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1 Facets and structured research data in the Digital Humanities John Bradley and Michele Pasin

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1 1 Facets and structured research data in the Digital Humanities John Bradley and Michele Pasin Annual Bliss Classification Association Lecture 19 April 2013

2 2 Facetted modelling in the dynamic world of structured humanities scholarship John Bradley Annual Bliss Classification Association Lecture 19 April 2013

3 Bpi1700: (British Printed Images before 1700) CVMA: (Corpus Vitrearum Medii AeviMedieval stained glass) PBE: Prosopography of the Byzantine Empire (published on CD) PBW: Prosopography of the Byzantine World PASE: (Prosopography of Anglo-saxon England) CCEd: Clergy of the Church of England: EMLoT: Early Modern London Theatres: DIAMM: Digital Image Archive of Medieval Music: OCVE: Online Chopin Variorum Edition: PoMS: Paradox of Medieval Scotland: Art of Making: Records of Early English Drama The Making of Charlemagnes Europe The Breaking of Britain Structured Data DDH projects 3

4 Text in, Text out Historical Research Source Secondry Source Source Primary Sources Article Book / Article the historical work as what it most manifestly is: a verbal structure in the form of a narrative prose discourse Hayden White (1973), quoted in Jörn Rüsen (1987). Historical Narration: Foundation, Types, Reason in History and Theory Vol 26 No 4 4

5 Historians and narrative text Multiplicity is inherent in the word-narratives used to communicate history. Words are complex forms of information; they have 'halos of meaning', making them wonderfully evocative but imprecise and slippery. [...] Historians embrace this range of meanings. We prefer the medium of words and narratives because it permits us to represent the past as multidimensional, complex, and nonlinear, even though structurally our prose and our logic are sequential. David J. Bodenhamer (2008), "History and GIS: Implications for the Discipline", in Anne Kelly Knowles (ed.) (2008). Placing History: How Maps, Spatial Data, and the GIS Are Changing Historical Scholarship. Redlands, CA: ESRI Press. p

6 Structured Data: Appropriate to the Humanities? humanistic inquiry reveals itself as an activity fundamentally dependent upon the location of pattern. Of all the technologies in use among computing humanists, databases are perhaps the best suited to facilitating and exploiting [pattern]. To build a database one must be willing to move from the forest to the trees and back again; to use a database is to reap the benefits of the enhanced vision which the system affords. Stephen Ramsay (2004). Databases in A Companion to Digital Humanities. 6

7 Appropriate to the Humanities? the underlying ontology [that a database represents] has considerable intellectual value. A well-designed database that contains information about people, buildings, and events in New York City contains not static information, but an entire set of ontological relations capable of generating statements about a domain. A truly relational database, in other words, contains not merely "Central Park", "Frederick Law Olmstead", and "1857", but a far more suggestive string of logical relationships (e.g., "Frederick Law Olmstead submitted his design for Central Park in New York during 1857"). (from Steven Ramsay, Databases in A Companion to Digital Humanities) 7

8 Data, Structure, Interpretation "There can be no data without structure, and all structure is interface, whether we view it as a screen appearance or not. [...] Even more importantly, all interfacesvisible as well as invisibleare interpretational forms." (McGann, Jerome (2010). "Sustainability: The Elephant in the Room". In Online Humanities Scholarship: The Shape of Things to Come. Houston Texas: Rice University Press) 8

9 Three example projects BPI1700: British Printed Images before 1700 EMLoT: Early Modern London Theatres PASE: Prosopography of Anglo-Saxon England 9

10 This website, funded by the Arts and Humanities Research Council, makes available a database of thousands of prints and book illustrations from early modern Britain in fully-searchable form. (from bpi1700 webpage)database Online version gives free access to all these images bpi

11 Purpose behind bpi1700 Printed images are striking and revealing, potentially serving a wide range of illustrative and interpretative uses. They range from high art to crude satire, and significant conclusions can be drawn from their circulation and consumption about the culture of their period. Yet they are surprisingly little used by researchers, partly because they are currently difficult to access. This project seeks to rectify this by making a comprehensive collection of early modern British prints available online, and by promoting research on their relationship to their milieu. (proposal to the AHRC) 11

12 BPI1700 online 12

13 13

14 Bpi1700 DB structure overview Work State Impression Producer Producer Type Person Subject Technique 14 Evidenced by Has theseRole in production Created by Created using Represented in Appears in FRBR? Other data

15 The real DB structure Impression data: from Merlin and the V&A Bpi1700 added value: Works and subject index 15

16 Early Modern London Theatres Transmission and understanding: Most of what we know about the early London theatres, which developed before, during and shortly after the life of Shakespeare, has been passed down to us through a complex process of filtration. Documents written at the time have been selected, copied, adapted, and interpreted over subsequent centuries, and that process has shaped our understanding. In turn, what we do with this received information will determine how future generations view the early theatres. "EMLoT lets you see what direct use has been made, over the last four centuries, of pre-1642 documents related to professional performance in purpose-built theatres and other permanent structures in the London area. [...] It tells you who used them, and when, and where you can find evidence of that use. It also gives you some access to what was used, because it includes a brief account (or abstract) of the transcriptions contents, together with a reference to the location of the original document. (from the EMLoT website) 16

17 Elements of the EMLoT structure Event Type Event Venue Auspices DocumentRecord Troupe Privy Council Office of the Revels Court of Requests Lord Chamberlains Office [...] Admirals Men Queens Men Worchesters Men Kings Men Oxfords Boys [...] Globe Theatre Fortune Blackfriars Bel Savage Boars Heads [...] playhouse context court case playhouse business payment player context [...] Source Primary Source 2ndary Source Transcription 17

18 PBE: Prosopography of the Byzantine Empire (published on CD) PBW: Prosopography of the Byzantine World PASE: (Prosopography of Anglo-saxon England) CCEd: Clergy of the Church of England: Breaking of Britain PoMS: Paradox of Medieval Scotland: PoNE: People of Northern England Database The Making of Charlemagnes Europe Structured Prosopographical projects 18

19 A Source Assertion An assertion made by the project team that a source "S" at reference R" states something ("F") about a person or persons ("P") 19

20 Core structure for DDHs Prosopographical databases Person Assertion Authority Lists Assertion Type Source Location Possession 20 Instance of Typed by Connected to Appears in Connected to

21 PASEs real structure PersonAssertion (Factoid) Authority Lists Sources Factoid Types Possesion Place 21

22 Marriages in PASE 22

23 Facetted Thinking and structure Facetted Classification: An approach to organise a body of materials using facetted principles. Facetted Browsing: The exploiting of facets to facilitate the exploration of a body of materials. 23

24 Facetted Browsing Principles "Remember the purpose of the classification and the users. Who will use it? Why? Will they search it, browse it, or both? How well do they know the subject? Always remember it is meant for them to use. Denton 2003: How to make a Facet Classification and put it on the Web referencing Kwasnick, Barbara H The role of classification in knowledge representation and discovery. Library Trends 48 (1):

25 Faceted classification: advantages "Kwasnick (1999, 40-42) lists several things in favour of faceted classifications: they do not require complete knowledge of the entities or their relationships; they are hospitable (can accommodate new entities easily); they are flexible; they are expressive; they can be ad hoc and free-form; and they allow many different perspectives on and approaches to the things classified. Denton

26 Searching the Clergy of the Church of England database 26

27 WWW Facetted browsing principles 1. The user should not be able to form a query that is known to have no results. 2. Users must always know where they are in the classification 3. Users must always be able to refine their query or adjust their navigation to see what is nearby in the classification 4. The URL is the notation of the classification. Denton

28 Facetted Browsing in bpi1700 Facets Selected Works 28

29 Facets in PASE 29

30 Facets in Early Modern London Theatres (EMLoT) 30

31 Facets in Early Modern London Theatres (EMLoT) 31

32 Facets in Early Modern London Theatres (EMLoT) 32

33 Faceted classification: problems "She [Kwasnick 1999] lists three major problems: the difficulty of choosing the right facets; the lack of the ability to express the relationships between them; and the difficulty of visualizing it all. Denton

34 Metadata Definition: Metadata is sometimes defined literally as 'data about data,' but the term is normally understood to mean structured data about resources that can be used to help support a wide range of operations. (UKOLN (2001): Metadata in a nutshell (http://www.ukoln.ac.uk/metadata/publications/nutshell/)http://www.ukoln.ac.uk/metadata/publications/nutshell/ Metadata and Dublin Core Perhaps the most well-known metadata initiative is the Dublin Core. (UKOLN 2001) 34

35 DC: The fifteen elements From Weibel, Stuart (2007), Dublin Core Metadata Tutorial. OCLC Research

36 Resourcehasproperty DC:Creator DC:Title DC:Subject DC:Date... X implied subject implied verb one of 15 properties property value (an appropriate literal) [optional qualifier] qualifiers (adjectives) DC (Metadata) base syntax From Weibel, Stuart (2007), Dublin Core Metadata Tutorial. OCLC Research 36

37 ResourcehasDate" " Revised ISO8601 ResourcehasSubject"Languages -- Grammar" LCSH From Weibel, Stuart (2007), Dublin Core Metadata Tutorial. OCLC Research 37

38 38 DC.Subject: Dublin Core Meta Tags DC.Creator: Alan Kelsey DC.Format: text/html DC.Date: DC.Publisher: Alan Kelsey, Ltd. DC.Coverage: Hennepin Technical College DC.Rights: Copyright 2011,... DC.Language: EN

39 Metadata: a world view of structure Metadata: two kinds of data: Resource: The object being classified Metadata: The classification data Classification data could be used as facets Does this rather flat model suit our purposes? 39 ResourcesMetadata

40 BLISS: BC2 standard facets thing/entity kind part property material process operation patient product by-product agent space time 40 "These fundamental thirteen categories have been found to be sufficient for the analysis of vocabulary in almost all areas on knowledge. It is however quite likely that other general categories exist; it is certainly the case that there are some domain specific categories, such as those of form and genre in the field of literature" (pp 79-80). Vanda Broughton (2001): Faceted classification as a basis for knowledge organization in a digital environment; the Bliss Bibliographic Classification as a model for vocabulary management and the creation of multidimensional knowledge structures, New Review of Hypermedia and Multimedia, 7:1, BC2 makes an excellent starting point for thinking of how to make a faceted classification. Its facets can be renamed and adapted to suit your particular circumstances. (Denton 2008)

41 Modelling: elements of the EMLoT structure Event Type Event Venue Auspices DocumentRecord Troupe Privy Council Office of the Revels Court of Requests Lord Chamberlains Office [...] Admirals Men Queens Men Worchesters Men Kings Men Oxfords Boys [...] Globe Theatre Fortune Blackfriars Bel Savage Boars Heads [...] playhouse context court case playhouse business payment player context [...] Source Primary Source 2ndary Source Transcription 41

42 Modelling "In terms of humanities computing, modelling is an iterative process of constructing and developing something like a computational 'knowledge representation' as this is defined in computer science. In fact we might say that a model is a manipulable knowledge representation. Willard McCarty Humanities Computing: Essential Problems, Experimental Practice in Literary and Linguistic Computing Vol 17 No 1. pp

43 Analytical Modelling: the utility of failure "the digital model illumines analytically by isolating what would not compute. In other words, the failures of analytic modelling are where its success is to be found. Willard McCarty (2008). Whats going on? in Literary and Linguistic Computing, Vol 23 No 3. p

44 Structure as a scholarly outcome, and its public presentation The tension between that and the need for a public face to the project. Classification: user focus: focus on universal structure Modelling Scholarly structure: scholar focus: focus on individual scholarly exploration and assertion 44

45 Where are the facets in a DB structure? 45

46 Spiteri 1998: CRG Principles: Fundamental Categories g) Fundamental Categories: "there exist no categories that are fundamental to all subjects, and... categories should be derived based upon the nature of the subject being classified" (pp 18-19) Spiteri, Louise. (1998). A Simplified Model for Facet Analysis. Now online at _facet_analysis.php 46

47 Spiteri 1998: CRG Principles: Relevance b) Relevance: "when choosing facets by which to divide entities, it is important to make sure that the facets reflect the purpose, subject, and scope of the classification system" (1998, 6). 47

48 Spiteri 1998: CRG (Classification Research Group) Principles: Differentiation a) Differentiation: "when dividing an entity into its component parts, it is important to use characteristics of division (i.e., facets) that will distinguish clearly among these component parts" (Spiteri 1998, 5). For example, dividing humans by sex. 48

49 Structured data requires clear categories: authority lists Authority lists provide a classification mechanism alGenderKeyalGenderalGenderAbrv 1 2(Other) 3MaleM 4FemaleF 5Institutio n Inst 6M/F 7Undefine d (Undefined) alOfficeTermKeyalOfficeTerm 1 2(Other) 3King 4Secundarius 5Judge 6Pincerna 7Comes 8Pope 9Queen 10Bishop 11Counsellor 12Abbess 13Archbishop 14Dux 15Priest 16Minister 17Fasellus 18Princeps 19Cleric 49 CaseType (PoNE) idtype 29agreement 64appeal of breach of peace 63appeal of homicide 28assize of last presentation (darrein presentm 1assize of mort d'ancestor 45assize of novel disseisin 14deforcement 52grand assize 37last presentation (darrein presentment) 38mort d'ancestor 2novel disseisin 59plea de namio vetito 47plea in ecclesiastical court 25plea of acquittal 7plea of advowson 18plea of agreement 27plea of an extent 42plea of appeal 62plea of breach of peace 8plea of charter-warrant 56plea of death 5plea of debt 21plea of detention 23plea of disseisin 10plea of dower 22plea of ejection 31plea of false judgment 58plea of false testimony [...]

50 Spiteri 1998: CRG Principles: Ascertainability c) Ascertainability: "it is important to choose facets that are definite and can be ascertained" (1998, 6). 50

51 Location Data in CCE: kinds of locations 51

52 Spiteri 1998: CRG Principles: Homogeneity & Mutual Exclusivity e) Homogeneity: "facets must be homogeneous" (1998, 18). f) Mutual Exclusivity: facets must be "mutually exclusive," "each facet must represent only one characteristic of division" (1998, 18). i.e., that the contents any two facets cannot overlap, and that each facet must represent only one characteristic of division. 52

53 53 PASE: Office/Status/Occupation

54 Spiteri 1998: CRG Principles: Permanence d) Permanence: facets should "represent permanent qualities of the item being divided" (1998, 18). 54

55 55 PASEs event types: an evolving understanding

56 Revised event types (PASE II) Acts of crime, law-breaking/violence Hostility, Burh-abandonment, Lust, Disobedience, Burning, Insulting... Legal/governmental/administrative acts and legitimate use of violence Legal/governmental/administrative acts Challenge, Archiepiscopal see: restoration, Property-given/selling... Legitimate use of violence Imprisonment, Execution, Campaigning, War, Outlawing... Life-events/social and economic acts and relations Life Events Retirement, Journey, Naming, Betrothal, Marriage, Birth... Social/economic acts and relations Visit, Promise, Begging, Ship-buiding, Slave-selling, Godparenting... Power-taking and power-leaving Political Acts Conquest, Agreement, Throne-sitting, Message-sending... Taking/leaving power Appointment of abbot, royal insignia-entrusting, Coronation, Deposition of bishop,... Religious/ecclesiastical acts Acts of Christian piety Commemoration of the dead, Martyrdom, Church going, Easter-observance, Confession... Acts of ecclesiastical authority Baptism, Confraternity, Tonsuring, Liturgical celebration, Ecclesiastical reform, Mission sending... 56

57 Conclusions Facetted thinking in our structured projects arises out of an exploratory and somewhat dynamic modelling rather than classification activity. It provides a way for the public to have better access to a data structure that emerges from the project teams emerging and shifting understanding and interests in their data. It has to fit with a model of data that has a mix of different entity types and no specific entity centre. It has to fit with a model that is subject to change and evolution Although facetted representation of our models is not a perfect fit with their nature, it has allowed for a browsing view of the data that enables the public to engage much better with the complexities of these projects materials. 57

58 58

59 59 DC.Subject: Dublin Core Meta Tags DC.Creator: Alan Kelsey DC.Format: text/html DC.Date: DC.Publisher: Alan Kelsey, Ltd. DC.Coverage: Hennepin Technical College DC.Rights: Copyright 2011,... DC.Language: EN

60 Why facets here? Complex structure? Sparse data Public interface CCE query example 60


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