• Use automated name rooting (the process through which name equivalents are generated, such as “Bill” and “Will” for “William”);

• Use automated name ordering (the process through which permutations of possible name equivalents are generated, such as “Lucia Vega Garcia” being represented as “Lucia Vega,” “Lucia Garcia,” or “Lucia Vega-Garcia”);

• Provide wildcard matching capabilities (capabilities for performing searches on incompletely specified names); and

• Use blocking and string comparators (comparison techniques used to generate a score reflecting degree of similarity rather than a simple “match-or-nonmatch” result).

L-9: Use commonly used unique identifiers for voter identification when available and when necessary privacy safeguards are in place.

L-10: Establish standards or best practices for matching algorithms.

L-11: Use the Social Security Death Master File and STEVE² (when deployed) for list maintenance.

L-12: Use third-party data when available to resolve possible matches.

L-13: Develop procedures for handling potential disenfranchisement caused by mistaken removals from voter registration lists.

L-14: Implement basic practices for backing up important data.

L-15: Implement basic security measures.

L-16: Take measures to help ensure system accessibility during critical times.

L-17: Consider fair information practices as a point of departure for protecting privacy in voter registration databases.

L-18: Take steps to protect voter privacy when voter registration data are released on a large scale.

L-19: Review appropriate nonelection uses of voter registration data.

L-20: Encourage and if possible require state, local, and federal agencies to cooperate with election officials in providing data to support voter registration.

L-21: Use inexpensive data export functions to facilitate data exchange.

L-22: Develop national standards for data-exchange formats for voter registration databases.