Electronic Laboratory Notebooks (ELNs) can be categorized according to the type of researchers they cater for. ‘Cross-disciplinary’ ELNs are intended for scientists across research areas, from SOP-driven input from departments such as Quality Control, to less process-driven groups, such as exploratory biology. More specialized ‘specific’ ELNs are intended only for scientists working in a particular discipline.
What factors affect an organization’s decision when selecting between these two ELN solutions? To effectively exploit the corporate knowledge officially recorded in an ELN, an organization should expect an ELN solution to benefit the entire company, as well as each of its departments, from R&D to legal, and from IT to management.
Specific ELNs are restricted to scientists working in a defined discipline, providing particular tools and data capture relevant only to that research area. The first generation of ELNs mainly cater for chemists who typically work in small groups, providing individual chemistry features that were not applicable across multiple scientific disciplines and large scale enterprise rollouts.
Conversely, cross-disciplinary ELNs are designed to provide a working environment that is easy to use across multiple disciplines to meet the full range of scientific needs. Offering scientists, from a wide range of research areas, the ability to store, search for and organize data, cross-disciplinary ELNs also typically provide additional extensions that cater to specific groups, such as combinatorial chemists. Cross-disciplinary ELNs characteristically also offer other benefits to an organization, such as:
While specific ELNs improve the productivity of a single research function, scientists from other disciplines will not use the specialized functionality. For example, analytical chemists require tools that cater for very process-driven input which other departments, such as exploratory biology, would find of little use or relevance.
An ELN that can only be used by one specialized group cannot offer information searching and sharing, to fully exploit scientific knowledge and promote company-wide collaboration. Because each research group would require its own individual ELN solution, an organization faces significantly increased costs when investing in specific ELNs.
Integrating existing systems and workflows with several discipline-specific ELN solutions poses a larger challenge to IT departments than introducing one single cross-disciplinary ELN, particularly if specific ELNs are tied to proprietary technology.
The deployment of a single cross-disciplinary solution also offers reduced installation, training and maintenance costs compared to several discipline-specific ELN packages.
A specific ELN enables data sharing only within the research group that uses it. Data is collected and stored in a format that is often difficult to share with the rest of the organization, so the knowledge contained in it remains unused and hidden from other scientists and managers. Specific ELNs inadvertently create barriers between departments and also require users to learn how to use each individual ELN.
Cross-disciplinary ELNs, on the other hand, effectively break down these barriers and promote information sharing by storing data in one easily accessible and searchable location. The benefit, in terms of IP protection, is that the full context of the experiment is presented in one place, removing the need to both install – and ensure users can access – many disparate systems.
Information that would otherwise remain dormant, such as study reports, can be located and retrieved by anyone with access rights, encouraging collaboration across research areas and exploitation of information for business decisions and strategic planning.
By providing a central location to store all the data and historical information from an experiment, an ELN solution allows “know how” to be distributed easily as new information is captured centrally and viewed immediately across an organization, regardless of research site and geographic location.
The IDBS E-WorkBook ELN is our cloudbased enterprise ELN, which provides the critical data capture and management backbone of The IDBS E-WorkBook Cloud. E-WorkBook ELN captures all the information that a scientist generates, and stores it in a common repository, allowing easy but controlled access, focused searching, and data mining and reporting, across an entire organization.
E-WorkBook ELN stores and searches any data type, from plain text, images, sketches, scanned documents, Microsoft Office® documents, spreadsheets and presentations, to chemical structures, and the sequences of genes and proteins. In addition, linking to other data in any repository is possible, as well as access to website URLs and PDF documents.
Any systems already used in the laboratory can be seamlessly integrated with the E-WorkBook ELN, a format-independent ELN, so that any database can be ‘plugged in’. For example, the E-WorkBook ELN enables a researcher to go to a LIMS, pull out the required image file, data table or binary output, and incorporate it into a report, maintaining experimental context.
A common view of data across disparate sources
As well as offering the fundamental capabilities of a paper replacement ELN, the E-WorkBook ELN offers an extensible framework that accommodates additional functionality for specific areas of scientific research. Bringing together every aspect of an experiment, the E-WorkBook ELN gives scientists a common view of data across disparate research areas, enabling complete visibility of experimental information.
Intuitive data management tool for all disciplines
Using industry-standard technologies, the E-WorkBook ELN offers a standardized format for global scientific collaboration. It enables easy access to, and translation of, data for decision making and business analysis tasks, such as predictive studies, risk assessment and generation of patent applications, creating knowledge from scientists’ work.
While specific ELNs serve the needs of particular types of scientists due to their task-specific tools, they may hinder the sharing and protection of knowledge on an organizational scale and, in the long run, are likely to cost more to maintain.
In contrast, cross-disciplinary ELNs provide the necessary flexibility and extensibility to make data available to other researchers and decision-makers, directly increasing information sharing for effective collaboration and communication. Task-specific tools can also be provided in cross-disciplinary ELNs that accommodate ‘extensions’ aimed at scientists in specific research areas, giving a common ‘portal’ to research throughout a project team, department or organization.
In general, cross-disciplinary ELNs allow the greater exploitation of shared data and bring lower associated costs through easier deployment and integration and increased user adoption. Cross-disciplinary ELNs demonstrate that their inherent flexibility, extensibility and maintainability is superior for both short- and long-term consideration.
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