Scientific data management system
A scientific data management system (SDMS) is a piece or package of software that captures, catalogs, and archives data generated by laboratory instruments (HPLC, mass spectrometry) and applications (LIMS, analytical applications, electronic laboratory notebooks) in a compliant manner, serving platform-independent data to informatics applications and/or other consumers.
As with many other laboratory informatics tools, the lines between a LIMS, ELN, and an SDMS are at times blurred. However, there are some essential qualities that an SDMS owns that distinguishes it from other informatics systems:
1. While a LIMS has traditionally been built to handle structured, mostly homogeneous data, a SDMS (and systems like it) is built to handle unstructured, mostly heterogeneous data.[1]
2. A SDMS typically acts as a seamless "wrapper" for other data systems like LIMS and ELN in the laboratory.
3. A SDMS is designed primarily for data consolidation, knowledge management, and knowledge asset realization. [2]
An SDMS can be seen as one potential solution for handling unstructured data, which can make up nearly 75 percent of a research and development unit's data.[3] This includes PDF files, images, instrument data, spreadsheets, and other forms of data rendered in many environments in the laboratory. Traditional SDMSs have focused on acting as a nearly invisible blanket or wrapper that integrate information from corporate offices (P&P, for example) with data from lab devices and other data management tools, all to be indexed and searchable from a central database. An SDMS also must be focused on increasing research productivity without sacrificing data sharing and collaboration efforts.[3]
Modern features of a SDMS
References
- ↑ "Considerations for Management of Laboratory Data". Scientific Computing. 15 September 2009. http://www.scientificcomputing.com/considerations-for-management.aspx. Retrieved 2011-05-04.
- ↑ Wood, Simon (2007). "Comprehensive Laboratory Informatics: A Multilayer Approach", pp. 3.
- ↑ 3.0 3.1 "Tomorrow’s Successful Research Organizations Face a Critical Challenge". Scientific Computing. 30 July 2008. http://www.scientificcomputing.com/tomorrows-successful-research.aspx. Retrieved 2011-05-04.
