Difference between revisions of "Scientific data management system"

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[[File:NIST Testing standard interfaces.jpg|right|thumb|NIST tests standard interfaces for its lab equipment. SDMSs allow labs to integrate equipment data with other types of data.]]A '''scientific data management system''' (SDMS) is a piece or package of software that acts as a document management system (DMS), capturing, cataloging, and archiving data generated by [[laboratory]] instruments ([[HPLC]], [[mass spectrometry]]) and applications ([[LIMS]], analytical applications, [[electronic laboratory notebook]]s) in a compliant manner. The SDMS also acts as a gatekeeper, serving platform-independent data to informatics applications and/or other consumers.
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 notebook]]s) 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:
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.<ref>{{cite web|url=http://www.scientificcomputing.com/considerations-for-management.aspx |author=Elliott, Michael H.|title=Considerations for Management of Laboratory Data |publisher=Scientific Computing |date=15 September 2009 |accessdate=04 May 2011}}</ref>
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.<ref>{{cite web|url=http://www.scientificcomputing.com/considerations-for-management.aspx |title=Considerations for Management of Laboratory Data |publisher=Scientific Computing |date=2009-09-15 |accessdate=2011-05-04}}</ref>


2. A SDMS typically acts as a seamless "wrapper" for other data systems like LIMS and ELN in the laboratory, though sometimes the SDMS software is readily apparent.
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. <ref>Wood, Simon (2007). [http://www.starlims.com/AL-Wood-Reprint-9-07.pdf "Comprehensive Laboratory Informatics: A Multilayer Approach"], pp. 3.</ref>
3. A SDMS is designed primarily for data consolidation, knowledge management, and knowledge asset realization. <ref>Wood, Simon (2007). [http://www.starlims.com/AL-Wood-Reprint-9-07.pdf "Comprehensive Laboratory Informatics: A Multilayer Approach"], pp. 3.</ref>


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.<ref name="SciComp1">{{cite web|url=http://www.scientificcomputing.com/tomorrows-successful-research.aspx |author=Deutsch, Scott |title=Tomorrow’s Successful Research Organizations Face a Critical Challenge |publisher=Scientific Computing |date=30 July 2008 |accessdate=04 May 2011}}</ref> 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 (SOPs, safety documents, etc.) 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.<ref name="SciComp1" />
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.<ref name="SciComp1">{{cite web|url=http://www.scientificcomputing.com/tomorrows-successful-research.aspx |title=Tomorrow’s Successful Research Organizations Face a Critical Challenge |publisher=Scientific Computing |date=2008-07-30 |accessdate=2011-05-04}}</ref> 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.<ref name="SciComp1" />


Some of the things a standard SDMS may be asked to do include, but are not limited to<ref name="SDMArch">{{cite web |url=http://personal.cscs.ch/~mvalle/sdm/scientific-data-management.html |archiveurl=http://web.archive.org/web/20120306015034/http://personal.cscs.ch/~mvalle/sdm/scientific-data-management.html |author=Valle, Mario |title=Scientific Data Management |publisher=Swiss National Supercomputing Center |archivedate=06 March 2012 |accessdate=05 March 2013}}</ref><ref>Heyward, Joseph E. II (2009). [https://scholarworks.iupui.edu/handle/1805/2000 "Selection of a Scientific Data Management System (SDMS) Based on User Requirements"], pp. 1–5 (PDF).</ref>:


* retrieve worklists from LIMS and convert them to sequence files
== Modern features of a SDMS ==
* interact real-time with simple and complex laboratory instruments
* analyze and create reports on laboratory instrument functions
* perform complex calculations and comparisons of two different sample groups
* monitor environmental conditions and react when base operating parameters are out of range
* act as an operational database that allows selective importation/exportation of ELN data
* manage workflows based on data imported into the SDMS
* validate other computer systems and software in the laboratory
 
==SDMS vendors==
 
See the [[SDMS vendor]] page for a list of SDMS vendors past and present.


== References ==
== References ==
<references />
<references />
<!---Place all category tags here-->
[[Category:Laboratory informatics]]
[[Category:Software systems]]

Revision as of 16:49, 4 February 2016

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