Data Acquisition Methods
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.
When preparing to acquire data, consult the Data Acquisition Considerations below. Once the data are collected and/or received from external sources, the data must be reviewed to assure that the data meet standards and can be certified as acceptable for their intended use by USGS. Read further for acquisition considerations for each Data Acquisition Method.
Common Data Acquisition Considerations
Business Needs: The first thing to always consider is the business need - why are these data required? What will be done with them?
Business 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.
Authoritative Data Source
An Authoritative Data Source (ADS) is a single officially designated source authorized to provide a type or many types of information that is trusted, timely, and secure on which lines of business rely. Information that is trusted means that the information provider exercises management responsibility for appropriate practices, procedures, and processes to produce information that is within acceptable thresholds for quality, integrity, and security. The intended outcome is to provide information that is visible, accessible, understandable, and credible to information consumers, which include DOI business users, DOI information exchange partners, and IT applications and services. The assessment and designation of Authoritative Data Sources are accomplished through analysis and recommendations that are documented in but not limited to Modernization Blueprint projects, business process reengineering projects, and E-Gov related projects.
If there is an ADS, does the information in it meet your business needs? Attribute values, domain ranges, spatial accuracy, etc.?
If the ADS meets your need then you should be using it; you are in fact required by OMB to be doing so. If it does not meet your needs, then documenting why it does not allows you to move forward to other acquisition options.
Newly Collected Data Considerations
Contractor/Volunteer vs. USGS: The decision of who will perform new data collection must be balanced between the following:
In the USGS, most data are collected by employees and/or their contractors. While USGS can obtain some data from outside sources, we recognize that the bulk of an employee's work is the creation and maintenance of data.
Because data collection is important to the Bureau, data collection is important to the data stewards [see Plan > Data Stewardship for more information]. Data collection is an area where cost savings mechanisms are needed. For instance, Global Positioning Systems and mobile units are now being used to take field data and enter them directly from the source. The problem remains that quality data be collected initially at the source (where data can be correlated directly with observation), where the strictest controls should be placed. Unfortunately, heretofore, strict control has not occurred at the source.
Therefore, before data are initially collected, strict controls must be in place. All of the analysis, definitions, and standards need to be in place prior to any field information collection. While this may seem obvious, it is not always practiced. Good planning will reduce this heavy budget item.
Data must be reviewed and updated on a regular schedule to maintain a high standard of quality. Metadata must also be updated at the same time. Managers need to be confident that they have the best possible data available when making decisions. Each time the data changes, the metadata must be updated as well.
Converted/Transformed Legacy Data Considerations
Legacy Quality: Is the data of sufficient quality to meet the science needs?
Technical Issues: Is the storage medium readable? Can the data be converted into a usable format? At what cost?
Shared/Exchanged Data Considerations
With Other Government Agencies: A Memorandum of Understanding (MOU), via the USGS Agreements Coordination Information System (ACIS), is required. Sample and existing MOUs are accessible via ACIS. Learn more about Memoranda of Understanding.
With Non-Government Agencies: Data Sharing Agreements need to include provisions concerning access and dissemination. It is not wise to enter into a data sharing agreement where privacy information may be disclosed since non-Federal organizations are not subject to the Privacy Act. Similarly, the non-Federal organization needs to be alerted that the Federal agencies may be compelled to release information under the FOIA. Learn more about Data Sharing Agreements.
Data Organization: Is the data organized in a usable form? Will it require conversion/transformation to make it usable? Who will perform this? At what cost?
Records Requirements: Data must have corresponding metadata and other pertinent documentation.
Completeness of Data: Is the dataset complete? If not, who will address the gaps in the data? At what cost?
Purchased Data Considerations
Data purchases require a Purchasing Agreement. By purchasing data, you are endorsing the data. Such data then becomes subject to the Information Quality Act, which covers all data, not just geospatial data.
Data Certification: Metadata are required for purchased data. The specifics of this requirement should be specified in the Purchasing Agreement.
Licensing Issues: What restrictions are placed upon the use of the data? Are there Privacy Act or FOIA considerations?