search.noResults

search.searching

dataCollection.invalidEmail
note.createNoteMessage

search.noResults

search.searching

orderForm.title

orderForm.productCode
orderForm.description
orderForm.quantity
orderForm.itemPrice
orderForm.price
orderForm.totalPrice
orderForm.deliveryDetails.billingAddress
orderForm.deliveryDetails.deliveryAddress
orderForm.noItems
LABORATORY INFORMATICS


Maximising long-term value


CORRECT STORAGE AND USE OF DATA IS THE KEY TO KEEPING DATA ‘CURRENT’ AND RELEVANT IN MODERN LABORATORIES, WRITES SOPHIA KTORI


Data is a company’s biggest asset, yet for any organisation, keeping a handle on the


potentially vast volumes and diversity of data that are generated can represent a considerable issue. Burkhard Schaefer, BSSN Software head of product and technology, feels that pitfalls occur when companies become blinkered to reaching their short-term endpoints and don’t co-ordinate their broader goals and expectations. ‘Organisations will commonly buy


informatics platforms and dedicated pieces of software with a focus on solving one problem, or achieving one business or scientific aim. They buy their instruments, are allocated space on their network for the software, and away they go.’ It’s a very opportunistic approach that just introduces more data generators into an ecosystem that may already be chaotic, Schaefer suggested. ‘When an organisation reaches the sort of size where it has to start segregating work between departments, countries or regions, data control starts to become a major issue.’


Bottom up, or top down? There are two approaches to handling the problem, Schaefer suggests. ‘Either


16 Scientific Computing World October/November 2019


we continue with your ‘best of breed’ approach to purchasing and deploying software based on an up-front need, and then try and bring it all together at a later stage, or we try and deal with things top-down. Taking this approach means taking a step back to look at existing systems and data management practices enterprise-wide, to understand whether any new systems can feasibly be integrated into that existing framework without impacting on the ability to manage and control new and existing data, and its associated metadata.’ BSSN Software has developed a two-


part approach to data husbanding and control. The concept involves creating a data lake as a structured file store that contains all of the key data, in parallel with a metadata repository that contains pointers to all of the key and relational data and signposts to where that data resides. ‘In this way users can easily find and extract the information they need, and they can search through all of the data and metadata using key fields that will help guide them through associated information, such as how the study was carried out, by whom and using which instruments, and indicate where they can find additional underlying data.’


Navigating large-scale data ecosystems It’s a user-friendly way of navigating large-scale data ecosystems without trying to squeeze everything into one place, Schaefer explained. Try and do that and you end up storing representations of results, rather than data in its original form. ‘If you stick with a centralised approach, then every data format that you have in a central repository constitutes a liability. That’s because you need to put an infrastructure in place that can read


and present that data to the user in a human-friendly format. Whatever format the file is in will require the software that can decode it. This can become costly and may engender access problems. And if you aggregate your data to reduce complexity, it will hold less value because you have no way of looking at it in its native format.’ Standardised communication languages


for instrument interfacing, such as SiLA (Standardisation in Lab Automation), and data format standards, such as AnIML (Analytical Information Markup Language), reduce ambiguity, and ensure that all data is usable, irrespective of where or how it was derived, Schaefer notes. ‘What people typically have to consider is, 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 to use it?’


A global philosophy of data control AnIML is an ideal format because it’s XML-based, and so immediately human


@scwmagazine | www.scientific-computing.com


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36