Infographic: SDMS Software & Its Functional Highlights

Infographic SDMS Software & Its Functional Highlights

“Capture, Catalog, Retrieve, Archive & Integrate”

Logilab SDMS is generic Scientific Data Management software designed to handle data from any analytical instrument and can facilitate data management with secured access control. It will perform scheduled data capture, cataloging, archival and facilitate restoring data. It has capabilities to extract data of interest from instrument output to be pushed to external systems like ELN, LIMS or ERP.

The global Scientific Data Management System (SDMS) Market is expected to account for USD 6327.5 million by 2027

Infographics SDMS & Its Functional Highlights

Global Electronic lab Notebook (ELN) Market 

The compound annual growth rate increased to 4.70% from 2021 – 2028

Logilab ELN Key Features:

1. Versatile Data Capture – Any instrument data of any format
2. Fully Automated, secured, error-free file handling by SDMS Data Scheduler
3. Easy Navigation, Secure, Faster & Wider search by Data Explorer
4. Human Readable Data for 21 CFR Part 11 compliance – PDF & Print Functionality
5. Comprehensive organization, categorization, and standardization of data – Tagging
6. Absolute security and control of operations – User & Password Management
7. Encyclopedic Tracking, Easy Troubleshooting – By Audit Trail
8. Easy extraction of data of interest – By Parsing Engine
9. Complete Access Control of all applications including non-compliant ones – CFR Gateway
10. Mobile usability to contemporaneously record data – By SDMS Mobile application.

Key Challenges 

Data Capture

Challenges associated with capturing data from different type of instruments, their data formats, communication protocols and other technical features

Security of Operations

Security challenges associated with users, data and system access, lack of clear tracking of who did what, at what point of time (i.e. without a history of the trail), controlling of data distribution.

Data Readability & searchability

Challenges associated with quick searching and retrieving data in a secured and controlled way, Presentation of data in a human-readable format

Data categorization

Challenges associated with mapping, categorizing and grouping of data in a logical way for easy searching and reporting

Data Integrity

Multiplicity of data existing in the system without a single source of truth due to storage of multiple versions in multiple locations (instead of single location) without any record of who and when they were created, what is the correct data that is required to be used. Challenges to fulfill the compliance requirements of statutory regulations and failure to fulfill the audit requirements affecting the continuity of business operations

Data of Interest extraction

Difficulty in separating part/parts of entire data (parsing) based on certain criteria for easy subsequent storage, processing, and reporting.

System installation, scalability, usability and portability

Challenges related to the installation of software and components, difficulties in accessing from multiple systems, issues in migrating of configuration and data from one system to another, use of non-standard software components.

Conclusion

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