Spreadsheet or database: Which makes more sense?

Gordon, Kurtiss J.

doi:10.1007/bf02948725

Cited by 6 publications

(6 citation statements)

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“…However, this approach raises a number of problems as spreadsheets present numerous well-known deficiencies compared to databases when dealing with involved data. As reported in previous studies [ 1 - 4 ], spreadsheets do not scale up well and, as the spreadsheet will expand to accommodate a growing number of records of increasing complexity, data handling -- from data entry to data mining and analysis -- will become increasingly cumbersome, hence reducing the utility of potentially valuable information.…”

Section: Introductionmentioning

confidence: 99%

The EnzymeTracker: an open-source laboratory information management system for sample tracking

Triplet

Butler

2012

BMC Bioinformatics

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BackgroundIn many laboratories, researchers store experimental data on their own workstation using spreadsheets. However, this approach poses a number of problems, ranging from sharing issues to inefficient data-mining. Standard spreadsheets are also error-prone, as data do not undergo any validation process. To overcome spreadsheets inherent limitations, a number of proprietary systems have been developed, which laboratories need to pay expensive license fees for. Those costs are usually prohibitive for most laboratories and prevent scientists from benefiting from more sophisticated data management systems.ResultsIn this paper, we propose the EnzymeTracker, a web-based laboratory information management system for sample tracking, as an open-source and flexible alternative that aims at facilitating entry, mining and sharing of experimental biological data. The EnzymeTracker features online spreadsheets and tools for monitoring numerous experiments conducted by several collaborators to identify and characterize samples. It also provides libraries of shared data such as protocols, and administration tools for data access control using OpenID and user/team management. Our system relies on a database management system for efficient data indexing and management and a user-friendly AJAX interface that can be accessed over the Internet. The EnzymeTracker facilitates data entry by dynamically suggesting entries and providing smart data-mining tools to effectively retrieve data. Our system features a number of tools to visualize and annotate experimental data, and export highly customizable reports. It also supports QR matrix barcoding to facilitate sample tracking.ConclusionsThe EnzymeTracker was designed to be easy to use and offers many benefits over spreadsheets, thus presenting the characteristics required to facilitate acceptance by the scientific community. It has been successfully used for 20 months on a daily basis by over 50 scientists. The EnzymeTracker is freely available online at http://cubique.fungalgenomics.ca/enzymedb/index.html under the GNU GPLv3 license.

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Section: Introductionmentioning

confidence: 99%

The EnzymeTracker: an open-source laboratory information management system for sample tracking

Triplet

Butler

2012

BMC Bioinformatics

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“…Spreadsheets might be sufficient when one needs to organize simple data. As reported in previous studies [11,14,5,8], spreadsheets do not scale up well and, as the spreadsheet will expand to accommodate a growing number of records of increasing complexity, data handling will become increasingly cumbersome, hence reducing the utility of potentially valuable information. For example, it is not possible in Excel to generate dynamic pivot tables to aggregate data without using more complex Visual Basic macros.…”

Section: Scalability Issuementioning

confidence: 97%

BenchDW

Triplet

Butler

2013

Proceedings of the 28th Annual ACM Symposium on Applied Computing

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The rapid development of -omics techniques have provided an unprecedented amount of data, enabling system-wide biological research. However, the success of systems biology is contingent on the ability to integrate a wide variety of types of biological data to automatically predict, assign functional annotations of proteins and perform comparative analyses. Although each biological data integration system presents to some extent a number of desirable features, none of them meets all the requirements for effective integration of system-wide data. In this paper, we present BenchDW, a generic and flexible benchmark framework that aims at facilitating the evaluation and quantification of the capabilities of those biological data warehouses. It currently comprises 22 different metrics ranging from documentation quality to accuracy and response times, which may be recorded for different hardware configurations. Each metric can be weighted to better suit the user's specific needs and compared to the gold standard. BenchDW was designed to be flexible, easy to use and offers many benefits over spreadsheets, thus presenting the characteristics required to facilitate acceptance by the scientific community. We demonstrate the utility of BenchDW by briefly reviewing three data warehouses (BioMart, BioXRT and InterMine) and by showcasing how it can be leveraged to identify the specificities of the systems of interest. BenchDW is available online at

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“…Databases improve data integrity and data consistency. "Some things, which are difficult to do or error prone in spreadsheets, can be done easily and reliably in database" [20].…”

Section: B Concurrent Design Engineeringmentioning

confidence: 99%

Open-source Framework for the Concurrent Design of CubeSats

Gateau

Senaneuch

Cordero

et al. 2021

2021 IEEE International Symposium on Systems Engineering (ISSE)

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In this paper, the open-source Nanospace framework is presented, dedicated to facilitate concurrent engineering during the preliminary design phase of CubeSats. It allows for direct information exchange between third-party expert software, while allowing transparent data visualization to any team member. It provides a web based GUI, and relies on a database with ACID properties and provides a RESTful API. Nanospace ensures concurrent access to the data, which is relevant when teams are working remotely. Nanospace also provides an intuitive way of visualizing other experts' contributions that can be of high value when looking for internal project understanding and transparency. The paper presents the modular software architecture of Nanospace, as well as design choices and the different options to connect to third-party specialized software and the database.

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Spreadsheet or database: Which makes more sense?

Cited by 6 publications

References 0 publications

The EnzymeTracker: an open-source laboratory information management system for sample tracking

The EnzymeTracker: an open-source laboratory information management system for sample tracking

BenchDW

Open-source Framework for the Concurrent Design of CubeSats

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