curated databases
DESCRIPTION
Curated Databases. Peter Buneman School of Informatics University of Edinburgh. The Population of Corfu. *** The only site to give attribution : http://www.statistics.gr/portal/page/portal/ESYE. These are both curated databases. What is a curated database?. - PowerPoint PPT PresentationTRANSCRIPT
Curated Databases
Peter Buneman
School of InformaticsUniversity of Edinburgh
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The Population of Corfu113.479 (2001) http://www.corfunext.com/corfu_geography.htm
107,879 (as of 2001 ) http://en.wikipedia.org/wiki/Corfu ***
93,000 http://www.corfunet.com/corfu/
109,512 www.agni.gr/
110,000 www.corfuvisit.net
70,000 http://www.newadvent.org/cathen/04362a.htm
107,600 http://www.greek-hotels.com/
105,043 http://www.merriam-webster.com/dictionary/corfu
approximately 110,000 www.kassiopi.com/MenuContent.aspx?MenuId=6
approximately 120.000 http://www.gardeno-corfu.com/
115,200 (2003 est) http://encyclopedia.farlex.com/Corfu
around 110,000 http://www.sunshinetravel.gr/CORFUGUIDE/CORFU_TRAVEL_GUIDE 0-1.htm
110.000 http://www.dialashop.com/travel/corfu.html
about 110,00 http://www.argobenitses.gr/greece.php
97,102 in 1981 http://geography.howstuffworks.com/europe/corfu.htm
107,880 http://catalogue.horse21.net/greece+hotels/corfu+hotels/hotels5/luxury
109,512 http://www.corfu-property.gr/content/view/14/38/lang,en/
about 100,000 http://members.virtualtourist.com/m/6ce90/67541/
110,000 approximately http://www.corfu-island.org/features.htm
107,000 http://www.nytimes.com/2009/09/11/greathomesanddestinations/11iht-recorfu.html
*** The only site to give attribution: http://www.statistics.gr/portal/page/portal/ESYEECDL
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These are both curated databasesECDL
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What is a curated database?
• A curated database is one that is maintained with a lot of human effort
• Curare: Latin “to care for”• Prime concern is quality of dataECDL
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What is a database?(for the purposes of this talk)
• Any structured collection of data that is subject to change/revision – Ontologies– XML and other structured text files– Structured wikis – Standard relational and object-oriented databases
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Curated databases have interesting properties…
• A digital reference work. Traditional dictionaries, gazetteers, encyclopedia have been replaced by curated databases.
• Value lies in the organization and annotation of data• Commonly constructed by copying parts of other (curated) databases.• Rapidly increasing in scientific research. (> 1000 in molecular biology)• Constantly checked/verified. Data quality and timeliness are important.• Often group efforts. Produced by a dedicated organization or
collaboration.• Increasingly seen as “publications” by scientists. (You get kudos if
someone uses your database – like a citation.)
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... and they are very expensive
10-7Big physics (LHC) data
10-3[Movie] 10-1Book1“Production” code/Curated data10“Reliable” code / Curated data
In $/€/£ per byte
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A change for the better?
Storage:• Redundant• Persistent• Distributed• Readable by peopleClear standards for citationHistorical record (old data is useful)Well understood ownership/IP
Storage:• Single-source• Volatile• Centralised• Internal DBMS formatNo standards for citationNo historical recordMind-boggling legal issues
20th century libraries did some things better!
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Some computer science issues
• Archiving (CS usage)• Provenance• Annotation/citation• Data cleaning
All of these are intimately connected.
For example, if you cite some part of a curated database, the version you cited should be available (archiving)
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CIA World Factbook Uniprot
Some well-known curated databasesID 11SB_CUCMA STANDARD; PRT; 480 AA.AC P13744;DT 01-JAN-1990 (REL. 13, CREATED)DT 01-JAN-1990 (REL. 13, LAST SEQUENCE UPDATE)DT 01-NOV-1990 (REL. 16, LAST ANNOTATION UPDATE)DE 11S GLOBULIN BETA SUBUNIT PRECURSOR.OS CUCURBITA MAXIMA (PUMPKIN) (WINTER SQUASH).OC EUKARYOTA; PLANTA; EMBRYOPHYTA; ANGIOSPERMAE; DICOTYLEDONEAE;OC VIOLALES; CUCURBITACEAE.RN [1]RP SEQUENCE FROM N.A.RC STRAIN=CV. KUROKAWA AMAKURI NANKIN;RX MEDLINE; 88166744.RA HAYASHI M., MORI H., NISHIMURA M., AKAZAWA T., HARA-NISHIMURA I.;RL EUR. J. BIOCHEM. 172:627-632(1988).RN [2]RP SEQUENCE OF 22-30 ND 297-302.RA OHMIYA M., HARA I., MASTUBARA H.;RL PLANT CELL PHYSIOL. 21:157-167(1980).CC -!- FUNCTION: THIS IS A SEED STORAGE PROTEIN.CC -!- SUBUNIT: HEXAMER; EACH SUBUNIT IS COMPOSED OF AN ACIDIC AND ACC BASIC CHAIN DERIVED FROM A SINGLE PRECURSOR AND LINKED BY ACC DISULFIDE BOND.CC -!- SIMILARITY: TO OTHER 11S SEED STORAGE PROTEINS (GLOBULINS).DR EMBL; M36407; G167492; -.DR PIR; S00366; FWPU1B.DR PROSITE; PS00305; 11S_SEED_STORAGE; 1.KW SEED STORAGE PROTEIN; SIGNAL.FT SIGNAL 1 21FT CHAIN 22 480 11S GLOBULIN BETA SUBUNIT.FT CHAIN 22 296 GAMMA CHAIN (ACIDIC).FT CHAIN 297 480 DELTA CHAIN (BASIC).FT MOD_RES 22 22 PYRROLIDONE CARBOXYLIC ACID.FT DISULFID 124 303 INTERCHAIN (GAMMA-DELTA) (POTENTIAL).FT CONFLICT 27 27 S -> E (IN REF. 2).FT CONFLICT 30 30 E -> S (IN REF. 2).SQ SEQUENCE 480 AA; 54625 MW; D515DD6E CRC32; MARSSLFTFL CLAVFINGCL SQIEQQSPWE FQGSEVWQQH RYQSPRACRL ENLRAQDPVR RAEAEAIFTE VWDQDNDEFQ CAGVNMIRHT IRPKGLLLPG FSNAPKLIFV AQGFGIRGIA IPGCAETYQT DLRRSQSAGS AFKDQHQKIR PFREGDLLVV PAGVSHWMYN RGQSDLVLIV FADTRNVANQ IDPYLRKFYL AGRPEQVERG VEEWERSSRK GSSGEKSGNI FSGFADEFLE EAFQIDGGLV RKLKGEDDER DRIVQVDEDF EVLLPEKDEE ERSRGRYIES ESESENGLEE TICTLRLKQN IGRSVRADVF NPRGGRISTA NYHTLPILRQ VRLSAERGVL YSNAMVAPHY TVNSHSVMYA TRGNARVQVV DNFGQSVFDG EVREGQVLMI PQNFVVIKRA SDRGFEWIAF KTNDNAITNL LAGRVSQMRM LPLGVLSNMY RISREEAQRL KYGQQEMRVL SPGRSQGRRE//
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Archiving / Database Preservation
• How do we preserve something that evolves (both in content and structure)
• Keep snapshots?– frequent: space consuming– infrequent: lose “history”
Most curated databases have a hierarchical structure that we can exploit…
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A Sequence of Versions
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This relies on a deterministic / keyed model – there’s a unique path to every data item.
Pushing time down
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[B., Khanna, Tajima, Tan, TODS 27,2 (2004)]
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An initial experiment
• Grabbed the last 20 available versions of Swissprot• XML-ized all of them• Also recorded all OMIM versions for about 14 weeks
(100 of them)• Combined into archive XML format file by pushing
time down.
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100 days of OMIM
Size
(byt
es) x
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XMill(archive)
gzip(inc diff)
versionarchive, inc diff
Legend•archive•inc diff •version•compressed inc diff•compressed archive
Uncompressed• Archive size is
– 1.01 times diff repository size
– 1.04 times size of largest version
Compressed • archive size is between 0.94 and
1 times compressed diff repository size
• gzip - unix compression tool• XMill - XML compression tool
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~ 5 years of UniProt
Size
(byt
es) x
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arch
ive
XMill(archive)
versi
onin
c diff
gzip(inc diff)
Legend•archive•inc diff •version•compressed inc diff•compressed archive
Uncompressed• Archive size is
– 1.08 times diff repository size
– 1.92 times size of largest version
• Compressed • archive size is between 0.59 and
1 times compressed diff repository size
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Snapshots are immediate. Longitudinal/temporal queries are also easy
Factbook
Demography
AndorraLiechtenstein
China
Economy
Population
[1990-2006]
*
* * *
**
[1990] [1991] [2006]…
Plot, by year, the population of Liechtenstein since 1990
34,24728,292 28,476
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A Working System
• Implemented by Heiko Müller
• For scale, we require external sorting of large XML files
• Designed and implemented by Ioannis Koltsidas Heiko Müller and Stratis Viglas
• Has a simple temporal query language
• Experimented with recent (HTML) versions of CIA world factbook
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What the archive looks like<T t="2002-2007"> <FACTBOOK> <COUNTRY> <NAME>Afghanistan</NAME> <CATEGORY> <NAME>Communications</NAME> <PROPERTY> <NAME>Internet users</NAME> <TEXT> <T t="2004-2005">1,000 (2002)</T> <T t="2006-2007">30,000 (2005)</T> <T t="2002-2003">NA</T> </TEXT> </PROPERTY> <PROPERTY> <NAME>Radios</NAME> <TEXT>167,000 (1999)</TEXT> </PROPERTY> <PROPERTY> <NAME>Telephones - main lines in use</NAME> <TEXT> <T t="2006">100,000 (2005)</T> <T t="2007">280,000 (2005)</T> <T t="2002-2003">29,000 (1998)</T> <T t="2004-2005">33,100 (2002)</T>…
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How did the population of Chinachange from 2002-2007?
<T t="2002-2007"> <FACTBOOK> <COUNTRY> <CATEGORY> <PROPERTY> <NAME>Population</NAME> <TEXT> <T t="2002">1,284,303,705 (July 2002 est.)</T> <T t="2003">1,286,975,468 (July 2003 est.)</T> <T t="2004">1,298,847,624 (July 2004 est.)</T> <T t="2005">1,306,313,812 (July 2005 est.)</T> <T t="2006">1,313,973,713 (July 2006 est.)</T> <T t="2007">1,321,851,888 (July 2007 est.)</T> </TEXT> </PROPERTY> </CATEGORY> </COUNTRY> </FACTBOOK></T>
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How did land area of countries change in 2002-2007?<T t="2002-2007"> <FACTBOOK KEY=""> … <COUNTRY KEY="NAME Austria"> <CATEGORY KEY="NAME Geography"> <PROPERTY KEY="NAME Area"> <SUBPROP> <NAME>land</NAME> <TEXT> <T t="2004-2007">82,444 sq km</T> <T t="2002-2003">82,738 sq km</T> </TEXT> </SUBPROP> </PROPERTY> </CATEGORY> </COUNTRY> … <COUNTRY KEY="NAME France"> <CATEGORY KEY="NAME Geography"> <PROPERTY KEY="NAME Area"> <SUBPROP> <NAME>land</NAME> <TEXT> <T t="2002-2006">545,630 sq km</T> <T t="2007">640,053 sq km; 545,630 sq km (metropolitan France)</T> </TEXT>… ECDL
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What are the differences between the factbookson 21/08/2007 and 10/09/2007?
<T t="21/08/2007-10/09/2007"> <CIAWFB KEY=""> <COUNTRY KEY="NAME Afghanistan"> <CATEGORY KEY="NAME Communications"> <PROPERTY KEY="NAME Internet users"> <T t="21/08/2007"> <TEXT>30,000 (2005)</TEXT> </T> <T t="10/09/2007"> <TEXT>535,000 (2006)</TEXT> </T> </PROPERTY> <PROPERTY KEY="NAME Telephones - mobile cellular"> <T t="21/08/2007"> <TEXT>1.4 million (2005)</TEXT> </T> <T t="10/09/2007"> <TEXT>2.52 million (2006)</TEXT> </T> …
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http://homepages.inf.ed.ac.uk/hmueller/xarch/download.html
Heiko Müller’s Xarch• Examples of use with
⁻ Ontologies⁻ XML files⁻ Relational databases
• Automatically converts RDBs into XML
• Efficiently extracts snapshots
• Simple temporal query language
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Provenance – a huge issue
• Where did this data come from?• How did it get here?• How was it constructed?• . . .
Two schools of research:• Workflow (coarse-grain) provenance – a complete
record of how some large scientific analysis/simulation was performed.
• Data (fine-grain) a record of how some small piece of data (in a larger databases) was produced
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Copy-paste, or<cntrl>C <cntrl>V
113.479 (2001) http://www.corfunext.com/corfu_geography.htm
107,879 (as of 2001 ) http://en.wikipedia.org/wiki/Corfu ***
109,512 www.agni.gr/
105,043 http://www.merriam-webster.com/dictionary/corfu
115,200 (2003 est) http://encyclopedia.farlex.com/Corfu
97,102 in 1981 http://geography.howstuffworks.com/europe/corfu.htm
107,880 http://catalogue.horse21.net/greece+hotels/corfu+hotels/hotels5/luxury
Data provenance: an example
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“Where provenance”
Possible explanations of how something was copied:
This data item was extracted from location L1 in document D1 and placed in location L2 in document D2
or
This data item was extracted from database D1 by query Q1 and placed in database D2 by update U2
(or some combination of the two)
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ID 11SB_CUCMA STANDARD; PRT; 480 AA.AC P13744;DT 01-JAN-1990 (REL. 13, CREATED)DT 01-JAN-1990 (REL. 13, LAST SEQUENCE UPDATE)DT 01-NOV-1990 (REL. 16, LAST ANNOTATION UPDATE)DE 11S GLOBULIN BETA SUBUNIT PRECURSOR.OS CUCURBITA MAXIMA (PUMPKIN) (WINTER SQUASH).OC EUKARYOTA; PLANTA; EMBRYOPHYTA; ANGIOSPERMAE; DICOTYLEDONEAE;OC VIOLALES; CUCURBITACEAE.RN [1]RP SEQUENCE FROM N.A.RC STRAIN=CV. KUROKAWA AMAKURI NANKIN;RX MEDLINE; 88166744.RA HAYASHI M., MORI H., NISHIMURA M., AKAZAWA T., HARA-NISHIMURA I.;RL EUR. J. BIOCHEM. 172:627-632(1988).RN [2]RP SEQUENCE OF 22-30 AND 297-302.RA OHMIYA M., HARA I., MASTUBARA H.;RL PLANT CELL PHYSIOL. 21:157-167(1980).CC -!- FUNCTION: THIS IS A SEED STORAGE PROTEIN.CC -!- SUBUNIT: HEXAMER; EACH SUBUNIT IS COMPOSED OF AN ACIDIC AND ACC BASIC CHAIN DERIVED FROM A SINGLE PRECURSOR AND LINKED BY ACC DISULFIDE BOND.CC -!- SIMILARITY: TO OTHER 11S SEED STORAGE PROTEINS (GLOBULINS).DR EMBL; M36407; G167492; -.DR PIR; S00366; FWPU1B.DR PROSITE; PS00305; 11S_SEED_STORAGE; 1.KW SEED STORAGE PROTEIN; SIGNAL.FT SIGNAL 1 21FT CHAIN 22 480 11S GLOBULIN BETA SUBUNIT.FT CHAIN 22 296 GAMMA CHAIN (ACIDIC).FT CHAIN 297 480 DELTA CHAIN (BASIC).FT MOD_RES 22 22 PYRROLIDONE CARBOXYLIC ACID.FT DISULFID 124 303 INTERCHAIN (GAMMA-DELTA) (POTENTIAL).FT CONFLICT 27 27 S -> E (IN REF. 2).FT CONFLICT 30 30 E -> S (IN REF. 2).SQ SEQUENCE 480 AA; 54625 MW; D515DD6E CRC32; MARSSLFTFL CLAVFINGCL SQIEQQSPWE FQGSEVWQQH RYQSPRACRL ENLRAQDPVR RAEAEAIFTE VWDQDNDEFQ CAGVNMIRHT IRPKGLLLPG FSNAPKLIFV AQGFGIRGIA IPGCAETYQT DLRRSQSAGS AFKDQHQKIR PFREGDLLVV PAGVSHWMYN RGQSDLVLIV FADTRNVANQ IDPYLRKFYL AGRPEQVERG VEEWERSSRK GSSGEKSGNI FSGFADEFLE EAFQIDGGLV RKLKGEDDER DRIVQVDEDF EVLLPEKDEE ERSRGRYIES ESESENGLEE TICTLRLKQN IGRSVRADVF NPRGGRISTA NYHTLPILRQ VRLSAERGVL YSNAMVAPHY TVNSHSVMYA TRGNARVQVV DNFGQSVFDG EVREGQVLMI PQNFVVIKRA SDRGFEWIAF KTNDNAITNL LAGRVSQMRM LPLGVLSNMY RISREEAQRL KYGQQEMRVL SPGRSQGRRE//
DE 11S GLOBULIN BETA SUBUNIT PRECURSOR.OS CUCURBITA MAXIMA (PUMPKIN) (WINTER SQUASH).OC EUKARYOTA; PLANTA; EMBRYOPHYTA; ANGIOSPERMAE; DICOTYLEDONEAE;OC VIOLALES; CUCURBITACEAE.
CC -!- FUNCTION: THIS IS A SEED STORAGE PROTEIN.CC -!- SUBUNIT: HEXAMER; EACH SUBUNIT IS COMPOSED OF AN ACIDIC AND ACC BASIC CHAIN DERIVED FROM A SINGLE PRECURSOR AND LINKED BY ACC DISULFIDE BOND.CC -!- SIMILARITY: TO OTHER 11S SEED STORAGE PROTEINS (GLOBULINS).
FT CHAIN 22 480 11S GLOBULIN BETA SUBUNIT.FT CHAIN 22 296 GAMMA CHAIN (ACIDIC).FT CHAIN 297 480 DELTA CHAIN (BASIC).FT MOD_RES 22 22 PYRROLIDONE CARBOXYLIC ACID.FT DISULFID 124 303 INTERCHAIN (GAMMA-DELTA) (POTENTIAL).
Where does this information come from? Which curator? Or was it the cited papers?Was it copied from some other DB?
Where Provenance
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Copy-paste model of curated DBs
(a) A biologist copies some UniProt records into her DB.(b) She fixes entries so that UniProt PTMs are not confused with hers.(c) She copies in some publication details from OMIM(d) She corrects a mistake in a PubMed publication number.[B. Chapman, Cheney, Sigmod ’06]
Curated databases are not views!!
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A very simple copy-paste language(uses a “deterministic” tree model)
How costly is it to record all this?
(1) delete c5 from T;(2) copy S1/a1/y into T/c1/y;(3) insert {c2 : {}} into T;(4) copy S1/a2 into T/c2;(5) insert {y : {}} into T/c2;(6) copy S2/b3/y into T/c2/y;(7) copy S1/a3 into T/c3;(8) insert {c4 : {}} into T;(9) copy S2/b2 into T/c4;(10) insert {y : 12} into T/c4;
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How to reduce space
• Complete provenance: Record every update.• Transactional provenance: Record the links at the end of some
user-defined transaction (sequence of updates)• Hierarchical (inferred) provenance. Only record a link if it
cannot be inferred from the provenance of a higher node
Taken together these provide a substantial saving on storage. Overhead comparable with the size of the DB in some realistic simulations
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(select A, 5 as B from R where A = 1)union (select * from R where A <> 1)
delete from R where A = 1; insert into R values (1,5)
update R set B = 5 where A = 1
1 3
6 7
1 5
6 7
1 3
6 7
1 5
6 7
1 3
6 7
1 5
6 7
Query languages and where provenanceA B A B
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Other forms of provenance in query languages
• Why-provenance: why is a tuple in the output, or what parts of the input “contributed to” the tuple? [Widom et al]
• How-provenance: how (by what process) was this tuple constructed. [Tannen et al]
DatabaseLarge, heterogeneoussource
Small part ofsource
Complex program or process
Simpler program/process
Taken together, these are the “explanation”.
“Piece” of data: data value, tuple.etc
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Workflow provenance
Taken from [Cohen, et al DILS 2006]• Each step S1. . . S4 is itself a workflow.• How does one record an “enactment” of the workflow?• How much “context” does one record?
– from people– from databases that change
• Recent attempts to produce a general model– Open Provenance Model [Moreau et al. 2007]– Petri Net + Complex Object [Hidders et al.Inf Syst 2008]
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Provenance is very general issue
• Intrinsic to data quality.• It is starting to be used in several areas of CS:
– Semantics of update languages.– Probabilistic databases– Data integration– Debugging schema transformations– File/data synchronization– Program debugging (program slicing)– Security
• The fundamental problem is finding the right model/models – can we combine data and workflow models?
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Annotation – closely related to provenance
• Much of the activity of curators is the annotation of existing data.
• When we copy that data, we should also copy its annotations
• The propagation of annotation follows (where-) provenance
• But the story is more complicated because we often annotate views
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The Distributed Annotation Server (DAS)
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Annotating Databases
Guinness Stout 5.0 Eire
Heineken Pilsner 5.0 Netherlands
Old Jock Ale 6.7 Scotland
Guinness Stout 7.5 Nigeria
Fischer Blonde 6.0 France
Guinness Stout
Heineken Pilsner
Old Jock Ale
Fischer Blonde
Guinness Stout 5.0 Eire
Heineken Pilsner 5.0 Netherlands
Fischer Blonde 6.0 France
Stijn says this is not a beer
Stijn says this is not a beer
Stijn says this is not a beer
π σ
Polygen [Wang & Madnick VLDB 1990], DBNotes [Bhagwat et al, VLDB 2004] Concern is propagation of annotations from views to source and back. Again, there is an interesting theory
Not strong
Not strong
Not strong
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How do you cite something in a database?
Many scientific databases ask you to cite them, but..• they don’t tell you how, or• they tell you to give the URL, or• they tell you to cite a paper about the database.
Nutrition Education for Diverse Audiences [Internet]. Urbana (IL): University of Illinois Cooperative Extension Service, Illinet Department; [updated 2000 Nov 28; cited 2001 Apr 25]. Diabetes mellitus lesson; [about 1 screen]. Available
from http://www.aces.uiuc.edu/~necd/inter2_search.cgi?ind=854148396NLM Recommended Formats for Bibliographic Citation.Internet Supplement. NLM Technical report Bethesda, MD 20894, July 2001.
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What is a citation?
Bard JB and Davies JA. Development, Databases and the Internet. Bioessays. 1995 Nov; 17(11):999-1001.[Location and descriptive information]
Ann. Phys., Lpz 18 639-641 Nature, 171,737-738(We often want more than location)
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Automatically generating citations
{ DB=IUPHAR, Version=$v, Family=$f Receptor=$r, Contributors=$a, Editor=$e, Date=$d, DOI=$i} ←
/Root[ ]/Version[Number=$’v, Editor=$?e, DOI=$.i, Date=$.d] /Data[ ] /Family[FamilyName=$’f] /Contributor-list/Contributor=$+a] /Receptor[ReceptorName=$’r]
{ DB=IUPHAR, Version=11, Family=Calcitonin, Receptor=CALCR, Contributors={Debbie Hay, David R. Poyner}, Editor=Tony Harmar, Date=Jan 2006, DOI=10.1234 }
A rule:
What gets generated (example):
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Other topics: Data quality and data cleaning
• Published data often looks clean but is intrinsically messy– “Dead” fields in the underlying data– Multiple syntactic conventions– Abuse of / confusion over formats & schema
• Human errors require human correction– Automate error detection rather than error correction
• Cleaning is an essential prerequisite in any integration or preservation task.
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Other topics: Evolution of Structure
• Curated DBs evolve from humble origins. Schemas are often wrong; they are– designed by people who don’t understand schemas– designed before the domain is fully understood
• Do ontologies help (you can build an ontology without worrying much about the schema) or do they defer the problem and make it worse?
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The larger (economic and social) issues
• Who will archive/curate curated databases?• Should they be open-access?
– who pays for their maintenance?• What are the legal/IP issues?
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A case study: IUPHAR database(curated by Tony Harmar and team)
• “Standard” curated database • Labour-intensive (hundreds of
contributors)
• Valuable (supported by drug companies)
• Simple, clean structure – as seen by users
50m
IUPHARDCC
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We wanted to use our archiver
• Our first task was to convert the database into a hierarchical structure (following the web presentation) so that we could archive it.
• We used the Prata XML (Fan et al) publishing software• This had some unexpected benefits…
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… <transduction>
<secondary>Y</secondary> <transcomments/> <transcites/> </transduction> </transductions> <ligandTypes> <ligandType> <typeName>Agonist</typeName> <ligandComment>empty</ligandComment> <ligands> <ligand> <radioactive>NO</radioactive> <endogenous>YES</endogenous> <alternative>NO</alternative> <ligandSpeices>Human</ligandSpeices> <ligandName>oxytocin</ligandName> <affinity>9.1-8.8</affinity> <ligandAction>Full Agonist</ligandAction> <ligandUnits>p<i>K</i><sub>d</sub></ligandUnits> <ligandCites>9</ligandCites> </ligand> <ligand> <radioactive>YES</radioactive> <endogenous>NO</endogenous> <alternative>NO</alternative> <ligandSpeices>Human</ligandSpeices> <ligandName>[<sup>3</sup>H]-oxytocin</ligandName> <affinity>9.1-8.8</affinity> <ligandAction>Full Agonist</ligandAction> <ligandUnits>p<i>K</i><sub>d</sub></ligandUnits> <ligandCites>9, 42</ligandCites> </ligand>…
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• We can preserve all versions of the data (as intended)• We can generate static web pages (less software, more
efficient)• We can make the database citable• Tony can trace the history of entries• Tony can generate an old-fashioned book (yes, he wants to do
this!)• We have a “community model” for data exchange• The data got cleaned up in the process• The representation information (required by archivists) is
greatly simplified
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Selected pages from the book – generated by a 100-line style sheet
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Our library will “host” the book, but not the database!
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Centralized vs. distributed publishing20th century libraries provided robust, distributed dissemination and preservation of reference material
Valuable information was lost in earlier “data centers” . Is this still happening?
Replication and distribution has always been the best guarantee of preservation. We should do the same for curated databases – a database LOCKSS ?
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Many of the issues are non “technical”
• A good economic model for sustainability– Open access works for journal papers– Can it work for curated DBs? They require long-term
support. And people who write reference manuals sometimes expect to make money out of them.
• Intellectual property in curated databases is a nightmare– legislation still largely based on the notion of copying.
• We can still help by providing good models of the processes in curating and publishing databases
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