BiblioDAP: The 1st Workshop on Bibliographic Data Analysis and Processing
This workshop targets researchers and practitioners in digital libraries and data science, but it is incremental as it primarily announces an event rather than presenting new research findings.
The paper introduces BiblioDAP'21, a workshop focused on addressing the challenges of automatic bibliographic data processing, such as reference extraction and citation graph building, due to the increasing volume of published papers and heterogeneous data formats.
Automatic processing of bibliographic data becomes very important in digital libraries, data science and machine learning due to its importance in keeping pace with the significant increase of published papers every year from one side and to the inherent challenges from the other side. This processing has several aspects including but not limited to I) Automatic extraction of references from PDF documents, II) Building an accurate citation graph, III) Author name disambiguation, etc. Bibliographic data is heterogeneous by nature and occurs in both structured (e.g. citation graph) and unstructured (e.g. publications) formats. Therefore, it requires data science and machine learning techniques to be processed and analysed. Here we introduce BiblioDAP'21: The 1st Workshop on Bibliographic Data Analysis and Processing.