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LABORATORY INFORMATICS g


are under pressure to complete short- term projects, rather than think about the overarching business objectives, and ‘what it is we are trying to solve in the long-term,’ Carter adds, concurring with Schaefer. Organisations should try to turn their thinking around and, instead of focusing on a short-term answer to an immediate question, look more globally at the overall problem, what are the available solutions, how long will they take to implement, and how that can be worked into a business model. ‘It’s a case of letting the timelines be dictated by the solution, rather than the solution being dictated by the timeline.’


Shifting regulatory sands The constantly changing regulatory landscape is also dictating the direction of platform development. There are tools emerging now that can overlay data and ensure it complies with regulations when applied in a regulated context, Carter notes. ‘The vision is that we will be able to separate regulatory elements of data management from the technological aspects of data collection, storage, interrogation and analysis. Companies like Arxspan want to be able to present the ideal software capabilities, user interfaces and security for our customers, knowing that there are third-party platforms that can be layered on top of these solutions to manage regulatory compliance aspects to data utility and control.’ One example, Carter notes, is Tranquil Data, a 2018 venture-backed startup that is developing software that is claimed to help firms transform and scale by addressing the challenge of implementing transparent methods for governing how data is used. Whatever the approach to data control


– top-down or bottom up in Schaefer’s words – solutions will inevitably be cloud-based, suggests Carter. Trying to shoehorn data into a legacy SDMS system doesn’t make sense, nor does moving it in this form into the cloud, which may not be feasible. ‘As one consultant in the SDMS space pointed out to me recently, this approach is effectively just transferring your data control issues from inside your data centre, to outside of your data centre, which can be cost- prohibitive. It also doesn’t address another key issue, which isn’t so much about where to put it, but how to put it there. Legacy systems may commonly limit the ability of administrators to put data in the cloud in the most cost-effective way.’ Making data intimately accessible while still under control will always be linked with the ability to keep that data secure, Carter notes. ‘Most commercial data


18 Scientific Computing World October/November 2019


“What will it cost me to bring that data into this open format, and what does it cost me to get that data out again in front of the scientists or decision makers who need it”


systems operate at record level security, but the Arxspan ELN and suite of cloud- hosted registration, inventory and assay management tools has been developed as a fully integrated data management and search platform that addresses security at the field level, and so provides an extra layer of confidence for collaborative research.’


Security at the most granular level What that means is that the system gives customers the option to set in place security permissions and access control at the most fundamental level, he continued. ‘By allowing view, and edit privileges at a field level, multiple scientists can collaborate on a scientific process or workflow without exposing sensitive information. Field security works with field state to limit or expose access to data in a just-in-time fashion for a user.’ Organising data security at this level takes a lot more thought to instigate and maintain, but can save problems downstream, Carter notes. ‘We offer that level of security, but the discipline of maintaining that security level and understanding how to document data is critical.’ The Arxspan platform has a number


of differentiating features that give customers better control of their data


and how that data is used, he claims. ‘Our architecture gives users the ability to run proprietary algorithms on-premise and still interface with the cloud solution, while the architecture’s RESTful API set give companies complete flexibility to carry out functions such as creating new forms, using their own tools.’ Two key benefits are scaling of individual processes and future-proofing of the system. ‘Managing the system by API means Arxspan can monitor which processes are under high demand and scale the resources for these processes, to improve end-user performance and eliminate potential system failures. Using RESTful API for the platform allows new capabilities to be built and plugged into the system, with limited impact on platform operation.’ This allows for more dynamic updates


to individual components of the system, without delays that might be caused by a major release cycle, Carter notes. ‘Customers can also use the API hooks to write, maintain and host proprietary web services in their own data centre or virtual private cloud, and still have the processes executed as part of normal user experience.


Synchronous / asynchronous processing Uniquely, Arxspan architecture allows users to separate operations into synchronous processing – in which case the operation must finish before the user has a response – and asynchronous processing, which can include long- running processes such as analytics or data warehouse population. ‘This allows for optimisation of the end-user experience, while still providing API hooks that allow longer-running activities without negatively impacting the user,’ Carter said.


@scwmagazine | www.scientific-computing.com


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