Differentiate data conversion from data transformation

• Data transformation: a change of coordinates in which a new set of coordinates replaces an old one. It convert the coordinates through translation, rotating, and scaling.

• Data Conversion: the translation of data from one format to another that is suitable for use in a particular software application. It is a conversion from one way of coding to another way.

Types of data conversion:

• Data structure conversion - rasterization and vectorization

• File format conversion

• Both types preserve coordinate data

Describe different methods of data conversion in GIS

• Rasterization - the conversion of point, lines and polygons into cell data

• Vectorization - the conversion of raster data to vector data

Understand the steps required to convert data from CAD to ArcGIS format

• Examine the CAD file and see entities (types of CAD entities), drawing structure (layers), and spatial domain (coordinates, projections, datums).

• Convert the CAD to feature data set.

• Associate the entity attribute information with the converted features for labeling and visualizing as well as for query and analysis.

Understand that CAD is rich in geometrics with high precision and accuracy as well as very organized and structured. Geometries can be converted and values in data structure can be obtained as feature attributes.

There is a geoprocessing tool called “CAD To Geodatabase” to implement the dataset of the CAD info. CAD properties are attributes

You can label all of the points and change the symbology to make any unwanted points invisible.

You can also label points with annotations.

Feature-to-polygon creates a feature class containing polygons formed by lines.

Suggest the value of converting automated digital data from one format to another

Describe different types of data products available

List different types of internet geospatial data services

• VGI - Volunteered Geographic Information: WikiMapia, OpenStreetMap, and even Twitter

• Some tools are FGDC listed tools and ArcGIS metadata editor which facilitate the creation, editing, and maintenance of metadata.

Suggest types of information that important outside of metadata

• Sampling methodologies, definition of variable terms, measurement system, taxonomic system, data model, collection rationale, policy constraints, anecdotes.

Identify some critical types of information as metadata

• Content, quality, condition, and other characteristics of data.

• Formal metadata includes content standards and is structured.

• Recording processing steps on theme. Document data collection methods (purposes, methods, units).

Differentiate geospatial metadata from data dictionaries

• Geospatial metadata includes catalog elements like title, abstract, and publication data; geographic elements like geographic extent and projection information; and database elements like attribute label definitions and attribute domain values.

• Data dictionaries are centralized repository of information about data such as meaning, relationships to other data, origin, usage, and format. Unlike metadata, it refers to collections of metadata for a whole data set instead of just one.

Describe metadata content and format standards

• Geospatial metadata has FGDC and ISO standards.