Database design and implementation CMPSCI 645. Lecture 14: Data Provenance

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1 Databas dsign and implmntation CMPSCI 645 Lctur 14: Data Provnanc 1

2 Provnanc provnanc, n. Th fact of coming from som particular sourc or quartr; origin, drivation [Oxford English Dictionary] } Data provnanc / linag } [BunmanKhannaTan01]: aims to xplain how a particular rsult was drivd. } Data-intnsiv scinc } Worry about provnanc 2

3 Motivation } Data intgration [WangMadnick90, LBrssanMadnick98] } Data Warhousing [CuiWidonWinr00] } Scintific Data Managmnt [BunmanKhannaTan01] } Dtrmins trust on rsults } Ensur rliability, quality of data } Rpatability/vrifiability } Avoid ffort duplication } Undrstanding transport of annotations 3

4 Exampl of data provnanc } A typical qustion: } For a givn databas qury Q, a databas D and a tupl t in th output of Q(D), which parts of D contribut to t? R Emp Dpt John D01 Susan D02 Anna D04 S Did D01 D02 D03 Mgr Mary Kn Ed Q = slct r.a, r.b, s.c from R r, S s whr r.b = s.b } Th qustion can b applid to attribut valus, tabls, tc. Q Emp Dpt Mgr John D01 Mary Susan D02 Kn 4

5 Timlin A Polygn Modl for Htrognous Databas Systms: Th Sourc Tagging Prspctiv. Y. R. Wang and S. E. Madnick. VLDB Supporting Fin-graind Data Linag in a Databas Visualization Environmnt. A. Woodruff and M. Stonbrakr. ICDE Tracing th Linag of Viw Data in a Warhousing Environmnt. Y. Cui, J. Widom and J. L. Winr. TODS Why and Whr: A Charactrization of Data Provnanc. P. Bunman, S. Khanna, Tan. ICDT On Propagation of Dltions and Annotations through Viws. P. Bunman, S. Khanna, Tan. PODS Containmnt of Rlational Quris with Annotation Propagation. Tan. DBPL

6 Timlin An Annotation Managmnt Systm for Rlational Databass. D. Bhagwat, L. Chiticariu, Tan, G. Vijayvargiya. VLDB 2004, VLDB Journal MONDRIAN: Annotating and Qurying Databass through Colors and Blocks. ICDE Provnanc in Curatd Databass. P. Bunman, A. Chapman and J. Chny. SIGMOD Annotation propagation rvisitd for ky prsrving viws. Gao Cong, Wnfi Fan, Floris Grts. CIKM ULDBs: Databass with Uncrtainty and Linag. O. Bnjlloun, A.D. Sarma, A. Y. Halvy, and J. Widom. VLDB Dbugging Schma Mappings with Routs. L. Chiticariu and Tan. VLDB On th Exprssivnss of Implicit Provnanc in Qury and Updat Languags. P. Bunman, J. Chny and S. Vansummrn. ICDT Intntional Associations Btwn Data and Mtadata. D. Srivastava and Y. Vlgrakis. SIGMOD Provnanc Smirings. T. J. Grn, G. Karvounarakis and V. Tannn. PODS Annotatd XML: Quris and Provnanc: J. N. Fostr, T. J. Grn, V. Tannn. PODS Containmnt of Conjunctiv Quris on Annotatd Rlations: T. J. Grn, ICDT

7 Two approachs } Eagr or annotation-basd } Changs th transformation from Q to Q to carry xtra information } Sourc data not ndd aftr transformation } Lazy or non-annotation basd } Q is unchangd } Good whn xtra storag is an issu } Rcomputation and accss to sourc rquird Annotation-basd Q Q Extra information 7

8 Typs of provnanc } Why } What DB tupls contribut to th prsnc of ach rsult tupl?! } How } By what procss is ach output tupl producd from th DB instanc?! } Whr } Whr (from what attribut of what tupl) dos ach output tupl valu com from?! 8

9 Why-provnanc xampl Agncis nam basd in phon t 1 : San Francisco t 2 : Santa Cruz ExtrnalTours nam dstination typ pric t 3 : San Francisco cabl car $50 t 4 : Santa Cruz bus $100 t 5 : Santa Cruz boat $250 t 6 : Montry boat $400 t 7 : Montry boat $200 t 8 : Carml train $90 Q: SELECT dstination, a.nam, a.phon a.phon FROM Agncis a, ExtrnalTours WHERE a.nam =.nam AND.typ= boat Rsult of Q 1 : nam phon

10 Linag } Linag for an output tupl t is a subst of th input tupls which ar rlvant to th output tupl Agncis nam basd in phon t 1 : San Francisco t 2 : Santa Cruz ExtrnalTours nam dstination typ pric t 3 : San Francisco cabl car $50 t 4 : Santa Cruz bus $100 t 5 : Santa Cruz boat $250 t 6 : Montry boat $400 t 7 : Montry boat $200 t 8 : Carml train $90 Q: SELECT dstination, DISTINCT a.nam, a.phon a.phon FROM Agncis a, ExtrnalTours WHERE a.nam =.nam AND.typ= boat Rsult of Q 1 : nam phon Linag: {t1, t5, t6} Problm: Not vry prcis..g. linag abov dos not spcify that t5 and t6 do not both nd to xist. 10

11 Why provnanc Agncis nam basd in phon t 1 : San Francisco t 2 : Santa Cruz ExtrnalTours nam dstination typ pric t 3 : San Francisco cabl car $50 t 4 : Santa Cruz bus $100 t 5 : Santa Cruz boat $250 t 6 : Montry boat $400 t 7 : Montry boat $200 t 8 : Carml train $90 Q: SELECT dstination, DISTINCT a.nam, a.phon a.phon FROM Agncis a, ExtrnalTours WHERE a.nam =.nam AND.typ= boat Witnss of t: Any subst of th databas sufficint to rconstruct tupl t in th qury rsult. Witnss basis: Lavs of th proof tr showing how rsult tupl t is gnratd Rsult of Q 1 : nam phon Linag: {t1, t5, t6} {t1, t5} {t1, t6} {t1, t2, t6, t8} {{t1, t5}, {t1, t6}} 11

12 Why: qury rwriting R Q(I),Q 0 (I) t1 t t2 t3 Q(x, y) : R(x, y) Q 0 (x, y) : R(x, y),r(x, z) Why(Q, I, t): {{t1}} Why(Q, I, t): {{t1}, {t1, t2}} Minimal witnss basis: Minimal witnsss in th witnss basis 12

13 Th viw dltion problm } D a databas instanc and V=Q(D) a viw dfind ovr D. } Find a st of tupls ΔD to rmov from D so that a spcific tupl t is rmovd from th viw } Minimiz th numbr of sid-ffcts in th viw } Viw sid-ffct problm Hard: quris with joins and projction or union PTIME: th rst } Minimiz th numbr of tupls dltd from D } Sourc sid-ffct problm Sam dichotomy [BunmanKhannaTan. PODS02] 13

14 How provnanc } Idntifis witnss tupls and th oprations prformd on thm to produc ach rsult tupl } Exprsss oprations using provnanc smirings } MERGE (+): union or projction } JOIN (): joins 14

15 Propagating annotations R A B C a b c p Join (on B) R S A B C D E a b c d p r S D B E d b r Th annotation p r mans joint us of th data annotatd by p and th data annotatd by r 15

16 Propagating annotations (2) R A B C a b c p Union R S A B C a b c p + r S A B C a b c r Th annotation p + r mans altrnativ us of th data annotatd by p and th data annotatd by r 16

17 Propagating Annotations (3) R A B C π AB R A B a b c 1 p Projct a b a b c 2 r p + r + s a b c 3 s + dnots altrnativ us of data 17

18 An xampl (SPJU) R A B C a b c d b f g p r s Q = σ C= π AC (π AB R π BC R π AC R π BC R) A C a a d d f c c (p p + p p) 0 p r 1 r p 0 (r r + r s + r r) 1 (s s + s r + s s) 1 For slction, multiply with annotation 0 and 1. 18

19 Exampl Agncis nam basd in phon t 1 : San Francisco t 2 : Santa Cruz ExtrnalTours nam dstination typ pric t 3 : San Francisco cabl car $50 t 4 : Santa Cruz bus $100 t 5 : Santa Cruz boat $250 t 6 : Montry boat $400 t 7 : Montry boat $200 t 8 : Carml train $90 Q: SELECT dstination, a.phon FROM Agncis a, (SELECT nam, basd in AS dstination FROM Agncis a UNION SELECT nam, dstination FROM ExtrnalTours) WHERE a.nam =.nam 19

20 Exampl Agncis nam basd in phon t 1 : San Francisco t 2 : Santa Cruz nam dstination ExtrnalTours nam dstination typ pric t 3 : San Francisco cabl car $50 t 4 : Santa Cruz bus $100 t 5 : Santa Cruz boat $250 t 6 : Montry boat $400 t 7 : Montry boat $200 t 8 : Carml train $90 Q: SELECT dstination, a.phon FROM Agncis a, (SELECT nam, basd in AS dstination FROM Agncis a UNION SELECT nam, dstination FROM ExtrnalTours) WHERE a.nam =.nam 20

21 Exampl Agncis nam basd in phon t 1 : San Francisco t 2 : Santa Cruz t 1 + t 3 t 4 + t 5 t 6 t 7 t 8 t 2 nam dstination San Francisco Santa Cruz Montry Montry Carml Santa Cruz Q: SELECT dstination, a.phon FROM Agncis a, (SELECT nam, basd in AS dstination FROM Agncis a UNION SELECT nam, dstination FROM ExtrnalTours) WHERE a.nam =.nam ExtrnalTours nam dstination typ pric t 3 : San Francisco cabl car $50 t 4 : Santa Cruz bus $100 t 5 : Santa Cruz boat $250 t 6 : Montry boat $400 t 7 : Montry boat $200 t 8 : Carml train $90 21

22 Exampl Agncis nam basd in phon t 1 : San Francisco t 2 : Santa Cruz t 1 + t 3 t 4 + t 5 t 6 t 7 t 8 t 2 nam dstination San Francisco Santa Cruz Montry Montry Carml Santa Cruz Q: SELECT dstination, a.phon FROM Agncis a, (SELECT nam, basd in AS dstination FROM Agncis a UNION SELECT nam, dstination FROM ExtrnalTours) WHERE a.nam =.nam ExtrnalTours nam dstination typ pric t 3 : San Francisco cabl car $50 t 4 : Santa Cruz bus $100 t 5 : Santa Cruz boat $250 t 6 : Montry boat $400 t 7 : Montry boat $200 t 8 : Carml train $90 22

23 Exampl Agncis nam basd in phon t 1 : San Francisco t 2 : Santa Cruz t 1 + t 3 t 4 + t 5 t 6 t 7 t 8 t 2 nam dstination San Francisco Santa Cruz Montry Montry Carml Santa Cruz Q: SELECT dstination, a.phon FROM Agncis a, (SELECT nam, basd in AS dstination FROM Agncis a UNION SELECT nam, dstination FROM ExtrnalTours) WHERE a.nam =.nam RESULT dstination phon 23

24 Exampl Agncis nam basd in phon t 1 : San Francisco t 2 : Santa Cruz t 1 + t 3 t 4 + t 5 t 6 t 7 t 8 t 2 nam dstination San Francisco Santa Cruz Montry Montry Carml Santa Cruz Q: SELECT dstination, a.phon FROM Agncis a, (SELECT nam, basd in AS dstination FROM Agncis a UNION SELECT nam, dstination FROM ExtrnalTours) WHERE a.nam =.nam RESULT dstination phon San Francisco

25 Exampl Agncis nam basd in phon t 1 : San Francisco t 2 : Santa Cruz t 1 + t 3 t 4 + t 5 t 6 t 7 t 8 t 2 nam dstination San Francisco Santa Cruz Montry Montry Carml Santa Cruz Q: SELECT dstination, a.phon FROM Agncis a, (SELECT nam, basd in AS dstination FROM Agncis a UNION SELECT nam, dstination FROM ExtrnalTours) WHERE a.nam =.nam RESULT dstination phon San Francisco t 1 (t 1 + t 3 ) 25

26 Exampl Agncis nam basd in phon t 1 : San Francisco t 2 : Santa Cruz t 1 + t 3 t 4 + t 5 t 6 t 7 t 8 t 2 nam dstination San Francisco Santa Cruz Montry Montry Carml Santa Cruz Q: SELECT dstination, a.phon FROM Agncis a, (SELECT nam, basd in AS dstination FROM Agncis a UNION SELECT nam, dstination FROM ExtrnalTours) WHERE a.nam =.nam RESULT dstination phon San Francisco t 1 (t 1 + t 3 ) Santa Cruz

27 Exampl Agncis nam basd in phon t 1 : San Francisco t 2 : Santa Cruz t 1 + t 3 t 4 + t 5 t 6 t 7 t 8 t 2 nam dstination San Francisco Santa Cruz Montry Montry Carml Santa Cruz Q: SELECT dstination, a.phon FROM Agncis a, (SELECT nam, basd in AS dstination FROM Agncis a UNION SELECT nam, dstination FROM ExtrnalTours) WHERE a.nam =.nam RESULT dstination phon San Francisco t 1 (t 1 + t 3 ) Santa Cruz t 1 (t 4 + t 5 ) 27

28 Exampl Agncis nam basd in phon t 1 : San Francisco t 2 : Santa Cruz t 1 + t 3 t 4 + t 5 t 6 t 7 t 8 t 2 nam dstination San Francisco Santa Cruz Montry Montry Carml Santa Cruz Q: SELECT dstination, a.phon FROM Agncis a, (SELECT nam, basd in AS dstination FROM Agncis a UNION SELECT nam, dstination FROM ExtrnalTours) WHERE a.nam =.nam RESULT dstination phon San Francisco t 1 (t 1 + t 3 ) Santa Cruz t 1 (t 4 + t 5 ) Montry t 1 t 6 Montry t 2 t 7 Carml t 2 t 8 Santa Cruz t

29 Back to xampl R A B C a b c d b f g p r s Q A C a c a d c (p p + p p) 0 p r 1 r p 0 d (r r + r s + r r) 1 f (s s + s r + s s) 1 32

30 Applying th laws: polynomials R A B C a b c p Q A C a pr d b r d 2r 2 + rs f g s f rs + 2s 2 Polynomials with cofficints in N and annotation tokns as indtrminats p, r, s captur a vry gnral form of provnanc 33

31 How to rad this provnanc R A B C a b c p Q A C a pr d b r d 2r 2 + rs f g s f rs + 2s 2 3 ways to driv (d ) 2 of th ways us only r, but thy us it twic th 3 rd uss r onc and s onc 34

32 Dltion Propagation R A B C a b c p Q A C a pr Q A C a 0 Q A C f 2s 2 d b r d 2r 2 + rs d 0 f g s f rs + 2s 2 f 2s 2 Dlt (d b ) from R St r to 0! 35

33 Som usful commutativ smirings (B,,, fals, tru) St Smantics (N, +,, 0, 1) Bag Smantics (P ( ),,,, ) Probabilistic vnts (A, min, max, 0,P) A = P<C<S<T<0 Accss Control Public Top Scrt 36

34 Provnanc hirarchy most informativ 2x 2 y + xy + 5y 2 + z N[X] x 2 y + xy + y 2 + z B[X] 3xy + 5y + z T rio(x) W hy(x) xy + y + z last informativ Lin(X) xyz P osbool(x) y + z 38

35 Exampl: distrust scors } Smiring: (R +, min, +,, 0) } Tokns: X={p,r,s} } Assignmnt function f : X! K f(p) =0,f(r) =1.5, f(s) = h(2r 2 + rs) =h(r r + r r + r s) = min(f(r)+f(r),f(r)+f(r),f(r)+f(s)) = min( , , )=

36 Exampl: accss control (A, min, max, 0,P) whr A = P<C<S<T<0 a c 2p 2 a b c d b f g p=p, r=s, s=t p r s q a d d f c pr pr 2r 2 +rs 2s 2 +rs a b c d b f g P S T q a a d d c c P S S S Evaluat with p=p, r=s, s=t using min for +, max for f T Usr with scrt claranc 40

37 Whr provnanc } Idntifis witnss clls } Important for annotations SELECT * FROM R WHERE A <> 5 UNION SELECT A, 7 AS B FROM R WHERE A= 5 UPDATE R SET B=7 WHERE A=5 R A B ? A B

38 Color algbra [Grts, Kmntsitsidis, Milano 06] A B P[Q] A B Q = SELECT * FROM R WHERE A <> 5 UNION SELECT A, 7 AS B FROM R WHERE A= 5 42

39 Color algbra A B P[Q] A B Q = UPDATE R SET B=7 WHERE A=5 43

40 Whr provnanc and smirings R u A x B y C 1 a 1 b 1 c 1 p S v B 1 C 1 b z c 1 m π AC (π AB R (π BC R S)) A 1 C 1 a 1 c 1 u 2 p 2 xy 2 + uvpmxyz 1 is a nutral annotation, usd whn w don t bothr to track data 44

41 Diffrnt annotations à Diffrnt tupls R A B C a b c d b z f g w p r s π C σ C= π AC (π AB R π BC R) C z w pr+r 2 s 2 45

42 Wrap up: issus and dirctions } Archiving } Comprssion } Gnralizations } Program Slicing [Chny07] } Ngativ Provnanc } Why Not? [SIGMOD09], Artmis [PVLDB09] } Causality 46

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