DataSeer
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About
DataSeer is an AI-powered platform designed to automate the traditionally manual and time-consuming process of monitoring open science practices within scholarly research. By utilizing Natural Language Processing (NLP), the tool scans research manuscripts to identify mentions of datasets, code sharing, protocols, and other open science indicators. Its primary purpose is to help stakeholders in the research ecosystem—specifically publishers, funders, and academic institutions—ensure that the research they support or publish adheres to data-sharing mandates and FAIR (Findable, Accessible, Interoperable, and Reusable) standards. The platform operates through three core solutions: Compliance Checks, Open Science Metrics, and SnapShot. Compliance Checks provide in-depth, article-specific reports that guide researchers on how to fulfill specific policy requirements, effectively acting as an automated editorial coach. Open Science Metrics offer a bird's-eye view, aggregating data across thousands of articles to benchmark performance by journal, institution, or country. Finally, the SnapShot tool allows for real-time triage during the submission process, flagging missed opportunities for data sharing in seconds. This suite of tools moves beyond simple data identification to track code, preprints, and study registrations. This technology is specifically tailored for editorial offices, grant-making foundations, and institutional research offices. For journal editors who lack the time to manually check every reference for raw data, DataSeer acts as a scalable editorial assistant. Funders can use the platform to verify that their grantees are providing a return on investment by sharing raw outputs as mandated by grant agreements. Institutions utilize the metrics to track their global impact and adoption of open science practices across their faculty, helping them stay competitive and transparent in a shifting academic landscape. What distinguishes DataSeer from standard research analytics tools is its focus on the actionability of compliance rather than just the observation of reporting. While other tools might list citations, DataSeer provides personalized guidance for authors, reducing the friction involved in the data-sharing process. It was founded by industry experts with a background in journal editing, ensuring the AI is trained on the specific nuances of research integrity. By integrating directly into the peer-review workflow, it transforms open science from a vague policy requirement into a measurable and manageable part of the publishing lifecycle.
Pros & Cons
Reduces manual editorial review time from 30 minutes to seconds per manuscript.
Provides specific, actionable revision instructions that help authors successfully share data.
Tracks diverse open science indicators including preprints, code, and study registrations.
Enables aggregate benchmarking across large corpuses to compare performance against peers.
Developed with support from the Sloan Foundation and guided by industry experts.
Pricing is not transparently listed and requires a direct inquiry for custom quotes.
Primary focus is restricted to scholarly research texts rather than general data monitoring.
Requires integration into existing editorial or institutional workflows to be fully effective.
Use Cases
Journal editors can automate the screening of submissions to identify missing datasets and ensure adherence to publication policies.
Research funders can monitor entire grant portfolios to verify that recipients are sharing raw research outputs as mandated by grant agreements.
Institutional administrators can use aggregate metrics to track the adoption of open science practices across their faculty and benchmark against peers.
Editorial offices can save staff time by using automated reports to coach authors on fulfilling FAIR data standards.
Platform
Features
• automated compliance reporting
• fair standards monitoring
• code and protocol detection
• personalized author coaching
• aggregate open science metrics
• real-time manuscript triage
• dataset identification
• nlp manuscript scanning
FAQs
How does DataSeer identify research datasets within a manuscript?
DataSeer uses Natural Language Processing (NLP) to scan manuscripts line-by-line in seconds. It is specifically trained to recognize references to raw datasets, methods, and protocols that authors have generated during their research.
What is the primary difference between SnapShot and Compliance Checks?
SnapShot is a real-time triage tool designed for immediate submission screening, whereas Compliance Checks provide deep, detailed reports with specific revision instructions for authors to follow.
Can DataSeer track open science practices other than data sharing?
Yes, the platform identifies a range of practices including code sharing, protocol reuse, study registration, preprint posting, and the use of open identifiers.
Who uses the Open Science Metrics tool?
This tool is primarily used by publishers, funders, and institutions to view aggregate summaries of open practices across thousands of articles for benchmarking and goal setting.
How does the tool assist with research integrity?
By ensuring that all supporting research findings and data are complete and accessible, the tool helps editors maintain integrity and transparency in increasingly challenging publishing environments.
Pricing Plans
Open Science Metrics
Unknown Price• Aggregate data summary
• Large corpus analysis
• Breakdowns by journal/publisher
• Funder and country analysis
• Strategic benchmarking
• Open practice trends
Compliance Checks
Unknown Price• In-depth compliance reports
• Tailored policy requirements
• Personalized author guidance
• Revision instructions
• FAIR standards coaching
• Editorial staff support
DataSeer SnapShot
Unknown Price• Real-time manuscript triage
• Automated workflow triggers
• Missed opportunity flagging
• Submission stage scanning
• Editorial focus prioritization
Job Opportunities
There are currently no job postings for this AI tool.
Ratings & Reviews
No ratings available yet. Be the first to rate this tool!
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