Difference between revisions of "Scientific data management system"

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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.
[[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.


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 |title=Considerations for Management of Laboratory Data |publisher=Scientific Computing |date=2009-09-15 |accessdate=2011-05-04}}</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 |author=Elliott, Michael H.|title=Considerations for Management of Laboratory Data |publisher=Scientific Computing |date=15 September 2009 |accessdate=04 May 2011}}</ref>


2. A SDMS typically acts as a seamless "wrapper" for other data systems like LIMS and ELN in the laboratory.
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.


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 |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" />
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" />


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>:


== Modern features of a SDMS ==
* retrieve worklists from LIMS and convert them to sequence files
* 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 17:34, 12 February 2016

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 notebooks) in a compliant manner. The SDMS also acts as a gatekeeper, 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, though sometimes the SDMS software is readily apparent.

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 (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.[3]

Some of the things a standard SDMS may be asked to do include, but are not limited to[4][5]:

  • retrieve worklists from LIMS and convert them to sequence files
  • 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

  1. ↑ Elliott, Michael H. (15 September 2009). "Considerations for Management of Laboratory Data". Scientific Computing. http://www.scientificcomputing.com/considerations-for-management.aspx. Retrieved 04 May 2011. 
  2. ↑ Wood, Simon (2007). "Comprehensive Laboratory Informatics: A Multilayer Approach", pp. 3.
  3. ↑ 3.0 3.1 Deutsch, Scott (30 July 2008). "Tomorrow’s Successful Research Organizations Face a Critical Challenge". Scientific Computing. http://www.scientificcomputing.com/tomorrows-successful-research.aspx. Retrieved 04 May 2011. 
  4. ↑ Valle, Mario. "Scientific Data Management". Swiss National Supercomputing Center. Archived from the original on 06 March 2012. http://web.archive.org/web/20120306015034/http://personal.cscs.ch/~mvalle/sdm/scientific-data-management.html. Retrieved 05 March 2013. 
  5. ↑ Heyward, Joseph E. II (2009). "Selection of a Scientific Data Management System (SDMS) Based on User Requirements", pp. 1–5 (PDF).
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