Scientific data management application

The SDMA application is an AI-enhanced platform for managing scientific publications, academic works, and research data built on top of an existing Document Management System (DMS). It enables automatic document analysis, information extraction, semantic search, and the creation of a knowledge layer that connects publications with research datasets. By integrating with IBM Planning Analytics, the application also supports budgeting, forecasting, research performance analytics, and scenario-based planning, helping organizations improve research management, compliance, and data-driven decision-making.

• Data and Document Workflow Engine
  The application automates the management and administration of scientific publications and research data through configurable workflow templates. This enables efficient document processing, simplifies access to information, and supports the effective use of scientific knowledge across research workflows.
• Analytical Modeling of Scientific Data
  The application provides advanced analytical capabilities that allow the creation of multidimensional models over scientific publications and research datasets. This enables comprehensive analysis of research outputs from multiple perspectives, such as by author, institution, research project, or funding program.
• Research Impact Assessment Templates
  The platform supports configurable templates for evaluating scientific performance and research outcomes. These templates enable organizations to assess the quality of publications, measure research impact, and support evaluation methodologies used in research funding and institutional assessment.
• Integration with External Data Sources and Applications
  The application integrates with external repositories, research databases, and institutional systems, enabling unified access to scientific publications and research documents from multiple sources.
• AI-Powered Document Content Analysis
  Using advanced Natural Language Processing (NLP) techniques, the application analyzes the textual content of documents to identify relevant entities, relationships, and contextual information, enabling automated knowledge extraction and improved document understanding.

The SDMA application is designed for organizations that manage large volumes of scientific publications, research documentation, and research data and require advanced tools for their efficient processing, analysis, and governance. The platform is particularly suitable for research institutions, universities, academic consortia, and public research organizations, where the management of scientific outputs, research datasets, and academic works forms a core part of daily operations.

The SDMA application helps organizations unlock the full value of their scientific knowledge by transforming large volumes of research documents and data into structured, searchable, and actionable information. By combining intelligent document management with AI-driven analytics, the platform improves research visibility, accelerates knowledge discovery, and supports more effective collaboration across research teams.

At the same time, SDMA strengthens governance and strategic decision-making by enabling research performance analysis, better utilization of funding and infrastructure resources, and improved transparency in research processes.