IAML Annual Study Weekend 12 April 2010 musicSpace: Music and the Semantic Web

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Contents 1.Motivation 2.Solutions 3.Evaluation 4.The Future 3

1. Motivation (the problem we’re addressing) 4

5 Centuries of material...

6... is now increasingly digitised

Yet, with exceptions like Copac,... 7

... data is typically siloed. 8

Geographical dispersal has been replaced by a virtual dispersal on the web. Data is now segregated into a plethora of online resources by: – Media type (text, image, audio, video) – Date of creation/publication – Subject 9

... data is typically siloed. Geographical dispersal has been replaced by a virtual dispersal on the web. Data is now segregated into a plethora of online resources by: – Language – Copyright holder – Ad hoc/insecure nature of project funding 10

... data is typically siloed. Crucially:  Data sources are not usually interoperable.  Data and metadata from one source cannot be used (automatically) as the basis for a query of another source 11

12 The Google/textbox search paradigm is limiting.

13 You’d better know what you want!

14 What tickles your fancy?

So, interacting with current data resources present barriers at all stages of the research process: 15

16 Inchoate ideas  Hum… something on Monteverdi’s madrigals? Specific complex questions  Which scribes have created manuscripts of Monteverdi’s works, and which other composers’ works have they inscribed?  What recording of works by Cage exist, which performers have recorded a particular work by Cage, and what else have they recorded?

17 Which scribes have created manuscripts of Monteverdi’s works, and which other composers’ works have they inscribed? We’d use RISM for this question. 1.Execute a ‘People’ search for ‘Monteverdi’. 2.Manually filter out results returned where the composer’s name appears in reference to a role other than that of composer (although for Monteverdi this isn’t likely to take long). 3.Examine the remaining records to identify the scribe in each case.

18 Which scribes have created manuscripts of Monteverdi’s works, and which other composers’ works have they inscribed? 4.Execute a ‘People’ search for each scribe of interest. 5.Manually filter out records where the scribe is named in reference to role other than that of scribe (e.g. ‘former owner’, ‘composer’ etc.). 6.Collate a list of other composers whose works the scribes have inscribed.

19 What recording of works by Cage exist, which performers have recorded a particular work by Cage, and what else have they recorded? We’d use BLSA, Copac and Naxos. 1.Search for recordings where the composer is ‘Cage’ in: i.BLSA ii.Copac iii.Naxos (Each requiring a different search formulation) 2.Collate results and make a list of performers.

20 What recording of works by Cage exist, which performers have recorded a particular work by Cage, and what else have they recorded? 3.Search Naxos for recordings where these performers are given as the ‘performer’ and ‘Cage’ is given as the ‘composer’. 4.Search BLSA and Copac for records that name these performers and Cage, and then manually filter out results where names do not occur in relation the appropriate role. 5.Manually collate repertoire lists for each Cage performer.

21 The barriers to tractability and their solutions NNeed to consult several sources … and metadata from one source cannot guide searches of another source. IInsufficient granularity of data and/or search option. MMulti-part queries have to be broken down and results collated manually. Pen and paper! Solutions: Integration Increase granularity Optimally interactive UI (‘mSpace’)

2. Solutions 22

Integration 23

24 Rather than using many portals...

25... what if you could use just one?

26 Our partners use a variety of data formats  MARC-XML  MODS-XML  Custom MARC  Source-specific XML  Tables/CSV  We import these as RDF Why RDF? 1.Standard format for the Semantic Web. 2.It’s modular; we can add records and record fields without having to start from scratch. 3.RDF can be created using lots of different tools.

Granularity 27

28 Metadata hierarchy  We use a two-level hierarchy based on metadata type. Person ComposerScribeAuthorPerformer etc.  Crucially, our search UI exposes this hierarchy so that both broad and narrow searching is possible.

29 Adding/exposing granularity  Where possible we add to/expose the granularity of the metadata. Person ‘Immyns, John [scr]’. Scribe ‘Immyns, John’. Book ‘Come Death, I shall not fear thee...’ with author ‘Monteverdi, Claudio’. Book of printed music ‘Come Death, I shall not fear thee...’ with composer ‘Monteverdi, Claudio’. (Because of marc-leader info.)

30 Generating metadata: Grove works lists

31 Our Tool for the Works Lists

User Interface 32

33 ‘musicSpace’ is a faceted browser

34 Screencast 1: Which scribes have created manuscripts of Monteverdi’s works, and which other composers’ works have they inscribed?

35 Screencast 2: What recording of works by Cage exist, which performers have recorded a particular work by Cage, and what else have they recorded?

3. Evaluation 36

37 Feedback on speed and ease of use:  ‘All the information showed up very quickly, and it was easy to find material. It was really good to have different kinds of material in the same place.’  ‘[musicSpace offers] a speedier way to research crossed search pathways.’  ‘Excellent interface – very simple to understand.’

38 Feedback on browsing around a subject or changing the search paradigm:  ‘I would recommend musicSpace for its ability to manipulate queries in order to get results that you wouldn’t otherwise be able to get [without starting over].’  ‘I liked the ability to explore around a topic once you’ve identified something of interest.’  ‘The ability to switch columns around and add new columns was most useful.’

39 Feedback on improved data granularity:  ‘[Without using musicSpace] it would not be at all easy to do an opera character search. You would have to use printed reference books like Pipers Enzyklopädie des Musiktheaters, but even this does not have an index of characters, so you’d have to look at the entry for each opera and manually collate information. You would also have to know what you were looking for before starting out!’  ‘I used musicSpace to explore how many operas have a character named Alceste. This information simply isn’t get-at-able using other search interfaces – you’d have to sort through the information by hand.’

An invitation to try our demo  Musicologists: – Monteverdi recordings – C19th opera buffa – Schubert’s songs – C20th electroacoustic music  Music librarians / library scientists  Music technologists / web scientists 40

An invitation to try our demo musicspace.mspace.fm (needs Firefox) 41

4. The Future 42

43  Works lists project with Grove Music Online  Composer URI project

44 Thank you!