Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

Summary

Many researchers generate "medium-sized", low-velocity, and multi-dimensional data, which can be managed more efficiently with databases rather than spreadsheets. Here we provide a conceptual overview of databases including visualizing multi-dimensional data, linking tables in relational database structures, mapping semi-automated data pipelines, and using the database to elucidate data meaning.

Abstract

Science relies on increasingly complex data sets for progress, but common data management methods such as spreadsheet programs are inadequate for the growing scale and complexity of this information. While database management systems have the potential to rectify these issues, they are not commonly utilized outside of business and informatics fields. Yet, many research labs already generate "medium sized", low velocity, multi-dimensional data that could greatly benefit from implementing similar systems. In this article, we provide a conceptual overview explaining how databases function and the advantages they provide in tissue engineering applications. Structural fibroblast data from individuals with a lamin A/C mutation was used to illustrate examples within a specific experimental context. Examples include visualizing multidimensional data, linking tables in a relational database structure, mapping a semi-automated data pipeline to convert raw data into structured formats, and explaining the underlying syntax of a query. Outcomes from analyzing the data were used to create plots of various arrangements and significance was demonstrated in cell organization in aligned environments between the positive control of Hutchinson-Gilford progeria, a well-known laminopathy, and all other experimental groups. In comparison to spreadsheets, database methods were enormously time efficient, simple to use once set up, allowed for immediate access of original file locations, and increased data rigor. In response to the National Institutes of Health (NIH) emphasis on experimental rigor, it is likely that many scientific fields will eventually adopt databases as common practice due to their strong capability to effectively organize complex data.

Introduction

In an era where scientific progress is heavily driven by technology, handling large amounts of data has become an integral facet of research across all disciplines. The emergence of new fields such as computational biology and genomics underscores how critical the proactive utilization of technology has become. These trends are certain to continue due to Moore's law and steady progress gained from technological advances^1,2. One consequence, however, is the rising quantities of generated data that exceed the capabilities of previously viable organization methods. Although most academic laboratories have suffici....

Protocol

NOTE: See Table of Materials for the software versions used in this protocol.

1. Evaluate if the data would benefit from a database organization scheme

1. Download the example codes and databases (see Supplemental Coding Files, which are summarized in Table 1).
2. Use Figure 1 to evaluate if the data set of interest is "multi-dimensional".
   NOTE: Figure 1 is a gr.......

Discussion

Technical discussion of the protocol
The first step when considering the use of databases is to evaluate if the data would benefit from such an organization.

The next essential step is to create an automated code that will ask the minimum input from the user and generate the table data structure. In the example, the user entered the category of data type (cell nuclei or structural measurements), cell lines' subject designator, and number of files being selected. The rele.......

Materials

Name	Company	Catalog Number	Comments
4',6'-diaminodino-2-phenylinodole (DAPI)	Life Technologies, Carlsbad, CA
Alexa Fluor 488 Phalloidin	Life Technologies, Carlsbad, CA
Alexa Fluor 750 goat anti-rabbit	Life Technologies, Carlsbad, CA
digital CCD camera ORCAR2 C10600-10B	Hamamatsu Photonics, Shizuoka Prefecture, Japan
fibronectin	Corning, Corning, NY
IX-83 inverted motorized microscope	Olympus America, Center Valley, PA
Matlab R2018b	Mathworks, Natick, MA
MS Access	Microsoft, Redmond, WA
paraformaldehyde (PFA)	Fisher Scientific Company, Hanover Park, IL
polycloncal rabbit anti-human fibronectin	Sigma Aldrich Inc., Saint Louis, MO
polydimethylsiloxane (PDMS)	Ellsworth Adhesives, Germantown, WI
Prolong Gold Antifade	Life Technologies, Carlsbad, CA
rectangular glass coverslips	Fisher Scientific Company, Hanover Park, IL
Triton-X	Sigma Aldrich Inc., Saint Louis, MO