FolkArtiNet is a project funded by DARIAH ERIC. For 2020, one of the streams of the annual DARIAH Theme funding was ‘Arts Exchanges’ with the goal to “explore what the current DARIAH knowledge base has to offer arts practitioners researchers, encourage institutional and organizational DARIAH partners within local and national DARIAH nodes to embark on collaborative projects with artists and grow our understanding of the infrastructural requirements of this community with regards to the technologies they use”.
Our objective is to identify infrastructural requirements of folk music artistic groups. We plan to investigate, understand and determine whether currently available tools and infrastructures can address the requirements or whether new tools and services should be developed. We will collect information through a series of interviews, an on-line survey and a workshop organized to facilitate artists’ experience exchange.
The project has started on December 1, 2020 and will last 12 months.
The project is funded under the Operational Programme Intelligent Development 2014-2020 Action 4.2 4/4.2/2020 which was established to support development of large strategic research infrastructures, both national and international, and to ensure their wide accessibility.
The project’s objective is to create a research infrastructure for arts and humanities. DARIAH-PL infrastructure will offer tools and services for acquiring, managing, processing and integrating various types of data from a wide spectrum of disciplines related to arts and humanities. Availability of integrated digital resources, advanced visualization tools and interpretation techniques based on Link Data paradigm, machine learning and uncertainty theory, will facilitate research in new areas and new applications in the industry.
Music Information Retrieval is one of the research areas that can contribute to the infrastructure by providing data and services and benefit from DARIAH-PL infrastructure resources. The MIR WG member institutions are also members of the project consortium. Our objective is to develop machine learning based methods and algorithms for data and knowledge explorations in the fields of music, especially Polish traditional music. They will include tools for automatic audio transcription and staff notation recognition which will provide low level music descriptors for comparative and higher level semantic analyses.
The project has started on January 1, 2021 and will last 3 years.
The project’s objective is to increase availability of digital resources of Polish cultural and scientific institutions by extending Digital Libraries Federation (FBC) functionality with content-based search.
FBC aggregates digital data from over 120 repositories, libraries, archives, museums and art galleries. Its users can search and browse these resources in one place – FBC web portal – and get access to a large number of digital assets. However, until now search was based only on metadata.
Content-based search requires representation that can be indexed. Therefore, text document which were scanned must be subjected to OCR (Optical Character Recognition) in order to obtain text representation. Similarly, music content must undergo OMR (Optical Music Recognition) in order to obtain symbolic music representation.