Access Range: Campus Network Only

Access Address: Online Access

The NeoSCI Research Support Database (referred to as NeoSCI) is a full‑cycle research ecosystem platform. By deeply integrating and intelligently analyzing reliable academic literature information, and leveraging advanced artificial intelligence and visual analytics technologies, it provides researchers with a series of in‑depth information‑mining services—such as intelligent search, AI‑powered literature review, bibliometric analysis, AI‑assisted research topic selection, and AI‑aided grant proposal writing—to enhance efficiency in grant applications, research topic identification, literature reviews, and other key research stages, thereby supporting scientific innovation and discipline development.

1. Features & Advantages of NeoSCI

(1) Authoritative Data & AI‑Driven Analytical Reports

NeoSCI draws on publication data from over 20,000 journals included in the Chinese Academy of Sciences Journal Partitioning Table. It combines authoritative, authentic literature with advanced AI models and visualization techniques to deliver unique research‑support and discipline‑building services, including:

Bibliometric Analysis Reports: Based on data from core journals (SCIE, SSCI, AHCI, ESCI) and grounded in bibliometric theory, these reports integrate big‑data analytics, visualization, and generative AI to deconstruct and replicate the key characteristics of bibliometric papers across four dimensions—methodology, structure, data presentation, and value—generating systematic, graphically rich knowledge maps that provide a scientific basis for discipline development and research decision‑making.

Grant Proposal Reports: NeoSCI can intelligently generate evidence‑based grant proposal drafts (e.g., for the National Natural Science Foundation or National Social Science Foundation) using either literature retrieved within NeoSCI or references uploaded by users. This helps users efficiently organize literature, discover potential scientific questions, and prepare high‑quality grant applications.

Research Topic Investigation Reports: Supports logical summarization of real literature, evaluates the practical significance and innovation of a topic, and recommends more detailed research directions and sub‑topics, aiding in the selection and writing of research papers.

Literature Review Reports: Helps users intelligently synthesize specific literature, generating review content with clear, traceable references and detailed citations, thereby improving the efficiency of literature review writing.

(2) Research Competitiveness Analysis Platform

Following the same principles and classification as the ESI (Essential Science Indicators) database and applying rigorous data calibration, this platform uses innovative AI tools and literature analysis methods to conduct bibliometric and analytical tasks—such as academic evaluation, benchmark analysis, disciplinary competitive landscape assessment, and tracking of high‑impact papers—from multiple dimensions (institution, discipline, etc.). It enables quick generation of analytical reports, providing comprehensive data support and decision‑making basis for university discipline development.

(3) Intelligent Search

NeoSCI supports literature search in both Chinese and English. When searching in Chinese, users can directly input a research topic; the system will automatically analyze and extract key concepts, then intelligently recommend suitable English search terms to facilitate literature discovery. Its enhanced search function combines natural language processing and semantic analysis to accurately understand user intent and quickly locate relevant literature, improving the efficiency of literature surveys.

(4) AI‑Assisted Research Topic / Grant Topic Selection

Based on papers published in core authoritative journals, NeoSCI analyzes, summarizes, and extracts core keywords from specific studies, recommends related concepts, and—building on the strengths and limitations of existing research—proposes several relevant academic questions. This provides users with deeper insights and guides them toward more refined research directions and potential scientific problems, inspiring researchers from multiple perspectives.

2. Application Scenarios

Research Preparation Stage: Literature reporting, literature reviews, topic investigation and analysis, paper topic selection, grant topic selection, etc.

Research Implementation Stage: Thesis/dissertation proposal writing, grant proposal writing, paper writing, etc.

Results Output Stage: Journal selection for submission, patent application, etc.

Research Management: Bibliometric analysis, disciplinary analysis, research output statistical analysis, etc.

Attachment: NeoSCI Brochure – 2025 Updated Edition