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NR 422- Project Management Jim Graham Spring 2010.

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Presentation on theme: "NR 422- Project Management Jim Graham Spring 2010."— Presentation transcript:

1 NR 422- Project Management Jim Graham Spring 2010

2 Credit Always give credit to your sources –Name, organization, URL, etc. –To not do so: In school is cheating Out side school; it’s against the law You are required to do your down work –Data can be created as a team –Each final product must be assembled individually

3 Dave’s Book – GIS Review Chapter 1: All Chapter 2: 2.1, 2.2.1, 2.5 Chapter 3: All Chapter 4 to 4.2.2 –Also: 4.2.6, 4.6

4 Standard Map Elements Title Maps Legend North Arrows Scale Bars Sources, author(s) Projection, Datum Regional Map

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9 GIS Professional Produce GIS reports, articles, posters, and web sites that are: –Accurate & Precise –Astatically pleasing –Informative –Legal –Include the standard cartography elements: Spatial data, legends, scale bars, north arrows, regional maps, credits, author(s), and projection & datum Are recognized as authors!

10 GIS Data Attributes (dbf) Spatial Data (shp) Metadata (xml) Projection (prj) Joins and Relationships Processing Models Layer files: Symbology

11 Various Formats Shapefile Coverage Rasters GeoDatabases All can be thought of as: –Spatial data –Attribute table

12 Definitions Shape –Points, polylines, or polygons describing one feature on the earth Feature –A Shape with attributes Feature class – one type of feature (point, polygon, polyline) Collection of features –Group of features of the same type (Shapefile) Dataset –Set of related collections of features (i.e. the Shapefiles for Rocky)

13 Arc Data Storage ShapefilesCoveragesGeoDatabases Collection of datasets Folder of Shapefiles ArcInfo Workspace GeoDatabase DatasetFolder of Shapefiles CoverageFeature dataset Collection of features ShapefileFeature class FeaturesPoint, Multipoint, Polygon, Polyline Point, Polygon, Polyline, etc. Point, Multipoint, Polygon, Polyline, Network Annotation

14 GIS Data Flow Project, resample Processing Processed Data Original Data Final data, maps Tables, text Analysis

15 Project Organization Project –Original Data Workspace for Coverages (folder) Folders based on topic –Processing Data Folders based on projection/datum –Folders based on topic –Final Data Folders based on projection/datum –Folders based on topic

16 GIS Data Organization One project –Original Data –Processing –Final data Multiple projects –Each projects data –Reused data Original Data Processing Final data

17 The 7 Habits of Highly Effective People 1. Be Proactive 2. Start with the end in mind 3. Put First Things First 4. Think Win-Win 5. Seek First to Understand, Then to be Understood 6. Synergize 7. Sharpen the Saw –Steven Covey

18 Scheduling Define the deliverables/products Document the deadline Work backwards Multiply the schedule by 1+?

19 Schedule 1.Deadline and deliverables/products 2.Reviews and updates 3.Creating documents (inc. web sites) 4.Analysis 5.Processing 6.Data preparation 7.Acquiring data 8.Proposal review 9.Proposal process

20 Jim’s Habits Panic up front – when it will make a difference Check your resources Have backups Don’t stay stuck (20 minutes) Do what it takes to deliver Find out what customers really want Do the right thing Model the behavior you want in others

21 The Tire Swing What the customer needed What was designed What marketing suggested What managemen t approved What was delivered Alan Chapman, http://www.businessballs.com/treeswing.htm

22 Documentation Maintain Metadata throughout the project –Make notes in “readme.txt” files in each folder –Go back and fill in the metadata when you have time Critical: –Sources: location and names –Accuracy, Precision, Error Rate

23 Working with Others Listen, really listen What is important to them? Divide up tasks: –Large enough for each person to make progress –Fit the task to the person –Coordinate, don’t micro manage –Check on progress: weekly to monthly

24 Budgets Overhead: ~50% –Administration –Physical Space –Networks/Internet –Phones –Office Supplies –Heating & Cooling People –Salary –Benefits Computers Data –Remotely sensed –Field data collection Printing


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