Global Iconography Database
The database is available for anyone with a research need. This rich resource of historical evidence will be of great value to musicians, luthiers, bow makers, students, researchers, academics, and teachers. If you are involved in historical or period instruments, early music, living history or re-enactment, or in academic study of musicology, ethnomusicology, organology, morphology and of course iconography the database is here to support you.
920 CE - Present
Although bowing is believed to have its origins in Persia in the 9th century c.860 CE, the earliest iconographic evidence is from c.920-930 CE Iberia. The BSIP iconography database spans all periods from the earliest evidence through to the present day.
Global
Geographically neutral, the database aims to provide a global resource uniting the historical evidence of all continents.
Curated
Curators ensure that the data presented is of the best quality available, with references and links back to the holding institutions.
Improving Musicology Research
BSIP supports research, and encourages greater use of scientific principles in musicology. The digital age is changing how research is carried out and we believe that technology should be leveraged as much as possible.
Referencing
Globally unique references, with specification down to individual depictions of musicians, bows and instruments provide a previously unavailable level of referencing!
Immutable references and permalinks provide a resource you can rely on for years to come.
Anon References
Floundering in the dark with "Spain, Unknown, 12th century, private collection" is now a thing of the past! Even completely unknown works can be accurately referenced.
Reproducibility
BSIP referencing means that a given dataset can be reproduced by anyone at a later date with a simple list of the source data.
In science, research should be reproducible. We believe that musicology should have the same practice. Researchers should be able to replicate the work of others to confirm their findings.
Shared Dataset
Avoiding Groundhog Day! Instead of researchers trudging the same path collecting the same data we can concentrate our efforts on new material work instead of expending a vast effort in merely repeating the journeys of those who have gone before us.