Ppt on sources of data collection

Stephanie Booth Development ddPCR Instrument. Sample Collection and Processing Water Sample Filter Extraction Kit Lysate Pure DNA or RNA Fluorophore/Quencher.

Development ddPCR Instrument Sample Collection and Processing Water Sample /DNA is NOT a match 0 5 1x dilution (1µL Santa Cruz Wharf sample in 5µL Reaction) Data Output 10x dilution (0.1µL Santa Cruz Wharf sample in 5µL Reaction) 6 PROCESS FLOW DIAGRAM /Extensible to fully-autonomous system w/ Multi-Primer Cassette PROTOTYPE 2-B Portable Biological Source Tracking Instrument 7 CRITICAL FEATURES 1.Continuous On-Site Detection of Target Bacteria and Viruses (DNA, RNA, Proteins and Metabolites) with a single/


Remote Data Sources in Primo Ebsco API WorldCat API Local Content.

results list Institutional Repositories & Primo Nathan Mealey, PSU Four Components of a Pipe ●Data source ●Scope ●Normalization rule ●Pipes Step 1: Create a data source Key Fields 1.Source format 2.File splitter 3.Name 4.Input record path Step / Bill Kelm, Willamette DSpace Collection 1. Created my new data source. DSpace Collection 2. Set up the new scope value. DSpace Collection 3. Set up the new pipe: DSpace Collection 4. Ran the pipe to harvest the collection. DSpace Collection 5. Harvested, but still/


ERCOT SYSTEM PLANNING Dynamic Model Data Management.

to resolve any concerns on the submitted model and parameters. ERCOT will be a single source to collect and compile all REs’ dynamic models and parameters and provide the data set to DWG for flat start base case creation. 4 Proposed Process: TSPs REsERCOT RARF/concerns 5 Draft of NERC MOD Standard MOD-026-1, MOD-027-1, MOD-025-2 These draft standards applies to Generator Owner and Transmission Planner Considering RARF is the adopted process in ERCOT region to collect all the model data, potential changes may/


------------- Image1 ------------- Field Data Digital Image File Name 15194 Source Title Miscellany Source Created or Published ca. 1571- 1600 Physical.

. 1r Digital Image Type FSL collection Source Call Number L.b.526 ------------- Image1 ------------- Field Data Digital Image File Name 5790 Source Creator Donne, John, 1572-1631. Source Title letter Source Created or Published 1601 Physical Description f. 1v Digital Image Type FSL collection Source Call Number L.b.526 ------------- Image1 ------------- Field Data Digital Image File Name 15246 Source Creator Great Britain. Privy Council. Source Title Copy of a Privy Council order to/


Vision Application Checklist. Collect Key Information ■ Don’t waste time chasing bad opportunities ■ Streamlines communication flow ■ Don’t know what.

Vision Application Checklist Collect Key Information ■ Don’t waste time chasing / Part Rejection Method How do you plan to eject part? Solenoid Indicator Light PLC input Camera Triggering Source How are you going to tell the camera to capture and image? Photo eye Proximity sensor Encoder /by Working Distance Lens Focal Length WD Determined by Field of View Size Lens Focal Length Lens Charts and Calculators PresencePLUS  Job Aid Choosing a Lens (P/N VR_P5_S1_E) iVu  Data Sheet iVu Lens Kit (P/N 145194 ) iVu /


Session 4: Renewable energy sources statistics United Nations Statistics Division International Workshop on Energy Statistics 24-26 September 2012, Beijing,

Beijing, China Renewable energy sources Important because: They address many environmental issues Reduce the dependency on fossil fuels A number of targets are set at national and international level on the use of renewable energy Outline Classification/ as they calorific values are different IRES No specific measurement units are recommended for national data collection (most suitable for the circumstance) However, certain units are recommended for dissemination. In particular, Fuelwood -> cubic metres /


INFO 4470/ILRLE 4470 Social and Economic Data Federal Data Providers (extras) John M. Abowd and Lars Vilhuber January 31, 2011.

M. Abowd and Lars Vilhuber January 31, 2011 Example: Toxic releases - Toxic releases are regulated - Data is thus collected - Why of interest? * “Fetal Exposures to Toxic Releases and Infant Health”, Janet Currie and Johannes F. Schmieder (2009)Fetal Exposures to Toxic Releases and Infant Health - How to find it? Sources for Toxic Release data - Through http://www.fedstats.govhttp://www.fedstats.gov - Through http://www/


CATEE PRESENTATION– DECEMBER 18, 2013 DIANA D. GLAWE, PHD, PE, LEED AP ENGINEERING SCIENCE DEPARTMENT COLLECTING & USING CONDENSATE ON SITE.

water) ON SITE WATER SOURCES Condensate Rainwater Cooling tower blowdown Reverse osmosis wastewater Gray water Etc. CONDENSATE Water that collects on a cool surface because the temperature of the surface is below /Source: San Antonio Condensate Collection and Use Manual for Commercial Buildings. Pending publication) * Patented by Trent Technologies, Inc. (CostGard) EFFECTIVE DESIGN AND OPERATION– AUTOMATED MONITORING Drip pan overflow alarm Condensate meter data collection Make-up water meter data collection/


Libraries and Data Management Joan Starr California Digital Library June,

-term identifiers An infrastructure to publish and get credit for sharing research data Data Publication Open source add-in for Microsoft Excel as a data collection tool EZID: long-term identifiers made easy take control of the management and distribution of your research, share and get credit for it, and build your reputation through its collection and documentation Primary Functions 1. Create long-term identifiers 2. Manage identifiers/


(1) WattDepot: A software ecosystem for energy data collection, storage, analysis, and visualization Robert S. Brewer, Philip M. Johnson Collaborative.

M. Johnson Collaborative Software Development Laboratory Information and Computer Sciences Dept University of Hawaii at Manoa http://csdl.ics.hawaii.edu/ (2) Motivation Research on changing energy use behaviors Need to collect & analyze energy data Requirements Collect data from many meters Sub-minute data collection Easy to simulate sensor data Internet-accessible repository Visualization variety & flexibility Open source Could not find an existing solution Developed WattDepot (3) Architecture Devices/


A Data-Centric Web Application Security Framework Jonathan Burket, Patrick Mutchler, Michael Weaver, Muzzammil Zaveri, and David Evans University of Virginia.

of Virginia http://guardrails.cs.virginia.edu GuardRails 2 Web applications are easier to create than ever! 3 Securing web applications is not nearly as easy! 4 5 6 7 “> alert(document.cookie); 8 9 10 11 Application Page A Page B Page C Page D Data/ active_children.collect {|c| c.id} conditions = ["#{Project.table_name}.id IN (#{ids.join(,)})"] 22 if include_subprojects && !active_children.empty? ids = [id] + active_children.collect {|c/.cs.virginia.edu Full source code can be downloaded from GitHub Contact Info:/


Pi In The Sky (Storing Big Data on Cloud) Jenish Koirala Claflin University Mentors: Dr. Raghu Raj, Dr. Richard Loft SIParCS at Mesa Lab, NCAR Boulder,

Its just $35 4 System Overview Collects Data Displays Information Uploads Files to cloud User asks information Transmits Data Queries Receives Reads data from file Populates database Weather Sensors/hosting software (like Dropbox) Version used: 7.0.1 Why OwnCloud? Open Source Already been used and tested on RPi Free Free Free!! 7 OwnCloud System/ 8 Modules and Libraries Pushing files using Pyocclient Library disk2 Making a copy of file on disk1 or disk3 use Secure Copy disk2 disk3 Sensor Processor 9 put_file/


Secondary Data Data previously gathered by someone other than the researcher for some purpose other than the research at hand.

gathered by someone other than the researcher for some purpose other than the research at hand. Sources of Secondary Data zInternal - data collected within the firm. zExternal - data collected outside the firm. External Secondary Information zPublished (free or nominal fee) y Government x(e.g. government census data - www.census.gov) y Trade Magazines x(e.g. Sales & Marketing Management) y Trade Associations x(e.g. National Automotive/


 Thank you all for your support  Evaluation-web implemented at all funded sites and is being used for CTRS client level data collection.  Data collected,

is being used for CTRS client level data collection.  Data collected, processed, and reported in a timely manner  Trend Analysis Conducted to Assess Program Performance.  Improved Quality of Data  Increased Integration with RWJ Data and Monthly Progress Reports Counseling Testing /only** NJ State grants for Counseling and Testing** *PA –Program Announcement Sites Not Funded by NJ DHSTS Funded by sources other than the above*  Total HIV positive test at All Sites – 584  Overall Seropositivity Rate – 0.6/


RapidformXO Design from 3D scan data TM Maarten Houben March 2007.

Create parametric CAD models from 3D scan data  Verify parts with deviation analysis and GD&T  Collect, clean and optimize 3D scan data ©2006 Rapidform Inc. All rights /way to effectively convert 3D scan data into parametric CAD models ©2006 Rapidform Inc. All rights reserved. Evolution of RE Software 1 st Generation Design/mesh data Import polygon mesh data Other Data Source Bundled 3D Scanner Software ©2006 Rapidform Inc. All rights reserved. XOR workflow Import polygon mesh data Import polygon mesh data /


May 2007 © InSites 4 Module CP.07.M4p190.4-20.ppt 1 Reflection Questions Concerning Data Collection Does your data collection focus on and strengthen what.

a trusting environment where people with differing perspectives feel physically and emotionally safe? Will your data collection be conducted in familiar surroundings to increase the comfort of your sources? Is your data collection process designed to be conducted at a pace and with responsibilities that are reasonable for your sources and those collecting the data? May 2007 © InSites 4 Module CP.07.M4p190.4-20.ppt 4 Does your/


Windows Database Applications CIS 341 Chapter 5. Objectives Update database Navigate records Event handler Bound control maintenance Update data source.

Navigate records Event handler Bound control maintenance Update data source Sequence updates Data Objects DB (original) Data Adapter Dataset Retrieve Update data Create dataset & save updates Data Grid Format Data Table (0) Data Rows Collection Data Row (0) Data Row (1) Data Tables Collection Data Set RowState property DataRowState EnumPurpose AddedIndicated a new row DeletedMarked for deletion DetachedNot part of a collection ModifiedChanges made to row UnchangedOriginal row values Change Management/


Data from : Chip Redmond – Weather Data Library/Mesonet Manager GMD 3 Annual Meeting; 3/9/16.

additional tools for: Wheat Sorghum Displays/data analysis Climate comparison by location** *where equipped, first steps towards statewide network **visit climate.ksu.edu for more statewide climate data Siting Location analysis -Long term placement (20+ years) -Wide area without obstructions -Representative of region -No nearby irrigation -Year round accessibility -Access required for a concrete base Data checks Data is collected and QC’d for consistency & accuracy/


Zone 4 Line A Preliminary Suspended Sediment Load Estimates HY08 Rand Eads RiverMetrics LLC 503-435-7516 Sources.

rivermetrics@gmail.com 503-435-7516 Sources Pathways and Loadings Workgroup December 8/ # 2b Changes in Data Collection Methods from HY07 to HY08 Bed-mounted boom provided complete data record for season Turbidity /sensor and sampler intake at depth-proportional sampling position Improved debris shedding Possible increase in sand to fine ratio Item # 2b r 2 = 0.89 r 2 = 0.90 r 2 = 0.89 Item # 2b 0.14 Item # 2b 0.12 Item # 2b 0.38 Item # 2b 0.12 Storms account for ~95% of/


Data collected by the researcher Observations, surveys, experiments Student primary source Questions created should help give more precise answers.

others and used for secondary analysis Found in news, Internet, statistics Student not part of data collections or questioning Can create questions based on data Create a collage showcasing various sources of second-hand data. The difference between first-hand and second-hand data is... What is your favourite holiday? Who is your favourite singer? What is your favourite sport to watch on TV? Student Workbook: Pages 31/


Python 20021080 Hyunjong Lee. contents  Introduction  Syntax & data types  Tools  Python as CGI.

 Garbage collection  Module structure (glue language)  Fast development cycle Syntax  Syntax is very simple  Similar to most of other languages  Indentation sensitive High level built-in data types  Complex number  List (can be nested)  Tuples  Dictionary Tools  Py2exe – convert python script into exe file  Python2c – convert python script into C source file  SWIG(simplified wrapper and interface generator) – glue code generator Python as CGI/


Primary Data Collection Method: Survey Design. Primary Data Collection Primary data collection is necessary when a researcher cannot find the data needed.

Primary Data Collection Method: Survey Design Primary Data Collection Primary data collection is necessary when a researcher cannot find the data needed in secondary sources Or when the data extracted from secondary sources are not reliable or correct Methods/Rate Increase perceived rewards ▫Be polite, say thank you ▫Summary of results ▫Tangible rewards (money, gift…can be very effective) Increase trust ▫Provide a sense of legitimacy ▫Make responding to the questionnaire seem important Test the questionnaire/


ITunes Version 4.7. iTunes Features: Copy & Store Music from CD Collection Add GarageBand Music You Mixed Buy Songs From iTunes Music Store Import Music.

7 iTunes Features: Copy & Store Music from CD Collection Add GarageBand Music You Mixed Buy Songs From iTunes/Stars or Control Click Track>My Rating Click My Rating Heading to Sort Select Radio From the Source List Select Category>Select Station>Return Key Connection Speeds Advanced>Open Stream Type in URL for Internet/ Storage Space Holds About 74 minutes of sound DVD Storage Space Holds About 1,000 Songs & Can Store Any Audio Format File Formats MP3 Stores One File Format Data CD Can Store Any Audio Format /


HYSWEEP® SURVEY HYPACK 2013.

HYPACK 2013 HYSWEEP® Survey Multibeam Survey Program Collects and logs multibeam and support sensors. Displays /. Select Display Styles. Setup QC tests. Enable Layers. Use Device Selection to select data when there is more than one source. 5 Profile and 3-D Seafloor Profile Window Single sweep from aft looking forward. Color/(Digibar). HYSWEEP® Sound Velocity Editor Squat and Settlement Enter a table of draft adjustment vs. speed. Be careful using this. Draft lookup is based on speed over ground, which/


CEDARS Data Warehouse (CDW) CDW at 30,000 ft. May 09 th, 2013 Terra Dominguez Data, Research & Federal Policy

) Real time, transactional data Open to the public TAS MFR/AFR School Safety CTE N & D EC ESL Homeless Data Sources Data Systems NC WISE EDDIE /collected PII – ‘Personally Identifiable Information’ and must be protected –No detail level data is used for Federal Reporting –FERPA guidelines are enforced and dictate how any detail level data is to be used Solely dependent upon accurate UIDs NC WISE ID 1234567 CECAS ID A729 Migrant ID 2779 UID Matching Engine CTE NC WISE LEP Migrant Immigrant EC With the help of/


By Tracey Windley and Jasper Nance Professor Herb Hess Kevin Buck 2006 ASEE Annual Conference 6/19/2006 Instant Data Gathering, Processing, and Display.

dollars from governmental and private sources alike over the past 9 /of data collection may cause researchers to become inattentive Time Costly Data collection can be costly and labor intensive. Solution Automation! 6 Problems With Data Organization and Data Presentation Poor data formatting could result in data loss or corruption Solution Data must be recorded and stored uniformly Data must include information about the conditions of the test and about the Researcher Data must be easily searchable Data/


COUNTY LOCATION QUOTIENTS: A collection of 12 location quotients maps for each industrial sector in 2000 By David L. Darling CD Economist And Sandhyarani.

COUNTY LOCATION QUOTIENTS: A collection of 12 location quotients maps for each industrial sector in 2000 By David L. Darling CD Economist And Sandhyarani Patlolla Department of Agricultural Economics Kansas State University Manhattan, Kansas Allen / Morris 1.23 McPherson.48 Public Administration Location Quotients Map-12 Sandhyarani Patlolla David L. Darling June 2003 Data Source: U.S. Census Bureau, Employment by industry data K –State Research and Extension. Red: 1.01 & Greater Blue: 0.75 & Lower Black: In/


UNIT SIX MARKET RESEARCH Ch. 6 The Research Process Steps in the Process -ID the problem -Conduct secondary research data collected from some other purpose.

some other purpose -Select/design primary research original research data -Collect data -Analyze data Market Research How is data? Experiment: minor league ticket prices Observation: sports apparel kids a wearing Survey: questionnaire Focus Groups: panel discussion Market Research Sample: How to select the sample Sample size Data Mining: collect data from several data sources Report and Analyze Data Mission Statement: an outline of the business’s purpose and the products and services/


Collect” Collaboration 23 – 25 March 2015 International Collaboration Sprint ABS, CBS, SNZ and STC 1.

: Implement new QDT CBS: QDT (PROD) STC: TBD - Questionnaire design + dev + test (consider collaborationfor FY2015/16). Census 2016 prod + CATI/CAPI collection under CMP. 3.Admin data ABS: Expand to other sources STC: TDD – expansion of admin data under ICOS SNZ: Build infrastructure 2016-17 Opps 4.Channel Management ABS: Implement CBS: CAPI (build Blaise 5), CATI (req investigate), ?PAPI (req investigate) 5.Resource Management/


WASH GAP Analysis (Ghotki) December 24, 2010.  The Gaps may be less then the that of presented here because WASH Cluster didn’t received any updates.

of presented here because WASH Cluster didn’t received any updates from IRCS, MSM and Pak Government regarding their Intervention in Northern Sindh and also due to Less reporting from WASH Cluster Partners. Source: WASH Cluster Information Management (based on Data collected/ Taluka NameHygieneNFIsSanitationWater Blank 7000 Ghotki Taluka 210003025456002156 Mirpur Mathelo Taluka 32928 Source: WASH Cluster Information Management (based on Data collected from WASH Cluster Partners till 18-12-2010, & PDMA Update/


AASBO Data Collection Project Ken Hicks, Dysart USD Jim Migliorino, Deer Valley USD.

? To improve a process or project Increases accuracy of decisions For most, this is used for IBA or Negotiations (Comparison Districts) Data - Data collection is a process used to prepare and collect information. Data - What should be compared? This discussion should /get similar districts. −Scottsdale USD should not be comparing to Murphy ESD. Regional and Type of district should be similar. Reports Data - What data source? Use AFR whenever possible. Use budget only for current year and return to AFR after/


Open access to biodiversity data: the speciesLink experience Dora Ann Lange Canhos

Access Win98 Biota FreeeBSD PostgreSQL ? ? ? ? ? speciesLink data providers: biological collections Challenges  Integrate data from  different taxonomic groups  distributed in different collections  Regardless of  where the collections are located  what software the collections uses  the Internet connectivity available  the expertise available  Without changing the routine  Maintaining full control of data by the collection  Not expensive (open source and free software)  Integrated with other/


TABLE-TOP EXERCISE: INDIAN OCEAN SCENARIO MAKRAN SOURCE Shallow, Offshore, Mw9.0 Training Programme in Seismology and Tsunami Warnings Kuala Lumpur, Malaysia,

SEISMIC DATA COLLECTION & ANALYSESSEISMIC DATA COLLECTION & ANALYSES SEA LEVEL MEASUREMENTS & ANALYSESSEA LEVEL MEASUREMENTS & ANALYSES DECISION-MAKING PROCESSESDECISION-MAKING PROCESSES MESSAGE CREATION & DISSEMINATIONMESSAGE CREATION & DISSEMINATION CHECKLIST Indian Ocean Events - Initial Bulletin EQ SOURCE CHARACTERIZATION /> 7.8Ocean-Wide Tsunami Watch INDIAN OCEAN BULLETIN CRITERIA Makran Accretionary margin, location of 1945 Tsunami in this region Island Arc Volcanics Mud Volcanoes 1945 A Mohktari et /


May 2007 © InSites 3 Module CP.07.M3p080.4-20.ppt 1 CLIP Inquiry Plan Template Inquiry Question Information Needed to Answer Inquiry Question Data Sources.

Plan Template Inquiry Question Information Needed to Answer Inquiry Question Data Sources Data Collection Methods Data Collectors Timing and Location of Data Collection Plan for Meaning Making from Data Gathering Data and Making Meaning from Data May 2007 © InSites 3 Module CP.07.M3p080.4-20.ppt 2 CLIP Inquiry Plan Template Type of Assistance NeededPossible SourcesComments Assistance Needed to Carry out Data Collection Plan May 2007 © InSites 3 Module CP.07.M3p080.4/


Blueprint Integrated Pilot Programs A community system of health supported by HIT Craig Jones MD Director, Vermont Blueprint for Health

Collection Data Source Data transmission & transformation VITL / GE Data Analysis Data Reports & Uses EMR Reporting Tool or Analyst Public Health Registries & Databases VDH Health Surveillance Analytic Database BISCHA Multipayer Database VCHIP Databases VCHIP Analysis & Report Generation BISCHA Reports VDH Health Surveillance Analyst Contracted Analysis Services Blueprint Integrated Pilots Evidence Based Quality Improvement Health Information Exchange “Cloud” for secure, privacy protected interchange of/


SATELLITE AND AERIAL IMAGE DATA, MOBILE COMPUTING, GIS, AND GPS FOR INTEGRATED CROP MANAGEMENT (ICM) Chuck O’Hara, Dan Reynolds, Roger King John Cartwright,

Accuracy Assessment Field Data Compilation Aerial MSI Data Collection Automation of NDVI Processing Vegetation Information Product Availability Standardize Data Products Development Data Distribution Planning Year Two Plans Implement PDA/GPS/GIS Technologies Continue Aerial MSI Collection and First Year Data Collection Components Satellite MSI Data Collection Bare Soils Aerial HIS Data Collection Compile Registration Accuracy Information Validate Data Products Improve Data Distribution Remote Sensing/


P – D – S – A What is it and why use it?. Continuous Improvement Cycle (PDSA) PLAN Identify improvement opportunity, collect baseline data and plan the.

(PDSA) PLAN Identify improvement opportunity, collect baseline data and plan the change DO Implement the change and collect data STUDY Analyze the results ACT Adopt /data – by number of, not name! 3.Use a +  to evaluate all learning opportunities. 4.Develop a plan for dealing with the  ’s in the next learning cycle. Post the plan. Do the plan. 5.Study what happened. 6.Make improvements based on what was learned. Workbook page 33 Getting Started – The Work Core Classroom & Student Learning Processes Source/


A Collective Impact Primer By June Sobocinski February 2013.

involves a centralized infrastructure, supported by dedicated staff It must have the commitment of important actors from different sectors It involves the adoption of a common agenda on how to solve the problem It involves shared measurement across organizations, continuous communication, and mutually reinforcing activities Isolated impact Similar organizations collect quality data, but are isolated and not coordinated with others Coordinated impact Similar organizations/


Shared Community Health Needs Assessment (CHNA) Creating The Story About Our Data Cumberland County Fall 2015/Spring 2016.

Shared Community Health Needs Assessment (CHNA) Creating The Story About Our Data Cumberland County Fall 2015/Spring 2016 Maine SHNAPP Funders 4 Phases of the SHNAPP Process Data Collection & Analysis Needs Assessment Reporting Community Engagement Health Improvement Plans Data Included in the Shared CHNA Reports Data Quantitative Data 25 Secondary Sources SHNAPP Stakeholders Survey Deliverables State-level Shared CHNA Report County-level Shared CHNA Reports Bangor, Lewiston/Auburn, Portland/


Shared Community Health Needs Assessment (CHNA) Creating The Story About Our Data Franklin County Fall 2015/Spring 2016.

Shared Community Health Needs Assessment (CHNA) Creating The Story About Our Data Franklin County Fall 2015/Spring 2016 Maine SHNAPP Funders 4 Phases of the SHNAPP Process Data Collection & Analysis Needs Assessment Reporting Community Engagement Health Improvement Plans Data Included in the Shared CHNA Reports Setting the Stage for Our Story Shared CHNA data tell a story Data interpretation Your role in the story Pulling it all together/


Shared Community Health Needs Assessment (CHNA) Creating The Story About Our Data Hancock County Fall 2015/Spring 2016.

Shared Community Health Needs Assessment (CHNA) Creating The Story About Our Data Hancock County Fall 2015/Spring 2016 Maine SHNAPP Funders 4 Phases of the SHNAPP Process Data Collection & Analysis Needs Assessment Reporting Community Engagement Health Improvement Plans Data Included in the Shared CHNA Reports Setting the Stage for Our Story Shared CHNA data tell a story Data interpretation Your role in the story Pulling it all together/


Shared Community Health Needs Assessment (CHNA) Creating The Story About Our Data Penobscot County Fall 2015/Spring 2016.

Data Penobscot County Fall 2015/Spring 2016 Maine SHNAPP Funders 4 Phases of the SHNAPP Process Data Collection & Analysis Needs Assessment Reporting Community Engagement Health Improvement Plans Data Included in the Shared CHNA Reports Setting the Stage for Our Story Shared CHNA data tell a story Data/& play in Penobscot County Stakeholder Survey – Total 1,639 surveys; Penobscot County 185 surveys Source: Maine SHNAPP Stakeholder Survey, 2015 Drug & Alcohol Abuse Penobscot County Per 100,000 population /


Shared Community Health Needs Assessment (CHNA) Creating The Story About Our Data Sagadahoc County Fall 2015/Spring 2016.

Shared Community Health Needs Assessment (CHNA) Creating The Story About Our Data Sagadahoc County Fall 2015/Spring 2016 Maine SHNAPP Funders 4 Phases of the SHNAPP Process Data Collection & Analysis Needs Assessment Reporting Community Engagement Health Improvement Plans Data Included in the Shared CHNA Reports Data Quantitative Data 25 Secondary Sources SHNAPP Stakeholders Survey Deliverables State-level Shared CHNA Report County-level Shared CHNA Reports Bangor, Lewiston/Auburn, Portland/


How Crash Data is Collected and Analyzed 10:50 AM-12:05 PM Room C December 3 rd, 2015 Kevin Murphy, DVRPC.

In Which At Least One Person Dies Within 30 Days Of The Crash. December 3 rd, 2015 How Crash Data is Collected and Analyzed Crash Data Definitions Severity Injury Crash: A Police-reported Crash That Involves/ authorized persons Narratives Diagrams Other data sources/products: Other data sources/products: public PA Crash Facts & Statistics NJ State Police, NJDOT Crash Records Fatality Analysis Reporting System (FARS) December 3 rd, 2015 How Crash Data is Collected and Analyzed Panelists: Kristin Rash/


Shared Community Health Needs Assessment (CHNA) Creating The Story About Our Data Androscoggin County Fall 2015/Spring 2016.

Data Androscoggin County Fall 2015/Spring 2016 Maine SHNAPP Funders 4 Phases of the SHNAPP Process Data Collection & Analysis Needs Assessment Reporting Community Engagement Health Improvement Plans Data Included in the Shared CHNA Reports Setting the Stage for Our Story Shared CHNA data tell a story Data/play in Androscoggin County Stakeholder Survey – Total 1,639 surveys; Androscoggin County 130 surveys Source: Maine SHNAPP Stakeholder Survey, 2015 Drug & Alcohol Abuse Androscoggin County Per 100,000 /


"Data sources index" a web application to list projects in Hadoop Luca Menichetti.

": "Experiment Dashboard Job Monitoring Atlas" }, { "name": "description", "value": "the job monitoring logs of all executions submitted by Atlas in.. },... 12 Example – REST API (2) # Create a project curl -X POST -d @templates/jm-atlas_CJ_template.json -H "Content-Type: application/vnd.collection+json" awg-virtual/data-sources-index/rest/projects/ # Retrieve curl awg-virtual/data-sources-index/rest/projects/jm-atlas # Delete curl -X DELETE awg-virtual/


Shared Community Health Needs Assessment (CHNA) Creating The Story About Our Data Lincoln County Fall 2015/Spring 2016.

Shared Community Health Needs Assessment (CHNA) Creating The Story About Our Data Lincoln County Fall 2015/Spring 2016 Maine SHNAPP Funders 4 Phases of the SHNAPP Process Data Collection & Analysis Needs Assessment Reporting Community Engagement Health Improvement Plans Data Included in the Shared CHNA Reports Data Quantitative Data 25 Secondary Sources SHNAPP Stakeholders Survey Deliverables State-level Shared CHNA Report County-level Shared CHNA Reports Bangor, Lewiston/Auburn, Portland/


Shared Community Health Needs Assessment (CHNA) Creating The Story About Our Data Washington County Fall 2015/Spring 2016.

Data Washington County Fall 2015/Spring 2016 Maine SHNAPP Funders 4 Phases of the SHNAPP Process Data Collection & Analysis Needs Assessment Reporting Community Engagement Health Improvement Plans Data Included in the Shared CHNA Reports Setting the Stage for Our Story Shared CHNA data tell a story Data/& play in Washington County Stakeholder Survey – Total 1,639 surveys; Washington County 133 surveys Source: Maine SHNAPP Stakeholder Survey, 2015 Drug & Alcohol Abuse Washington County Per 100,000 population /


Shared Community Health Needs Assessment (CHNA) Creating The Story About Our Data Somerset County Fall 2015/Spring 2016.

Shared Community Health Needs Assessment (CHNA) Creating The Story About Our Data Somerset County Fall 2015/Spring 2016 Maine SHNAPP Funders 4 Phases of the SHNAPP Process Data Collection & Analysis Needs Assessment Reporting Community Engagement Health Improvement Plans Data Included in the Shared CHNA Reports Setting the Stage for Our Story Shared CHNA data tell a story Data interpretation Your role in the story Pulling it all together/


Chapter 8. To Show Why Retailers Should Research To Examine Retail Information Systems To Describe the Marketing Research Process To Discuss the Data.

Internal vs. External Collectors Sampling Methodology –Probability –Nonprobability Data Collection Methods –Survey –Observation –Experiment –Simulation Provide Informal Feedback All Data to Be Collected Onsite Gather Information for Suppliers Pass Along Consumer Buying Characteristics Participate in Single Source Data Collection Why Retailers Should Systematically Collect and Analyze Information for Strategy Development The Role of Retail Information Systems The Marketing Research Process and its Components/


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