There are four methods of acquiring data: collecting new data; converting/transforming legacy data; sharing/exchanging data; and purchasing data. This includes automated collection (e.g., of sensor-derived data), the manual recording of empirical observations, and obtaining existing data from other sources.
There are a number of consideration when acquiring data . Once the data are collected or received, the data must be reviewed to assure that the data meet standards and can be certified as acceptable for their intended use by USGS.
- Project Needs: The first thing to always consider is the need – why are these data required? What will be done with them?
- Project Rules: A business rule identifies the constraints under which the business operates. For instance, where applicable, all geospatial data must have Federal Geographic Data Committee (FGDC) compliant metadata. These rules will affect your data acquisition decisions.
- Data Standards: Any Government, USGS, or industry standards that apply will need consideration.
- Accuracy Requirements: Among the most familiar accuracy requirements is the locational accuracy for spatial data; but there are other accuracy requirements that you may need to consider as well.
- Cost: Cost is always a consideration. Sometimes it’s cheaper to buy than to collect.
- Currency of Data: For many types of work, the data need to be fairly current. For others, data may need to cover a specified time period. For others, data need to be in a specific season. If you are trying to determine vegetation coverage, for example, you may want photographs from the summer, when vegetation is at the highest. If you are trying to look for land forms, you may want winter photos.
- Time Constraints: You should determine how soon you need the data.
- Format: Do you need the data as spatial data, photos, flat files, Excel files, XML files? This may not apply, but you need to determine that for each project.