2. Metasearching: The Promise and Peril Roy Tennant

3. Outline Why Metasearching? –The Problem –The Promise –Principles Metasearching in Libraries Today Issues Present Challenges and Possible Futures

4. The Problem Most users do not care where the information they need comes from, or who provides it…nor should they have to But our systems presently require them to know: –How to select one or more databases –How to get to them –How to use the unique search options for each How can we create systems that minimize what the user needs to know to get what they want?

7. The Promise of Metasearching The “Holy Grail” of resource discovery: simple to use one-stop shopping The simplification of a formerly complex activity (put the complexity in the back end, not the front) Allows the user to focus on evaluating results, not figuring out where to search

8. Principles Only librarians like to search, everyone else likes to find All things being equal, one place to search is better than two or more “Good enough” is often just that The size of the result set isn’t as important as how the results are displayed (e.g., relevance)

9. Principles Our ability to create effective one-stop searching is dependent on our ability to appropriately target user needs Services should be placed as close to the user as possible

26. http://searchlight.cdlib.org/cgi-bin/searchlight Source: ARL Statistics

28. Lessons from SearchLight Metasearching is not for everyone or every purpose… …but metasearching is still worth doing (it serves particular needs and audiences) For a large research library, metasearching is best focused on particular needs (e.g., “a few good things”) or subject areas (e.g., Biology)

30. CDL Metasearch Infrastructure Project Web site

32. No.AuthorTitleYearSourceActions 1.Watson JD;Molecular structure of nucleic1953Nature [via ExpandedView full text Crick, FHacids. A structure for Academic ASAP] deoxyribose nucleic acid. [details] [basket] 2.Miller GAThe magical number seven plus 1956Psychol Rev [via ExpandedView full text or minus two: some limits on our Academic ASAP] capacity for processing information. [details] [basket] 3. Bush, VannevarAs we may think1945The Atlantic [via Google]View full text [details] [basket] | | | HomeLibrary InfoResearchServices Giant squid Search More search options | Search tips Best bets for finding articles related to giant squid * BIOSIS Previews * Expanded Academic ASAP * Lexis-Nexis Best bets for finding articles related to giant squid * BIOSIS Previews * Expanded Academic ASAP * Lexis-Nexis Ask a LibrarianAsk a Librarian for help with research or using FindIt. FindIt is a service of the UC Libraries, powered by the CDL.UC LibrariesCDL UCSC home FindIt Basic Search | Advanced Search Help Search less, find more... Current Search Results | Marked Items Sign In | Quit For background information about giant squid, try Encyclopaedia Britannica. For background information about giant squid, try Encyclopaedia Britannica. Sort results by: Relevance | Title | Source | Year Search for giant squid found 3,345,452 results. The system retrieved 60 results and is displaying 1-50. If you want to wait longer you may wish to try to get more results. To save time, search in only one place: Google1,234,132 Britannica Online1,203 Expanded Academic ASAP 345  Previous Search Results Next -->  PreviousNext -->

33. User Interface software Initiates search Sends search to Metasearch Software Sends search to Database Advisor Tool Performs search, identifies top 2-3 DBs, writes out file referenced by results page Launche s multiple searche s Receive s results Merges, dedupes results Builds display Sends merge ddispl ay to Database Advisor Service

34. Technical Underpinnings Structured query/response methods: –Z39.50 –SRU/SRW, the “next generation” (XML Web Services) version of Z39.50 –XML Gateways (proprietary XML APIs) Unstructured query/response: –URL packing and HTML screen scraping Record merging and de-duping Ranking (mostly a dream) OpenURL support (e.g., SFX)

35. Software Provider Issues Access management Search mapping Unreliability of targets Systems that don’t support an API (that must be screen-scraped) Inadequate result data for good: –Deduping –Ranking

36. Database Provider Issues Access control (robust authentication and authorization) Load Inappropriate searches (searching databases that don’t apply) Branding and “unfair” deduping

37. Library Issues Selecting the right system Cost (both upfront and ongoing) System design and implementation System maintenance –Ability to add new resources/targets –Ease of interface changes –Ease of upgrades

38. User Issues What must I go through before hitting the search button? How difficult is it to review results? Are results ranked by relevance? (that will be my assumption) Will I get buried? (too many sources, too many results?) Do I have methods to easily focus in on what I want? Once I find what I want, can I get to the full-text with a click? Can I copy a citation and put it in my paper?

39. Present Challenges & Possible Futures Software still needs improvement (duh) Some databases are still not searchable If you create a “family” of portals, how does one find the right portal to search? A meta- metasearch? We can learn from other systems (e.g., redlightgreen) Standards are on the way (e.g., NISO)