Online Patent Databases: Search Tools and Strategies

1. Search Tools and Strategies David Barford Consultant Ulaanbaatar March 2015

2. Online Patent Databases - introduction • Intellectual Property Offices, Patent Offices and other authorities around the world have made internet-based patent databases available • This constitutes one of the world’s principal sources of detailed scientific and technical information • Millions of patent documents can now be searched free of charge

3. Online Patent Databases – examples • WIPO • https://patentscope.wipo.int/search/en/search.jsf • EPO • http://worldwide.espacenet.com/advancedSearch?locale=en_EP • USPTO • http://www.uspto.gov/patft/index.html • JPO • http://www.ipdl.inpit.go.jp/homepg_e.ipdl • Google • https://www.google.com/?tbm=pts&gws_rd=ssl

4. Online Patent Databases – a note of caution • PLEASE NOTE - • each database covers a different set of documents–though there is often overlap • some documents may be there in full, but others only in part eg the title and abstract • each database has a different set of rules as to how it can be searched

5. SEARCH TOOLS

6. So – is searching patent databases just like doing a search on google? • Well, you could search patent databases by just throwing in queries comprising various words and phrases, and hoping for the best • Or you could be much more precise, by structuring your search queries using search tools and operators

7. How? • For word searching, you can select: • how the words are combined • whether any words are to be excluded • whether the words have to be next to or near to one another, and how close they must be • and you can search using part words, phrases and brackets • Or you can search using classifications, numbers, dates or names • Or you can combine any or all of these

8. Fields • You can also decide which sections – or fields - of the database you wish to target with your search, eg • the full text • the front page • the title • the abstract • the patent or application numbers • the priority dates, application dates or publication dates • names of applicants and inventors • combinations of these

9. In short: • To structuresearch queries: • use operators (Boolean, Proximity, Wildcards and truncation) • usephrasing and nesting • To direct a search to selected areas of the database: • use field operators to specify which fieldsare to be searched • These are the topics we’ll be discussing in more detail

10. George Boole • Philosopher and mathematician, born in 1815 • Famous for having developed Boolean algebra, the basis of digital computer logic • Derived from this algebra are the most commonly used operators in online searching - Boolean operators

11. Boolean operators • The most important Boolean operators are: • AND • OR

12. Examples • So if we are searching for documents relating to electric cars, we can use the search query electric AND car •  only documents having both the words “electric” and “car” • But if we are looking for documents relating to cars or trucks, we will need to search for car OR truck •  any document having either the word “car” or “truck” or both of these words or all three of these words • If no operator is specified, many databases automatically assume that you mean AND, ie: • electric car  only documents having both the words “electric” and “car”

13. Boolean operators : AND electric car electricANDcar

14. Boolean operators : OR car OR truck

15. Proximity operators

16. Proximity operators If we are searching for electric cars, as in the previous example, we do not really want to pick up documents which simply contain, anywhere in the document, the word electric and the word car What we really want is to find documents which have the words electric and car in the same part of the document. So we can use proximity operators. For instance in Patentscope, we can use the operator NEAR

17. Proximity operators in Patentscope • electric NEAR car documents having both the words “electric ” and “car” within five words of each other • To select a different number of words n, use the command “~ n” • electric NEAR car ~ 10 documents having both the words “electric ” and “car” within ten words of each other

18. Phrasing

19. Phrasing in Patentscope • Searching words using the AND operator can give false drops eg one of the documents found when searching “bicycle AND stand” describes • an isocyanate compound .. bicycle (2.2.1) heptane … left to stand at room temperature • To avoid this, need to specify that bicycle and stand are near to each other, so could use the proximity operator NEAR as in the previous example • But really we only want bicycle and stand next to each other • So search the phrase“bicycle stand“ ie with the words of the phrase enclosed in quotation marks • Cautionary note phrases such as “electric car“ - will be searched as just that, so won‘t pick up the phrase “electric or hybrid car“. So here need to go back to proximity operators

20. Wildcard operators and truncation

21. Wildcard operators and truncation • If searching in the area of electrical technology, you might wish to include all the words electric, electrical, electricity, electronics, electrostatic etc • Could use the Boolean operator OR, ie search electric OR electrical OR electricity OR electronics OR electrostatic • Better to truncate - ie search “electr”, with a wildcard operator to look for all words beginning with electr . This is called right truncation • Different search systems use different symbols as wildcard operators – for instance* or ? or % or $

22. Wildcard operators and truncation in Patentscope • Patentscope uses *, so search term would be electr* • Patentscope uses ? for single character truncation • Can also use internal truncation in Patentscope, for instance: • elec*ty will find electricity • elec*al will find electrical, but also electoral!

23. Nesting

24. Nesting in Patentscope • Queries which mix different Boolean operators can be ambiguous. • For instance, car OR truck AND electric could mean: • car OR (truck AND electric), or alternatively • (car OR truck) AND electric – which is what we want • To avoid such ambiguities, organise search queries by putting in the parantheses (ie brackets) • so search for (car OR truck) AND electric • This is called nesting (or grouping)

25. Conclusion • When searching patent databases, it is essential • to think carefully about what exactly you want to search for • and to express it accurately and unambiguously • The computer will then do exactly as you ask it to; nothing more and nothing less

26. Fields

27. Fields • The content of a patent document can be broken down in different ways, eg: • The textual matter - title, abstract, description and claims– collectively the full text • The front page data – again this includes the title and abstract, but also includes details of dates, names, numbers and classifications (and excludes the description and claims) • The front page data is also called the bibliographic data

28. Example of bibliographic data • Latest bibliographic data on file with the International Bureau • Pub. No.:    WO/2011/020165    • International Application No.:    PCT/AU2010/001083 • Publication Date: 24.02.2011 International Filing Date: 23.08.2010 • IPC: A01G 17/14 (2006.01), E04H 17/06 (2006.01), E04H 17/10 (2006.01), E04H 17/20 (2006.01) • Applicants: ONESTEEL WIRE PTY LIMITED [AU/AU]; Level 40 259 George Street Sydney, New South Wales ... • Inventor: HOWLETT, Warren John............ • Agent: GRIFFITH HACK; Level 29 Northpoint 100 Miller Street North Sydney . • Priority Data: 2009903959   21.08.2009   AU 2009904631   24.09.2009   AU • Title (EN) POST MOUNTING SYSTEM AND DEVICE(FR) SYSTÈME ET DISPOSITIF DE MONTAGE DE MONTANT • Abstract: (EN) A post mounting system comprises a post and at least one device for mounting to the post. The post is ..................

29. Searching fields • These different parts of the document are called fields, and many of them can be searched individually, for instance, if I’m interested in ladders I can search: • The full texts for any mention of a ladder, or • The abstracts - which will only cover cases where the mention of a ladder is fairly significant • The titles - which will only cover cases where the mention of a ladder is much more significant • Example in Patentscope • ~ 20,000 hits for ladder{no field specified; default field is full text} • ~3,000 hits for AB:ladder{field operator AB limits search to abstracts} • ~ 2,000 hits for TI:ladder{field operator TI limits search to titles}

30. Searching patent document reference numbers and dates Application or filing number Publication number Priority number Application date or filing date Publication date Priority date

31. Searching applicants’ or inventors’ names • Search an applicant or inventor’s name: • Novartis, BMW, Sony, Mittal, etc. • Dyson, Smith, etc. • Careful since same applicant may use different versions of their name, e.g. International Business Machines Corporation, IBM, IBM Ltd., IBM GmbH, etc.

32. Searching by patent classification • Similarly you can search using patent classification: • IPC • ECLA • F/FI Terms • USPC • Others

33. Searching fields in Patentscope – Simple Search:no need for field operators

34. Searching fields in Patentscope – Advanced Search:need for field operators

35. Combining fields • Fields can be combined eg: IC:H01Q1/24 AND AB:protect • This will search documents classified in IPC:H01Q1/24 and having the word “protect” in the abstract • (H01Q1/24 deals with cell phone aerials)

36. Further information • Patentscope – SeeHelp, How to search, Query syntax, Fields definition • Other databases USPTO, Espacenet etc, will use similar approaches – but there will be differences which you will need to familiarise yourself with from the respective Help pages

37. Search tools - What we’ve discussed • Online searching of patent databases can be much more sophisticated and focussed than a simple internet search: • by structuring search queries, and • by directing search queries • Structure search queries: • by using operators – Boolean, proximity, wildcard and truncation • by using phrasing and nesting • Direct search queries to selected fields • to search for dates, names, numbers and classifications • to search for words in titles, abstracts, descriptions, claims or the full text

38. SEARCH STRATEGIES

39. The client – a professional working relationship (1) • Discuss client's objectives and requirements • Explain the different types of search • Explain strengths of searching patent databases– eg structured and flexible worldwide access to enormous volumes of detailed technical data across all technical fields • Explain potential shortcomings – no guarantee that every reference will be found; challenges in certain specialised fields

40. The client – a professional working relationship (2) • Discuss client's knowledge of prior art, names of competitors • Agree what you will search for • Explain that you will go back to client if necessary before search is complete – eg too many hits, too few hits, clarification required • Report: record subject matter searched for, where search made; list of patents found (citations), analysis of citations – relevance, content (page and line or column numbers, figure numbers), and, if relevant, information on publication date, legal status etc

41. Approach to searching – what to search for • Depends on type of search: • Validity • Patentability • Freedom to operate • State of the art • Depends on client’s views and knowledge • Depends on complexity of invention and technical field of invention

42. Approach to searching – how (1) • Can use a quick online review to • gain some familiarity with the technology • become aware of any specialised vocabulary • find synonyms, classifications etc • find out who is working in the field • If you are aware of who’s working in the field – inventors, or applicants - can start with a name search • If you are aware of an existing patent number, can start with a number search • Can look for suitable classifications eg in the International Patent Classification (IPC) http://www.wipo.int/classifications/ipc/en/index.html

43. Approach to searching – how (2) • Then carry out full search with words, classifications, names etc as appropriate • Use available search tools and fields (topic 7) • Boolean operators AND, OR, NOT and others • Fields of search – eg title, abstracts, full text • Try different strategies with a low number of words/classifications to explore the technology step by step • Prepare strategies offline and paste into command input window

44. Approach to searching – where • Where? • Online databases listed above • Local databases or registers... • Again may depend on type of search

45. Words or Classifications? • Factors influencing whether to search using words or classifications or both • dealt with in Theme 5 – after lunch

46. Carrying out the search

47. Carrying out the search • Select database, enter search terms – and go! • Unfamiliar with the technology or the database? • Do some quick experimental searching to get your eye in and gain a preliminary view

48. Don’t get bogged down! • Thousands of hits? - • Try limiting word searches to the abstracts or titles • Narrow down what you’re searching for eg limit the search to an example rather than a general principle • A quick and dirty search may strike lucky • But be cautious, you may need to go back and widen the scope of your search in the light of what you’ve found

49. An iterative process • Learn as the search proceeds • Adjust your search in the light what you find and what you learn • If necessary, go back to the client to seek clarification or explain where you’ve got to • This should be an iterative process

50. When to stop • Depends on type of search • Freedom to operate searches – need to be very thorough • State of the art searches – depends on the nature of the query and what you find. Hits can be analysed thoroughly (qualitative); or statistically (quantitative).