The 3 Characteristics of a Reliable Data Source

As a real estate appraiser, there are numerous data types and sources available that you could use to solve a specific appraisal problem. In order to reasonably believe that a source is reliable, it is recommended that you assess the dependability of a data source based on the following three characteristics, at a minimum.

1. Accuracy

Is the data source known to be typically correct, factual, consistent, and precise? Is the data required to be entered in a uniform format? In other words, a data source such as the MLS may require certain data points such as site size to be entered in a consistent and specific data format.


An assessor’s office has recently been found by a governmental oversight committee to have produced property records that are neither accurate nor uniform in an effort to lessen the tax burden on those well-connected to various local community leaders. This finding has been well-reported in the local market’s news sources. In this case, the assessor property records would be considered to be an unreliable source by an appraiser until the assessor’s office has remedied the discovered concerns about the property records.

On the other hand, an assessor’s office that is known to employ a state-of-the-art property data gathering system that is verified on a biannual schedule by an independent source and discloses all records such as sketches, property ratings, and calculations which allows the public to replicate the assessor’s work may be deemed as a reasonably reliable source by an appraiser.

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2. Trustworthiness

Is the data source considered to be objective, impartial, and credible?


Exaggerations pertaining to a specific outcome may compromise or alter the neutral perspectives of the data. For example, relying on property details as listed in a “For Sale by Owner” listing may be determined to be unreliable data as the author of the data (the homeowner/seller) may exaggerate positives of the property or under-report negative concerns of the property, all in an effort to sell the property quickly and at the highest price point possible.

3. Timeliness

Is the data from a time period suitable for the appraisal’s effective date? How often is the data updated? Data would be measured on timeliness if it is a dynamic record rather than a static record. For example, if an appraiser was confirming the year built of the subject dwelling and found that it was built in 1955, she could rely on this data even though its reporting date was 10 years ago, since the year built does not change over time. However, the appraiser would not want to rely on MLS data that is 10 years old for determining the property’s current condition, modernization, and quality for an appraisal with a current effective date. The subject home may have undergone remodeling or renovations over the past 10 years, or the subject dwelling may not have been maintained over the past 10 years, either of which could drastically impact the appraisal assignment results.


The accuracy of some data may decay over time. For example, data about the subject property’s condition, interior finishes, and modernization are just a few items that may significantly alter over time. Thus, as a precautionary measure to limit liability to the appraiser and in an effort to adequately inform the client, the appraiser should disclose the effective date of sources of data—especially data points that are impacted by the passage of time.

As an illustration, perhaps an appraiser is relying on an aerial image of the subject property captured three years ago. The appraiser should indicate the effective date of the satellite image in the appraisal report, as the subject property may have been altered in the past three years in a way that negatively or positively impacts the subject’s marketability or value.