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The EP-INV-Patstat db and preliminary results

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1 The EP-INV-Patstat db and preliminary results
Andrea Maurino DISCo - Dip. di Informatica, Sistematica e Comunicazione Università di Milano Bicocca viale Sarca 336/14, , Milano (Italy)

2 Index APE-INV project EP-INV-PatStat Feedback Web application
Preliminary results Ongoing works ••• ITIS Lab •••

3 A preliminary truth The world is dirty! and Real world data are dirty!
A mandatory and prelimnary task before to realize any analysis or statistic is Clean your data ••• ITIS Lab •••

4 Disambiguation of academic inventors: ESF-APE-INV
Project chair: Francesco Lissoni (uniBocconi) Technical Manager: Andrea Maurino (uniMiB) Project steps: Reclassification of all patents by inventor (INV) Matching between inventors and academic scientists (APE) Results expected: To produce a freely-available database of “Academic Patenting in Europe” ••• ITIS Lab •••


6 Which is the part of PatStat interested by disambiguation?
Users should not consider these tables, SUBSTITUTIVE TABLES with disambiguated inventors and inventors information are provided by APE-INV project Source: PatStat documentation

7 INVENTORS_INFO INVENTORS_INFO table CODINV2 NAME-SURNAME COUNTRY / GCOUNTRY STATE REGION / GREGION COUNTY / GCOUNTY CITY / GCITY STREET / GSTREET ZIP / GZIP LONGITUDE LATITUDE GACCURACY Fields preceded by letter G are the result of Google-based standardization algorithm, all the other fields are cleaned PatStat addresses (eg. CITY and GCITY) We report Google information only when GACCURACY is larger than or equal to 6 (i.e. Address is available at the level of Street).

In order to connect DISAMBIGUATION and INVENTORS_INFO tables with PatStat dataset we include in the repository other two tables: PATSTAT_PUBL_NR allows to link each inventor (as identified by the CODINV2 code in the APE-INV dataset) to her granted patents (PUBLN_NR). PATSTAT_APPL_ID Allows to identify the APPLN_ID corresponding to each PUBLN_NR (NB In the specific case of EP patents there is a one-to-one correspondence between APPLN_ID and PUBLN_NR). The table reports also the information of the PatStat edition the APPLN_ID refers to. PATSTAT_PUBL_NR CODINV2 PUBLN_NR 100 1 101 2 102 3 115 4 PATSTAT_APPL_ID PUBLN_NR APPLN_ID PEDITION 1 5 42011 2 6 3 7 4 8

CODINV2: is a stable key generated within the APE-INV project. It identifies uniquely any distinctive combination of inventor and address CODINV: is a code associated to each CODINV2 after applying the disambiguation procedure. If two or more distinct CODINV2s are found to be the same person, they are assigned the same CODINV CODINV CODINV2 1 100 101 2 102 3 115 Dite qui che in futuro speriamo di passare da CODINV e CODINV2 codes (che sono nostri idiosincratici) a PERSON_ID, se PatStat riuscirà a crearne uno stabile. Dite anche per i brevetti successivi al 2000 abbiamo comunque una tavola di conversione CODINV2-PERSON_ID scaricabile dal sito web, all'indirizzo:

10 Feedback web application
••• ITIS Lab •••

11 Why sharing data Instead of looking for one golden algorithm, APE-INV proposes data dissemination and users’ feedback recording 2 kinds of users: Take the data and run (dissemination only): they use the data in their studies a-critically. No benefit for the project, risky for them (data are disambiguated according to the state-of-the-art of dissemination techniques, but we can always do better..). Critical users (dissemination+feedback): they use the data, usually sub-samples of the whole dataset, and have the possibility to increase the data quality: Hand checked data and survey work on smaller samples Algorithms fitting better sub-sample specificities (es. Country, firm, technological field) Data sources external to PatStat helping the disambiguation effort ••• ITIS Lab •••

12 How does data dissemination work?
Access with id and password Choose the country(s) of inventors you need (eg. My research is on Italian inventors) Get the EP-INV dataset and the CONTROVERSY.txt Query results in txt format.

13 Some results ••• ITIS Lab •••

14 Number of academic patents, 1996-2006

15 Ownership distribution of academic patents lower bound estimates

16 Ownership distribution of academic patents, upper bound estimates

17 Ongoing works ••• ITIS Lab •••

18 Temporal Record linkage
“Panta rei” (Heraclitus) everything flows, everything is constantly changing. Database may keep trace of these never ending changes Examples People change names Xin Dong Xin Luna Dong People change works Havely moves from Univ. of Wa. to Google Nations change YUGOSLAVIA  Serbia-Montenegro Serbia Kosovo Based on the paper P. Li, X.L.Dong, A.Maurino, D.Scrivistava, linking temporal data, VLDB 2011 ••• ITIS Lab •••

19 An example person_id person_name person_address appln_filing_date
110670 ABELE, MANLIO, G. 5 EAST 22ND STREET;NEW YORK, NY 10016 18/10/1990 06/04/1992 110671 5 EAST 22ND STREET, 205;NEW YORK, NY 10010 20/02/1991 110672 ABELE, Manlio, G. 5 East 22nd Street, 205,New York, NY 10010 110674 5 East 22nd Street,New York, NY 10016 12/04/1995 12/03/1996 110675 Abele, Manlio 250 East 54th St.,New York, NY 10022 19/03/2004

20 Experimental Evaluation
Effectiveness test: Data set: patent data, 1871 records, 359 entities, in Comparison: three existing algorithms, w./o. decayed similarity

21 Thanks! 疑问 ••• ITIS Lab •••

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