With ever-increasing technological advancements, basic research laboratories are making scientific discoveries at unprecedented rates. With increasing knowledge and understanding about our world, basic research scientists need affordable ways to improve data management and sharing methodologies. When scientists can perform experiments more accurately and with better reproducibility, they are able to improve data integrity and ultimately quicken time to publication.

In order to be effective in today’s data-rich research environment, scientists are looking to software tools to help facilitate research and time to publication. LabKey Server provides essential tools to overcome key basic research challenges, including:

Effectively Managing Heterogeneous Lab Data

Effective management and merging experimental data can help identify gaps in research or highlight key insights to new discoveries, but manually comparing performance of a particular molecule, cell line, or other entity across experiments a time-consuming and difficult process.

LabKey Server helps teams manage lab data by providing:

• Assay integration modules that directly import and transform lab data, such as luminex, flow cytometry, mass spectrometry, ELISA/ELISpot, and more.
• A flexible, customizable platform that can handle data from team specific assays
• Easy-to-perform data integration

Establishing Good QC Metrics

Creating good quality control methods as part of standard workflows ensure data integrity and ultimately allow scientists to compare data across experiments to collect reliable, reproducible data.

LabKey Server helps enforce good quality control practices by providing:

• Automatic type checks, missing value indicators, and range validators on data
• Built-in QC trend reports, Levy-Jennings and other QC graphs
• Dataset QC states that flag data for review

Collaborative Data Sharing

Sharing data with internal and external collaborators improves scientific integrity and innovation. Effective collaboration reduces duplicative effort, quickens analytical time, and improves data integrity, enabling cross-functional work and quicker development of discoveries.

LabKey Server facilitates collaboration by providing:

• Multi-level security permissions, giving teams full control of what information they share and who it is shared with
• An assay request tracker that allows teams to collaboratively assign new experiments and track their fulfillment
• Study publishing tools that de-identify data, allowing collaborators to examine data and analyses without interfering with the raw data

Want to see how LabKey Server can help increase data workflows in your basic research environment? Explore these, and other features, of the LabKey Server platform with a 30-day hosted trial. Get started >

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 >

We are very excited to share that LabKey was recently selected to deliver a HIPAA and FISMA compliant data storage environment to support the collection of patient-provided data through a set of mobile device applications being developed by Boston Technology Corporation.

LabKey Server will serve as a centralized repository for data collected via the ResearchKit- and ResearchStack-based mobile applications and will integrate this data with related clinical information. The platform will also provide a portal for clinical partners to access and explore integrated data, conduct analysis, and share information with collaborators, using LabKey Server’s robust role-based permissions model and advanced security features to ensure HIPAA- and FISMA-compliant treatment of protected data.

The LabKey team is excited about this new project and the functionality it will bring to the LabKey Server platform, paving the way for future integrations with mobile research applications. This project will introduce the use of the LabKey Server platform as an enterprise-level back end service for applications developed with ResearchKit® and ResearchStack, and will allow us to offer this powerful technology to cutting-edge researchers who require rapid integration of patient-reported data with clinical data.[vc_cta h2=”” shape=”square” style=”flat”]Interested in using LabKey Server as a data management and analysis platform for your mobile app?
Contact the LabKey team to learn more![/vc_cta][vc_column width=”3/4″]

About Boston Technology Corporation

Boston Technology Corporation (BTC), a Boston-based digital health technology services company, provides mobile and web solution development for secure patient experience and engagement, medical and clinical research and IoT Human Interface applications. Please visit their case studies page for more information on applications developed by BTC for provider organizations, biotech and medical device companies, and major universities.[vc_column width=”1/4″][vc_single_image image=”76328″ img_size=”” onclick=”custom_link” link=”http://www.researchstack.org”][vc_column width=”3/4″]

About ResearchStack

ResearchStack is an SDK and UX framework for building research study apps on Android. It is designed from the ground up to meet the requirements of most scientific research, including capturing participant consent, extensible input tasks, and the security and privacy needs necessary for IRB approval.[vc_column width=”1/4″][vc_single_image image=”76327″ alignment=”center” onclick=”custom_link” link=”http://www.researchstack.org”][vc_column width=”3/4″]

About ResearchKit

ResearchKit is an open source framework introduced by Apple that allows researchers and developers to create powerful apps for medical research.[vc_column width=”1/4″]

There are many complexities involved with incorporating a data management platform into your workflow, but terminology shouldn’t be one of them! This quick guide to LabKey Server standard terms will have you speaking LabKey in no time.

Web Part – A user interface panel designed for specific functionality. Examples: file management panel, wiki editor, data grid.

Dashboard/Tab – A collection of web parts assembled together for expanded functionality.

Folder – Folders are the “blank canvases” of LabKey Server: the workspaces where you organize web parts and dashboards. Folders are also important in security: they form the main units around which security is applied and administered.

Project – Projects are top level folders. They function like folders, but have a larger scope. Projects form the centers of configuration, because the settings made at the project level cascade down into their sub-folders by default. (You can reverse this default behavior if you wish.)

Assay/Assay Design – A container for instrument-derived data, customizable to capture information about the nature of the experiment and instrument.

List – A general data table – a grid of columns and rows.

Dataset – A table like a list, but associated with and integrated into a wider research study. Data placed into a dataset is automatically aligned by subject ids and timepoints.

Data Grid – A web-based interactive table that displays the data in a Dataset, List, Query.

Report – A transformational view on the underlying data, produced by applying a statistical, aggregating, or visualizing algorithm. For example, an R script that produces a scatter plot from the underlying data.

Looking for more set-up information?
Visit the LabKey Support portal for tutorials and documentation.

Ready to get started?
Download LabKey Server Community Edition.

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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