ELN Selection Template
Download NEUWAY Pharma’s guide for selecting the best electronic lab notebook software for their needs and adapt it to suit your own.
Rethinking the Role of ELNs – Are we making things worse?
In this talk, Brendan McCorkle, CEO of SciNote, explored the role of ELNs in data management, and asked the question - are we making things worse?
What is SciNote? We are a lab digitalization company with the mission to help humanity benefit the most from science and to preserve research data for future generations. Our electronic lab notebook (ELN) helps labs manage experiments, data, and teams, allows inventory tracking, and supports 21 CFR Part 11 and GLP compliance. It is the chosen solution by researchers at the FDA, USDA, and 90K+ researchers in over 100 countries.
Functionalities Overview SciNote for Industry Labs
Download this document to learn more about team onboarding, data structure, efficient inventory tracking and management, streamlined protocol and SOP management, seamless team collaboration, compliance with CFR 21 Part 11 and GxP regulations, versatile integrations, and API access.
Staying Ahead of the Shuffle: 5 Keys to Lab Inventory Tracking in Ever-Changing Environments
Have you ever encountered the frustration of being unable to replicate an experiment due to the lack of traceability in your inventory items? Or perhaps faced the challenge of maintaining data continuity when students or staff members depart, taking crucial inventory information with them? These scenarios are all too common, underscoring the vital importance of inventory tracking and traceability in research.
Join us in our upcoming webinar, as we discuss 5 crucial inventory management strategies that can directly prevent the loss of vital experimental information, ensuring your research endeavors remain on track. Plus, discover the impact of integrating an Electronic Lab Notebook (ELN) with your inventory management system through real-world use cases. See firsthand how this integration, or utilizing an ELN with an embedded inventory management system, can bridge the gaps, keeping your research data accessible, comprehensible, and fully traceable—even years after conducting the experiment.
Unleashing the Power of AI in Biotech: 5 Actionable Insights from Ganymede, Snthesis, and SciNote
The digital transformation of the field of biotech R&D is accelerating, driven by the integration of artificial intelligence (AI) and machine learning (ML). These technologies are reshaping the way biotech companies approach, analyze, and interpret vast amounts of data, paving the way for more informed decision-making and innovative breakthroughs.
However, as AI innovation has been happening so fast, what actions can companies take to keep on top of it all?
In this webinar, CEOs from SciNote, Ganymede, and Snthesis discuss the current landscape of AI use in biotech, best practices and platforms that your team can leverage right now to ready your lab and data for AI/ML, and our predictions of how AI/ML will develop in the biotech industry in the future.
SciNote Electronic Lab Notebook
SciNote is a cloud-based ELN software with lab inventory, compliance, & team management tools used by the FDA, USDA and scientists in 100+ countries.
SciNote’s flexibility allows you to organize all your data in your preferred way. It gives structure and context to all your notes, excel sheets, tables, checklists, or pictures.
Organize your work by projects, experiments, and tasks. Write notes, assign inventory items, add a protocol, and enjoy checking off the protocol steps you’ve completed.
7 Steps to Manage Your Research Data Digitally
Research funding agencies such as NIH, NSF, ERC, and the European Commission have adopted data management and sharing policies. Well-organized data will help you stay on top of your data management plan, and optimize the potential of your research – from publication, funding, to collaboration opportunities.
But, how do you get started?
In this webinar, we will walk you through 7 actionable steps that will help you begin managing your data digitally and keep your data organized. We will discuss FAIR, the guiding principle of scientific data management and sharing. Lastly, we will compare common ways of recording and storing data, and discuss their pros and cons.
This webinar is open to anyone interested in managing research data digitally. We will focus on the strategies to get you started, regardless of what system you will be using. You are welcome to share information about this webinar with anyone you think might be interested.
Keep the TCO of Your Big Data Platform Under Control with HPCC Systems®
In today’s enterprise, a successful big data strategy can mean the difference between success and failure. For example, Netflix reports the company is able to save $1 billion a year from customer retention thanks to its use of big data analytics, and enterprises in every other vertical market are following suit. Market research firm Statista forecasts big data analytics software spending will hit $68 billion by 2025. But adopting a big data strategy is a big undertaking for enterprises, and there are a host of questions an IT team must answer before they can decide on the best big data platform for their needs.
This paper will examine multiple criteria an enterprise IT team should consider before they adopt any big data platform. By rigorously evaluating a potential platform in each of these categories, IT teams will have a better understanding of the total cost of ownership (TCO) of their chosen platform. The paper will then apply each of those criteria to reveal how well an HPCC Systems data lake platform addresses the criteria. Finally, the paper will examine how an actual HPCC Systems customer evaluated HPCC Systems TCO and decided the platform was the best fit for their big data needs.
Understanding HPCC Systems® and Spark – A Comparative Analysis
Since its beginning, HPCC Systems has given its users a platform consisting of a single homogenous data pipeline. This significantly minimizes the amount of effort users spend on platform management, installation, and maintenance. Perfect for both data lakes and warehouses, HPCC Systems is extremely capable and efficient in processing large amounts of data due to an architectural design that leverages two specialized clusters, named Thor and Roxie, to manage and optimize the platform’s various functions.
This paper serves as a comparison between the architectures and feature support of Spark and HPCC Systems in regard to data lake capabilities.
HPCC Systems®: The End-to-End Data Lake Management Solution
Today, most organizations recognize that data is key to the ability to innovate and remain competitive in a rapidly changing business landscape. A key challenge:
As datasets become larger and more complex, it’s impossible to quickly respond to changing business needs using traditional relational data store such as data warehouse.
To overcome this challenge, many organizations — including some of the world’s largest companies — are successfully using a proven alternative approach: a data lake. Data lakes support datasets that are extremely large, complex and diverse, and they easily accommodate new data sources such as IoT. They allow IT groups to quickly create new applications that support changing business needs, unlocking the power of complex data for all users within the organization. They also scale much more easily and cost-effectively than relational databases. As a result, data lakes enable greater responsiveness to business groups and external customers, reduced costs, and greater scalability.
Taming the Data Lake: The HPCC Systems Open Source Big Data Platform
A “Data Lake” is an architecture and methodology for the continuous management of complex data that stores data on raw format for increased agility on data exploration. As it enters the lake, each piece of data is readily available for manipulations and insights via a unique identifier and a set of extended metadata tags. In contrast, a “Data Warehouse” stores data in a predefined format for faster delivery of data analysis results.
HPCC Systems offers the best of both worlds by combining the fast performance of a Data Warehouse for information delivery with the ability to treat data as if it were in a Data Lake when it comes to data exploration. HPCC Systems uses distributed data architecture and a parallel processing methodology in order to work with large datasets. Enterprises are adopting data lake technology to manage their rapidly growing internal datasets and to solve complex problems through data analysis to improve their relationships with customers and suppliers.
All Digital 3 Evaluation Checklist
Selecting an ELN (Electronic Lab Notebook) for your lab can be overwhelming. This checklist will help you gather information and make the necessary decisions to move into the next phase of choosing an ELN system.
NEOsphere Streamlines Experimentation Process With eLabJournal
NEOsphere strives to become the preferred proteomics partner of pharmaceutical and biotechnology companies active in the TPD space to expand their programs and create new entry points for drug discovery.
To streamline their documentation process and track samples more efficiently, the NEOsphere team searched for a customisable solution that fit their unique needs. They needed an online solution to scale up their documentation and enable them to better manage their increased samples throughout the entire experimentation process.
eLabNext Enables Internal COVID-19 lab for Boston University
Boston University (BU) was able to establish an in-house COVID-19 testing lab for its students, faculty, and staff with the help of eLabNext solutions. Despite the challenge of integrating two separate EMR systems and testing robots, eLabNext's robust APIs played a critical role in enabling the lab to process over 9,000 samples at its peak. This case study showcases how eLabNext facilitated BU's testing objectives by providing a streamlined and efficient approach. If you're interested in integrating custom lab tools and equipment like BU, download the case study to learn more.
Bringing ‘All Digital’ to Your Lab
Interested in learning about the transition from paper to digital in the lab? Download our white paper.
Key Points:
- Life science labs across academia, industry and government are producing, storing, analyzing and sharing a massive amount of digital data.
- Yet, many researchers still rely on paper lab notebooks that don’t have the capacity, formatting or sharing capabilities to accommodate or integrate digital data.
- An all-digital approach using an electronic lab notebook (ELN) can solve these issues through improved searchability, time-saving functionality, decreased data entry errors, and more.
- eLabJournal is an intuitive, flexible, all-in-one ELN that improves lab efficiency when documenting, organizing, searching, and archiving data, samples, and protocols.
