Track: DML

Mathematicians dream of a digital archive containing all peer-reviewed mathematical literature ever published, properly linked, validated and verified. It is estimated that the entire corpus of mathematical knowledge published over the centuries does not exceed 100,000,000 pages, an amount easily manageable by current information technologies.

The track objective is to provide a forum for the development of math-aware technologies, standards, algorithms, and formats that can lead towards fulfilling the dream of a global Digital Mathematical Library (DML). The DML track also serves as an interdisciplinary venue to share experience and best practices among projects in digital libraries, natural language processing, optical character recognition, pattern recognition, information retrieval, and other areas that could change the paradigm for creating, storing, preserving, searching, and interacting with a mathematical corpus.

Track topics span all aspects of DML creation, maintenance, and use, including (but not limited to):

• DML creation and maintenance (content acquisition, validation and curation)
  • Acquisition from paper sources (OCR and document analysis)
  • Acquisition from digital sources (crawling and indexing)
  • Formula and diagram recognition
  • DML authoring languages and tools
  • Content extraction (math mining)
  • Classification, including application of MSC
  • DML management, including business models and funding
  • Digital rights management
  • Preservation and sustainability
• DML architecture and representations
  • Centralized and distributed libraries
  • Representations of mathematical content, including mathematical content standards
  • Metadata content and management
• DML access and applications
  • Mathematics retrieval
  • Web interfaces for DML content
  • User and application program interfaces (UIs and APIs)
  • Document processing workflows
• DML collections and systems
  • Archives of written mathematics
  • Experience from running existing DMLs

All accepted papers will address problems that arise specifically in the context of mathematical content. Nevertheless, authors of contributions that rely on sophisticated mathematical knowledge and algorithms might consider submitting their papers to the Mathematical Knowledge Management (MKM) track. Authors who wish to describe prototype DML systems and projects might consider submitting complementary papers to the Systems and Data track.