PaperBot

PaperBot performs periodic full-text searches across publisher web portals (including Elsevier, Wiley, Springer, PubMed/PubMedCentral, Nature, and Google Scholar) to index and extract bibliographic metadata, full references, corresponding author email contacts, and keyword hits for structured literature metadata organization.

Key Features:

• Automated literature retrieval: Periodic full-text searches using pre-set search logic retrieve bibliographic metadata, full references, corresponding email contacts, and keyword hits from publisher portals.
• Configurable search parameters: Search portals, keywords, and metadata dimensions can be reconfigured to tailor retrieval to specific research needs.
• Metadata management and triage: Retrieved article metadata supports relevance-based triage and annotation of metadata content.
• Manual article addition: Individual articles can be added by DOI or PubMed ID.
• Microservice architecture: The system is implemented as loosely coupled modules that can operate independently or be integrated with other components.
• Scalable schema-less storage: Metadata is stored in a schema-less NoSQL database that scales within clusters.

Scientific Applications:

• NeuroMorpho.Org literature curation: Deployed as a testbed to support the NeuroMorpho.Org repository for digital neuronal reconstructions, enabling custom metadata dimensions such as animal species, brain region, neuron type, and digital tracing system, and increasing processed information volume while maintaining a stable workforce.

Methodology:

Periodic full-text searches across specified publisher portals using pre-set search logic extract bibliographic metadata, full references, author email contacts, and keyword hits; articles can be ingested manually via DOI or PubMed ID; metadata is stored in a schema-less NoSQL database and the system is organized as microservices.