or by the portal user, to sort the merged result set. Federated search portals, either commercial or open access, generally search public access bibliographic databases, public access Web-based library catalogues (OPACs), Web-based search engines like Google and/or open-access, government-operated or corporate data collections. These individual information sources send back to the portal's interface a list of results from the search query. The user can review this hit list. Some portals will merely screen scrape the actual database results and not directly allow a user to enter the information source's application. More sophisticated ones will de-dupe the results list by merging and removing duplicates. There are additional features available in many portals, but the basic idea is the same: to improve the accuracy and relevance of individual searches as well as reduce the amount of time required to search for resources. This process allows federated search some key advantages when compared with existing crawler-based search engines. Federated search need not place any requirements or burdens on owners of the individual information sources, other than handling increased traffic. Federated searches are inherently as current as the individual information sources, as they are searched in real time. Implementation One application of federated searching is the metasearch engine. However, the metasearch approach does not overcome the shortcomings of the component search engines, such as incomplete indexes. Documents that are not indexed by search engines create what is known as the deep Web, or invisible Web. Google Scholar is one example of many projects trying to address this, by indexing electronic documents that search engines ignore. And the metasearch approach, like the underlying search engine technology, only works with information sources stored in electronic form. One of the main challenges of metasearch, is ensuring that the search query is compatible with the component search engines that are being federated and combined. When the search vocabulary or data model of the search system is different from the data model of one or more of the foreign target systems, the query must be translated into each of the foreign target systems. This can be done using simple data-element translation or may require semantic translation. For example, if one search engine allows for quoting of exact strings or n-grams and another does not, the query must be translated to be compatible with each search engine. To translate a quoted exact string query, it can be broken down into