Modern research technologies have greatly increased the amount of scientific data being generated, but making full use of that data is still a major challenge. Data accessibility is a consideration at all stages of the research process; for bench scientists making data accessible to informaticians, for teams sharing data cross-departmentally, and for researchers making data accessible to the public.

The accessibility of data is essential for a number of reasons:

1. Minimizing Data Redundancy of Research Efforts

Research redundancy is a major problem within research organizations and across the research community. By making data accessible to their desired audience, researchers can reduce the number of redundant experiments conducted and instead iterate upon existing research to accelerate discovery.

2. Drawing More Reliable Conclusions from More Data

Broader data accessibility allows research teams to pool data and conduct analysis with greater confidence in their results. The more data a researcher has access to, the more statistical power they have to validate research conclusions and preempt questions of data quality.

3. Inspiring Novel Questions from Different Approaches

New research questions are inspired by different research approaches and through the study of new methodology. Attacking scientific investigations from varying perspectives also helps reduce bias in analytics, experimental design, and conclusion drawing.

Expanding Data Accessibility with LabKey Server

LabKey Server not only helps teams collect and curate their data, but also helps make it accessible to collaborators and downstream researchers.

Web-Based Access

LabKey Server allows researchers to make their data accessible to a broad or narrow audience through a web-based portal. Web-based access makes it easy to share data as desired and allows interested collaborators to evaluate and alternatively analyze “self-serve” research data. This method of data sharing is both more secure than email (see fine grained permissions below) and much lower overhead than a standard institutional database as users can query, view, and export data without having to interface with a data scientist.

Fine-Grained Permissions

LabKey’s fine-grained permissions model makes secure, selective sharing of to data simple and reliable. With LabKey Server, teams can easily control who sees their data, restricting access to selected individuals or pre-defined groups, or making data accessible the general public. Researchers also have fine-grained control over what datasets are shared: either a single table of data or an entire research project.

Powerful Metadata

LabKey Server captures detailed metadata to help increase discoverability of research data and provide crucial context for other researchers who hope to explore, reanalyze, and/or expand upon it. Research teams can customize metadata captured for each of their data types and add organization specific metadata to support internal needs.

Interested in learning more about how LabKey Server can enhance the accessibility of your research data? Contact the LabKey team for more information or request a demo!

*To learn how configure accessibility features of LabKey Server, read documentation >

High-throughput analysis techniques are incredibly powerful and provide teams with more data than ever. While that depth of data often holds the key to scientific insights, organizing such large quantities of data in a consistent and discoverable way has become a major challenge for research teams.

Many teams rely on spreadsheet-based systems to organize and manage their data. This approach becomes less-effective as research scales because spreadsheet-based strategies lack two essential characteristics:

1. Consistency

Manual file management relies on the individual contributor’s abilities to consistently create, name, and store data files. This opens the door to a wide range of human errors that will ultimately impact the discoverability and reliability of your data. Common consistency errors that result from manual data management include:

• Poorly named files
• Inconsistent locations
• Duplicate files

2. Discoverability

Collecting data is a giant hurdle in research, but in reality, it is just the first of many. Researchers need to be able to locate datasets of interest in order to conduct analysis. In a file based environment, discoverability of files is dependent on the consistency with which they are maintained. Were they saved in the correct location? Have they been named according to an agreed upon convention? Is there a clear authoritative file or are there duplicates?

A hitch in any one of these areas can severely hinder the discoverability of your data and make it significantly more difficult to:

• Track what research data has already been collected
• Find the data you are looking for when it comes time to analyze

Biology-Aware Data Management with LabKey Server

Scientific data management systems like LabKey Server, help increase the consistency and discoverability of your research data. LabKey Server increases the consistency of data management by providing structured data grids for storing various type of research data. Each data grid type also captures relevant metadata, specific to that data type, in order to help make data more discoverable.

Research-Centric Data Structures

Unlike spreadsheets that treat all types of data the same, LabKey Server provides four primary data structures with unique features to better support common types of research data.*

LabKey Assays – Assay data grids capture data generated from individual experiment runs. Assay data is automatically structured in a batch-run-results hierarchy when data files are added. LabKey Server supports data a variety of common assay designs out of the box, but teams can also design their own assay data structure using LabKey’s General Purpose Assay Design.

LabKey Datasets – Datasets track patient/subject measurements over time. LabKey datasets are automatically aligned and joined together, making it easy to query the integrated data and to create visualizations from multiple datasets.

LabKey Specimens – Specimen repositories track the status of each specimen and vial in your inventory. Built-in reports provide a birds-eye view of specimen information, and advanced search capabilities allow for easy location of specimens.

LabKey Lists – LabKey lists provide general purpose, online, interactive grids for any tabular data. Data stored as a LabKey list can be sorted, filtered, and visualized using built-in tools.

Storing data in a consistent, structured manner is the key for teams that hope to achieve maximum efficiency in operations and maximum value from their data. Not only is it much simpler to find data when it is stored in an expected location, but the centralization and integration makes it possible to query data to more quickly locate information of interest.

Interested in learning more about how LabKey Server can increase consistency and discoverability of your research? Contact the LabKey team for more information or request a demo!

*To learn how to add data to LabKey Server, read documentation >

Our collaborators at the O’Connor Lab (University of Wisconsin-Madison) are making headlines for releasing real-time data via LabKey Server to help accelerate Zika virus research. Recently featured in the Nature article “Zika researchers release real-time data on viral infection study in monkeys,” Dave O’Connor and his team are being applauded for making their research available so quickly.

“O’Connor’s team is to be lauded for their efforts to make their Zika virus data publicly available as soon as possible,” says Nathan Yozwiak, a senior scientist in Pardis Sabeti’s laboratory [computational geneticist at the Broad Institute and Harvard University in Cambridge] “Distributing up-to-date information — in this case, animal model data — as widely and openly as possible is critical during emergencies such as Zika, where relatively little is known about its pathogenesis, yet public concerns and attention are so high.”

The O’Connor lab uses LabKey Server to manage their extensive list of experiments, Illumina sequencing data, purchases, oligonucleotides, freezer samples, and other lab inventory, as well as to provide basic electronic lab notebook (ELN) functionality. To make their LabKey Server data public, the O’Connor lab simply had to update the study permissions.

“It was easy for the ZEST members to make their online lab notebook open to all, O’Connor says. The team uses the biomedical-research collaboration system LabKey Server, as does the Wisconsin National Primate Research Center in Madison, which is where many of the ZEST collaborators work and which (along with the US National Institutes of Health) is supporting the research. Researchers created a study to store and update their data, and simply had to switch permissions to allow anyone to view it. Meanwhile, regulatory agencies at the University of Wisconsin–Madison understood that the work was time-sensitive and expedited approvals for animal care and biosafety (without reducing scrutiny, O’Connor adds).”

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