-dashboarding/?rId=3390.
We touch on the role of the advanced report author to illustrate the limitless potential of the IBM Cognos 10 platform for delivering professional reports. The following demo are featured: 1) Viewing and interacting with multiple data visualizations, 2) Simple filtering through self-selected values to focus on specific data and provide better insights, 3) Easy double-click functionalities to drill down into details on specific data points, 4) Self-managing desired changes from one chart type to another, including data point color schemes, 5) Analyzing data on a deeper level through improved Do More... actions with advanced feature options, 6) Dropping additional dimensions into dashboards, 7) Building a report from scratch as a business author, starting with Workspace Advanced (using a crosstab report as an example), 8) Ad-hoc experience that provides ability to see selected report dimensions and measures to build and visualize in real-time as one fluid experience, 9) Dragging and dropping columns of data, 10) Easy toolbar short cuts for quick data formatting, 11) Data exploration functionalities with Workspace and Workspace Advanced, such as drilling up, drilling down and replacing data, 12) Moving report draft from Workspace Advanced into Report Studio for additional content development with more sophisticated options, including visualizations within tables in Report Studio, 13) Adding value prompts through the Report Studio Prompt Wizard to drive context filtering, 14) Using padding within Report Studio to provide adequate spacing between objects and 15) Adding drilling up and drilling down options to reports.
Senturus, a business analytics consulting firm, has a resource library with hundreds of free recorded webinars, trainings, demos and unbiased product reviews. Take a look and share them with your colleagues and friends: http://www.senturus.com/resources/.
20140902 LinDa Workshop Semantincs2014 - LinDA Project OverviewLinDa_FP7
油
LinDa Project presentation - Challenges, tools, workplan and objectives
Presentation at LinDA Workshop on 2nd September 2014 at Semantics2014 by Spiros Mouzakitis
Tips and Tricks to be an Effective Data ScientistLisa Cohen
油
Data Science is an evolving field, that requires a diverse skill set. From Analytical Techniques to Career Advice, this talk is full of practical tips that you can apply immediately to your job.
This document discusses Hortonworks and big data. It provides an overview of Hortonworks' history and role in developing Apache Hadoop. Key points include: Hortonworks was created in 2011 to focus on enterprise Hadoop and started with 24 engineers from Yahoo; Hortonworks develops, distributes and supports the only 100% open source enterprise Hadoop distribution; and Hortonworks aims to drive innovation in Apache Hadoop projects and enable ecosystem interoperability.
The Softer Skills analysts need to succeed in their careersPaul Laughlin
油
A talk that I gave to the UK's Operational Research Society's annual Analytics & AI Summit 2021 (#AS21). Focusing on the Contracting & Delivering parts of this training model.
This document provides a brief guide for writing grant proposals, outlining the key sections and what they should contain. It discusses the format, including an introduction, problem statement, objectives, methods, evaluation, and sustainability. It also discusses researching funding databases, news/membership organizations, and developing a donor base. The guide emphasizes being clear, measurable, and data-driven while aligning with the funder's priorities.
This slideshow was used at a training session delivered at the Social Sciences Division, University of Oxford, on 2014-05-07. It provides some tips for keeping your research material under control.
Market Research Meets Big Data Analytics for Business Transformation Sally Sadosky
油
This document summarizes a presentation given by Al Nevarez and Sally Sadosky of LinkedIn on how the company uses market research and big data analytics. It discusses LinkedIn's business goals and vision, how it conducts market research through surveys, and how it analyzes massive amounts of member data using tools like Hadoop and Pig to gain insights at low cost. Integrating survey data with behavioral data through SQL joins allows answering questions about member segments and experiences.
40 属 advises and supports companies and institutions to generate real added value from data and to generate data-driven innovations and new business models. We help to reinvent your business with data. 40 属 is the expert for data driven business transformation
March Towards Big Data - Big Data Implementation, Migration, Ingestion, Manag...Experfy
油
Gartner, IBM, Accenture and many others have asserted that 80% or more of the worlds information is unstructured and inherently hard to analyze. What does that mean? And what is required to extract insight from unstructured data?
Unstructured data is infinitely variable in quality and format, because it is produced by humans who can be fastidious, unpredictable, ill-informed, or even cynical, but always unique, not standard in any way. Recent advances in natural language processing provides the notion that unstructured content can be included in data analysis.
Serious growth and value companies are committed to data. The exponential growth of Big Data has posed major challenges in data governance and data analysis. Good data governance is pivotal for business growth.
Therefore, it is of paramount importance to slice and dice Big Data that addresses data governance and data analysis issues. In order to support high quality business decision making, it is important to fully harness the potential of Big Data by implementing proper Data Migration, Data Ingestion, Data Management, Data Analysis, Data Visualization and Data Virtualization tools.
Check it out: https://www.experfy.com/training/courses/march-towards-big-data-big-data-implementation-migration-ingestion-management-visualization
This document provides an introduction to data science, including the main roles in data science, the data pipeline process (OSEMN), and steps within the process. It discusses obtaining data from various sources, cleaning data by examining for errors and missing values, exploring data through visualizations and statistics to find patterns, modeling data to create predictive algorithms, and interpreting results through data storytelling. The roles covered include data scientists, data analysts, data engineers, and business intelligence specialists.
Open Source Framework for Deploying Data Science Models and Cloud Based Appli...ETCenter
油
Next generation applications address more sophisticated questions that go beyond 'What happened?' by using Machine Learning/Statistical modelling to answer 'Why?' and 'What will happen next? Data insights can be easily deployed and rapidly delivered to the decision makers via cloud based applications. This framework focuses on technologies available for the entire data workflow from ingestion and modeling to cloud deployment; Hadoop, MADlib, Python, R, CloudFoundry, etc. This presentation will also include examples of how this framework and innovative Data Science techniques have been applied across diverse business units within Media, including pricing analyses for ad optimization and predicting viewership.
2nd Big Data Business Forum Nov 13th to 15th, 2013 in San FranciscoMario Faria
油
The 2nd Big Data Business Forum will happen from November 13th to 15th, 2013 in San Francisco. This is one of the top data and analytics conferences of the year.
Agile Data Science is a lean methodology that is adopted from Agile Software Development. At the core it centers around people, interactions, and building minimally viable products to ship fast and often to solicit customer feedback. In this presentation, I describe how this work was done in the past with examples. Get started today with our help by visiting http://www.alpinenow.com
Effective Commercial Underwriting using Big Data and Risk Analyticsintellectseec
油
How can property and casualty insurers effectively use Big Data and Risk Analytics to underwrite better? This presentation explains the role of Big Data in insurance, talks about how to use Big Data along with traditional data methods and presented information about the technology around Big Data and its use for commercial insurance.
Presentation to Analytics Network of the OR Society Nov 2020Paul Laughlin
油
Presentation on 'The Softer Skills that Analysts need' presented by Paul Laughlin at a virtual event run for the Analytics Network group within the UK OR Society. Exploring Paul's 9 Step Model for effective analysis & explaining how Softer Skills are essential throughout that workflow.
The document provides an economic development plan for the west side of Lake Helen, Florida. It defines the study area around an I-4 interchange and creates 3-mile and 5-mile market assessment areas. An analysis of existing conditions in the study area finds it includes 195 parcels totaling 471.57 acres, with the most common land uses being residential vacant land, commercial vacant land, residential single family, and store-office-single family residential. The plan will provide industry and use recommendations for the study area based on the existing conditions analysis and a market assessment of the surrounding region.
Located within the Metro Orlando region, the City of Kissimmee is using the healthcare sector as a means to diversify its economy, revitalize its urban core, and attract high-wage jobs to the community. To this effect, the city designated the northern part of its downtown as a Medical Arts District (District) in 2012. This area is anchored by two major hospital campuses, which have helped to attract other medical providers to the area. City officials are interested in supporting the expansion of health care services within this area and contracted with the East Central Florida Regional Planning Council (ECFRPC) to develop a strategic plan for the District.
This document summarizes deliverables from a food entrepreneurship plan for Goldsboro, NC. It includes a food zoning toolkit analyzing best practices from 15 jurisdictions, a Seminole County food assessment mapping existing food production assets, and next steps to develop a Goldsboro food entrepreneurship plan. The zoning toolkit examines definitions, permitted districts, and standards for urban agriculture, shared commercial kitchens, and mobile food vending. The assessment inventories agricultural land, farms, processors, distributors, kitchens and markets. The Goldsboro plan will identify code changes and potential food production locations in the community.
The document provides information on best practices for regulating food uses in zoning codes based on a review of six case studies. The main food uses examined are urban agriculture, shared commercial kitchens, and mobile food vending. Key findings include:
- Definitions of urban agriculture differentiate between market gardens and urban farms based on scale and allowed activities.
- Allowed zoning districts vary but generally permit urban agriculture in commercial and industrial areas, with some also allowing in residential.
- Specific standards address site development, equipment, composting, accessory structures, signage, and parking to ensure compatibility.
Economic Research Initative Issue #6 Findings and ConclusionsLuis Nieves-Ruiz
油
The document summarizes the findings of a study on major industry clusters and economic drivers in Orange County, Florida. It identifies four key clusters: healthcare, floriculture/nursery, modeling/simulation/training, and tourism. The healthcare cluster contains over 40,000 jobs across three sub-clusters along Orange Avenue and Colonial Drive. The floriculture/nursery cluster in northwest Orange County contains around 2,500 jobs but may be threatened by suburbanization. The modeling/simulation/training cluster contains over 20,000 jobs in technical fields and appears to be the only true technology cluster.
The document discusses the history and development of artificial intelligence over the past 70 years. It outlines some of the key milestones in AI research including the creation of logic theories, machine learning algorithms, and neural networks. Recent advances in deep learning have led to AI systems that can perform complex tasks like image recognition and natural language processing.
Historic preservation, economic development, and community revitalization programs are interrelated. Significant dates in historic preservation include the Antiquities Act of 1906, Colonial Williamsburg in 1926, and the National Historic Preservation Act of 1966. Economic development theories include von Thunen's model of land use, central place theory, economic base theory, and clusters. Community revitalization strategies involve creating special districts, strategic plans, tax incentives, and programs like enterprise zones, business improvement districts, and Main Street programs.
This document summarizes agricultural production and food systems in Orange County, Florida. It finds that while agriculture contributes $269.9 million annually, farms are small and scattered. The top crops are nursery, citrus, beef, and other animals. There is some urban agriculture but most farmland is planned for development. The county has 47 food manufacturers and 122 distributors, though connections between production, processing and distribution are limited. The document recommends adding food-related uses and districts to zoning codes to better connect residents to local food.
Orange County's economic development is driven by its growing and diverse population, strong infrastructure, and policy framework that supports key industries. The county population grew 24% between 1990-2000 and is projected to increase another 50% by 2030 under moderate growth projections. While retirees make up a smaller portion of residents compared to other Florida communities, international migration has contributed to a diverse population with large Spanish, Haitian, Jamaican and Asian communities. Orange County has a young median age and healthy workforce, though over 60% lack a post-secondary degree, which may impact its ability to attract high-tech industries. The county has invested in transportation infrastructure and urban centers to support economic clusters in tourism, life sciences, and technology.
This document analyzes industries along the SR 429 corridor to identify economic clusters. It finds the largest number of firms are in building and real estate, while nursery and floriculture appears the most mature cluster. Tourism support and health care show solid industry agglomerations. Emerging clusters with potential include information technology and metallurgy. The document recommends further study of industry linkages to develop an economic strategy for the corridor.
This document discusses the healthcare sector in Orange County, Florida. It finds that while the sector employs over 82,000 people, no industry has a location quotient above 1, indicating it is not a basic industry. However, hospitals are large employers and purchasers. The county is developing a "Medical City" cluster around Lake Nona that may boost the sector. Diagnostic imaging centers have a location quotient of 1.96, showing specialization. Overall, the sector is growing but not yet established as an export industry for the local economy.
This document summarizes Orange County's high technology sector, particularly the modeling, simulation, and training (MS&T) industry. It finds that Orange County has strengths in several high-tech industries like commercial machinery and data processing. The MS&T industry is a major part of the local economy but hard to define using standard industry codes. Most MS&T companies cluster near the University of Central Florida and support national security. The document concludes technological innovation will be important for the local economy and bioscience may also play a larger role.
Nursery and Floriculture Sector in Orange County Luis Nieves-Ruiz
油
The document discusses the nursery and floriculture industry in Orange County, Florida. It began in the 1880s supplying citrus growers and expanded to include indoor foliage plants. By the 1920s, local nurseries were shipping over 1 million ferns annually. Today, most production is concentrated near Apopka and includes over 4,000 acres of ornamental plants and container nurseries. The industry also supports over 100 supplier firms and contributes significantly to the local economy. However, urban growth presents challenges by increasing land costs and limiting available space for nurseries.
This document provides an overview of cohousing communities. It describes how cohousing combines private dwellings with extensive shared community spaces and facilities. Residents are involved in designing and managing their community. Key characteristics include participatory processes, pedestrian-oriented neighborhood design with common spaces, and a large common house used for meals and activities. Financing can be challenging given the time needed for resident participation. Emerging models involve developers assisting with land acquisition and construction while still allowing for community input.
People's growing interest in fresh, locally produced food has increased demand for urban agriculture, community gardens, and farmers' markets. However, many zoning codes pose barriers by strictly separating land uses. This white paper examines how three jurisdictions incorporate food uses into their zoning codes, including definitions, allowed districts, and development standards. Recommendations are provided for Orange County's codes to better facilitate food production and access.
1. Welcome to the Planning Divisions
Research Resources
Workshop
2. Research Resources Workshop
Introduction to Data Sources
Formats, Products, Getting Started
Doing Research with GIS
Putting Research to Work in Scenarios
Question and Answer Session
7. Introduction to Data Sources
Examples of Data Sources
Demographic
Economic
Land Use/Spatial
Other
8. Introduction to Data Sources
Examples of Data Sources
Demographic
Economic
Land Use/Spatial
Other
9. Introduction to Data Sources
U.S Census Bureau/American Community
Survey
http://factfinder.census.gov/home/saff/main.html
?_lang=en
Bureau of Economic and Business Research
(BEBR)
Your Logo
10. Introduction to Data Sources
Examples of Data Sources
Economic
Land Use/Spatial
Other
11. Introduction to Data Sources
North American Industry Classification System (NAICS)
Several digit levels of complexity
NAICS 11 Agriculture
NAICS 112 Animal Production
NAICS 1121 Cattle Ranching
12. Introduction to Data Sources
Info USA
http://ocgis2.ocfl.net/imf/imf.jsp?site=ocfl
County Business Patterns
http://www.census.gov/econ/cbp/index.html
FRED
http://fred.labormarketinfo.com/default.asp
Your Logo
13. Introduction to Data Sources
Examples of Data Sources
Demographic
Economic
Land Use/Spatial
Other
14. Introduction to Data Sources
Department of Revenue Codes
CODE DESCRIPTION
CONTAINER NURSERY - ABOVE
GROUND OPEN, SHADED OR
6930 GREENHOUSE
ORNAMENTAL LANDSCAPE
6900 PLANTS / TREES
MIXED CONTAINER AND FIELD
6940 NURSERY
FIELD NURSERY - IN GROUND
6910 OPEN FIELD OR SHADED
Your Logo
15. Introduction to Data Sources
Committed Land Use Inventory
PDNAME TOTRESUNIT SFUNITS MFUNITS THUNITS TOTNONRESF COMMSF OFFICESF INDSF HMTSUNITS
Foothills of Mt.
Dora PD 640 640 0 0 130744 130744 0 0 0
Colonial
Sunflower 575 190 385 0 135634 135634 0 0 0
Windsor
Services Office
Park Building 0 0 0 0 2880 0 2880 0 0
Robert Allen
Commercial 0 0 0 0 16800 16800 0 0 0
Your Logo
16. Introduction to Data Sources
Examples of Data Sources
Demographic
Economic
Land Use/Spatial
Other
18. map
%
6
n
1 3Cmapr
0ull
%3Cmapr
Introduction to Data Sources
Nielsen Claritas
Draw your own
polygon
Ten cents per
point/information
Used by market
consultants
Your Logo
19. Introduction to Data Sources
Data use depends on the
following:
Question
Methodology
Not all data is suitable for
all projects
Your Logo
20. Introduction to Data Sources
Q: How Many people live within the RSA?
Methodology
GIS Analysis
Quantitative Techniques
Data Sources Used
U-Code Layers
U.S Decennial Census
BEBR 2009 Population Estimate
Your Logo
21. Introduction to Data Sources
Q: Is there enough Industrial Land to meet
2030 demand?
Methodology
Quantitative Analysis
GIS
Data Sources Used
Info USA
Woods and Poole
DOR Codes
Committed Land Use Inventory
Your Logo
22. Introduction to Data Sources
P: Study Food Production in Orange County
Methodology
GIS Analysis
Literature Review
Database Review
Data Sources Used
USDA Agricultural Census
DOR Codes
Info USA database
Your Logo
24. Formats, Products, Getting Started
Creativity and Inspiration for Project
Design
Types of Products and Outputs
Project Management Process
Project Maintenance
25. Formats, Products, Getting Started
Creativity and Inspiration for Project
Design
Types of Products and Outputs
Project Management Process
Project Maintenance
26. Formats, Products, Getting Started
Creativity and Inspiration for Project Design
The 6 myths of creativity:
1. Creativity comes from creating types
You want everyone in your organization producing novel and useful ideas
2. Money is a creativity motivation
It is critical to match people to projects where their interest lie
3. Time pressure fuels creativity
Creativity requires an incubation period: let the ideas bubble up
4. Fear forces breakthroughs
People are more likely to have a breakthrough if they are happy
5. Competition beats collaboration
The most creative teams have the confidence to share and debate ideas
6. A streamlined organization is a creative organization
27. Formats, Products, Getting Started
Creativity and Inspiration for Project Design
Effective kick-off and brainstorming sessions:
1. An army of one
Group brainstorming really does not work that well.
Being in a group creates a set of distractions that is difficult to overcome:
competition, desire to look good, social inhibitions.
However, it is an important exercise in team-building:
1) alternate individual brainstorming with group sessions; 2) brainwriting
2. Asking the right questions
It is important to define the problem right.
The goal should be quantity of ideas, not quality.
3. Bad ideas
When brainstorming, you should be generating, not evaluating ideas.
28. Formats, Products, Getting Started
Creativity and Inspiration for Project
Design
Types of Products and Outputs
Project Management Process
Project Maintenance
29. Formats, Products, Getting Started
Types of Products and Outputs
1. Written documents
2. GIS products
3. Outreach materials
4. Online content
30. Formats, Products, Getting Started
Types of Products and Outputs
1. Written documents 3. Outreach materials
Report Boards
White Paper Presentation materials
Summary Brochures & handouts
Policy recommendation(s) Minutes/transcripts from
Issue Brief an outreach campaign
Issue(s) Series PowerPoint presentation
2. GIS products 4 Online content
Maps Web page(s)
Data layers Online information
Technical memorandum storage (ftp sites)
- data sources;
- assumptions;
- methodology;
- results
31. Formats, Products, Getting Started
Creativity and Inspiration for Project
Design
Types of Products and Outputs
Project Management Process
Project Maintenance
32. Formats, Products, Getting Started
Project Management Process
Your responsibilities as a project manager:
1. Establishing a project schedule
2. Defining the scope of the project
3. Proving periodic briefing to management staff
4. Serving as a resource to team members
5. Keeping the project focused and on schedule
6. Ensuring quality control and quality assurance
33. Formats, Products, Getting Started
Project Management Process
Steps in managing a project:
1. Identify a project goal
2. Define the scope, approach, limiting constraints
3. Establish a project schedule
4. List available resources that may be used for
background and information
5. Develop an outreach plan (if applicable)
6. Compile the project team
7. Schedule the project kick-off meeting
8. Develop a monitoring and reporting system
9. Ensure implementation and follow-up
34. Formats, Products, Getting Started
Project Management Process
Steps in managing a project:
1. Identify a project goal
What is the purpose of the project, study, process, or paper?
Why is it necessary, or being done?
2. Define the scope, approach and limiting constraints
Scope describes the work required
Approach describes the manner in which you will achieve the scope
Constraints time, costs, support and resources
35. Formats, Products, Getting Started
Project Management Process
Steps in managing a project:
3. Establish a project schedule
Provide specific due dates for delivery of
products and services and describe the tasks
Include data collection time
Include outreach activities and important
meetings (if applicable)
Include project hearing and approval dates (if
applicable)
Build in time for review of draft products
36. Formats, Products, Getting Started
Project Management Process
Steps in managing a project:
4. List available resources that may be used for background and information
Economic/demographic and spatial data sources
Technology (prof. software, GIS, keypads, etc.)
Other Department and Divisions
Policies/Codes/Plans
Previous studies and reports
Professional organizations and their publications
Communication Division (if any outreach is planned)
37. Formats, Products, Getting Started
Project Management Process
Steps in managing a project:
5. Develop an outreach plan (if applicable)
Create a list of stakeholders
Identify the issue, the message, the target
audience, and the tools used to distribute the
information
Develop an outreach schedule
Design a website component with materials for
posting and schedule frequent updates
38. Formats, Products, Getting Started
Project Management Process
Steps in managing a project:
6. Compile the project team
Balance your team
Define roles and expectations
Match the team members interests to tasks
Maintain organization and ensure that one key person is responsible for each
major task
Always acknowledge and give credit for contribution
39. Formats, Products, Getting Started
Project Management Process
Steps in managing a project:
7. Schedule the project kick-off meeting
Prepare an agenda and a draft outline
Establish a regular meeting time and place
Ensure that you are gathering the teams
feedback and making necessary adjustments
8. Develop a monitoring and reporting system
Keep the project on schedule, provide
updates
9. Ensure implementation and follow-up
40. Formats, Products, Getting Started
Creativity and Inspiration for Project
Design
Types of Products and Outputs
Project Management Process
Project Maintenance
41. Formats, Products, Getting Started
Project Maintenance
Project evaluation
measurement mechanism
evaluation schedule
Project implementation
implementation schedule
major milestones
Project update
monthly/annual/bi-annual/as-needed
Web site maintenance
maintenance schedule
person responsible
Data storage
43. Doing Research With GIS
Understanding GIS
and Extensions
Spatial Analyst
CommunityViz
Getting Started Source: latlabrafael.wordpress.com
44. Doing Research with GIS
GIS Geographic Information System
Set of computer tools that for working with data that are tied to a
particular location on the earth
Three components: Arc Map - Arc Catalog - Arc Toolbox
Helps planning, public works, engineering, and
government professionals with decision-making
Comprehensive Planning as an Example
Policy decisions on long-range changes to a communitys physical
environment and citizen participation
Socioeconomic and commercial demographics combined
to facilitate analysis and provide insights for community building
45. Doing Research with GIS
ArcGIS Extensions
3D Analyst Provides powerful and advanced visualization analysis
Spatial Analyst Broad range of powerful spatial analysis tools
Network Analyst Network based spatial analysis (routing, directions)
Schematics Schematic representation of ArcGIS Geodatabase
Geostatistical Analyst Spatial data exploration using statistical methods
Survey Analyst Suite of survey measurement-based analysis
Tracking Analyst Sophisticated analysis of time-related data
County Layers
http://ocgis2.ocfl.net/imf/imf.jsp?site=ocfl
46. Doing Research with GIS
Query
Queries extract features or records from a data
table and isolate for further use, such as printing,
calculating statistics, editing, graphing, or doing
more queries.
Two main categories: Attribute and Spatial
47. Doing Research with GIS
Spatial Analyst
Spatial Analyst provides a broad range of powerful spatial modeling
and analysis tools.
You can create, query, map and analyze cell based raster data,
perform integrated raster-vector analysis, derive new information from
existing data, and query information across multiple data layers.
48. Doing Research with GIS
CommunityViz
Planning software that runs on a GIS platform
Scenario 360 and Scenario 3D
Scenario 360
and Site
Builder 3D
toolbar
360 Analysis
360 Set up
48
49. Doing Research with GIS
Scenario 360
Create and experiment with hypothetical scenarios
Assess economic, environmental, social, and visual
considerations
Make and change assumptions on the fly
View impacts of proposed changes
Create 3D visualizations of scenarios
50. Doing Research with GIS
Doing Research with GIS
Scenario 3D
Creates beautifully realistic, interactive, sharable 3D scenes.
Google SketchUp models can be imported to create context-related
visualizations
51. Doing Research with GIS
Northgate Redevelopment Case Study using CommunityViz
Created new building points at the centroids of the existing building footprints:
Base Scenario: land uses and square footage from the PA website
Wellness Village Scenario: square footage, density and other development
parameters assigned based on a proposed development program
Ran the Common Impacts Wizard to compare the Base Scenario and the
Wellness Village Scenario
52. Doing Research with GIS
Getting Started on a GIS Project http://www.esri.com
Decide on a general topic of interest and research question
Select the tool or model to use
Determine the data needed for the project
Write the proposal according to established guidelines
Sources for free training (Virtual Campus) and recommended
trainings
http://training.esri.com/gateway/index.cfm?fa=catalog.gateway
County staff that can help
http://www.orangecountyfl.net/cms/DEPT/growth/fiscal/gis.htm
54. Putting Research to Work
Scenario Planning
Trend Analysis
Using Indicators
Putting It All Together
55. Putting Research to Work
Scenario Planning
To make sense of all this..
housing foreclosures hunger
H1N1 virus recession
unemployment budget deficits
climate change homelessness
commercial foreclosures
water supply fossil fuels
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56. Putting Research to Work
Why do scenario planning?
Organize staff knowledge and insights
Gather the publics feedback
Use possible outcomes as a learning tool
Form plans of action
Meet the needs of agencies/funders (FHWA)
Practice within planning profession
Deal with the problem of too much information
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57. Putting Research to Work
Scenarios are
plausible, but structurally different futures
(Heijden 1996)
stories that use consistent interpretations of
possible future events (Avin 2007)
Not as linear as forecasts
Not valid without logic or cause for existence
Not inherently good or bad (no straw men
allowedAvin 2007)
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58. Putting Research to Work
Scenario planning and The Art of the Long
View (Schwartz)
List driving forces (variables, trends, events)
Make a scenario grid (based on trends)
Imagine possible futures (stories from your
grid)
Brainstorm implications and actions
Track indicators (shows when scenario is now
reality)
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59. Putting Research to Work
Scenario planning and The Art of the Long
View (Schwartz)
Graphic from Your Future in 5 Easy Steps: Wired Guide to Personal Scenario Planning (Wired Magazine)
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60. Putting Research to Work
Schwartz advice on scenario planning
Include outsiders
Look far ahead
Start with both the present and the past
Do preliminary work in smaller groups
Hold workshops and discussion groups
Live in a permanent strategic conversation
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61. Putting Research to Work
Avins advice on scenario planning
Dont assume past patterns will make a
baseline (trends/markets change over time)
Clarify problems before goals and objectives
Limit megatrends, unless directly applicable
Limit total scenarios to 3 to 5 that are clearly
different (and brand using titles)
Use task forces and public forums
Get leadership support
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62. Putting Research to Work
Trend Analysis
Collecting everything you need to know
when you need to know it
then fitting it all together.
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63. Putting Research to Work
Trend AnalysisData Sources
Email newsletters or RSS feeds
OPPAGA
Florida Trend
John Burns Real Estate
Planetizen
Urban Land Institute (ULI)
Local Initiatives Support Corporation (LISC)
Others?
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64. Putting Research to Work
Trend Analysis
Google Reader
Organize your RSS feeds
Blogs and Twitter
Other RSS optionsnow in Safari and
Firefox, Microsoft Outlook 2007
Google Alerts
Receive emails with links to resources
Customize keywords and number of alerts
Daily or weekly email
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65. Putting Research to Work
Indicators
how we know what we think we know about
scenarios and their stories
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66. Putting Research to Work
Developing and tracking indicators
Can have several uses
May be used as evaluation criteria to compare
scenarios
May be used as monitoring criteria to
determine arrival of a scenario
Can carry forward key points from process of
scenario development
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67. Putting Research to Work
Developing and tracking indicators
Set benchmarks for measurement
Obtain public input to the extent possible
Survey established indicators in environment
for potential use (ex. HCI, myregion.org)
Monitor news, data releases, other sources
Evaluate developments quarterly
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68. Putting Research to Work
Putting It All Together
Examples of scenario-based research
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69. Putting Research to Work
Putting It All Together
Issue Briefs
Summaries
White Papers
SeriesHOK Landscapesthe Futurity Series
http://campaign-archive.com/?u=4c3469dd28c20d086ef782e8b&id=ea2dba5f07&e=9fb2884b26
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70. Putting Research to Work
HOKs Futurity TrendsDo you agree?
Social change from Millennials*
Increasingly urban planet
Alternative energy
Climate change and sustainability
*Issue Brief at http://www.hok.com/Planning/pdf/Landscapes_June_2009/Social%20Change.pdf
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71. Putting Research to Work
HOKs Futurity TrendsDo you agree?
Water and food supply shortages
Science and technology advances
New frontiers (life on the moon)
Mega multi-national corporate growth
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72. Putting Research to Work
Putting It All Together
myregion.org
Seven-county Central Florida region
Data collection for several reports
Values Study
Social Capital Survey
Several others (very useful for references and
indicators)
Central Florida Regional Indicators report
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73. Putting Research to Work
Putting It All Together
myregion.org
How Shall We Grow? Regional Visioning
Public participation process
Four land use scenarios
Public voting online/Bright House
Selection of 4Cs scenario
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