A semantic data management toolkit
Innovative and customer-centric companies in particular are increasingly confronted with enormous amounts of data, data of high complexity and changing data structures. LinkAhead can help you unearth this often still hidden treasure trove of data.
The dynamic toolbox LinkAhead enables professional data management where other approaches are too rigid and inflexible. When your requirements change, due to new circumstances, upgraded equipment or evolving needs, traditional databases are costly to adapt, if possible at all. With LinkAhead, however, these adaptations are already built in by design and easily possible whenever necessary. LinkAhead thus enables professional data management in areas which previously could not benefit from it.
LinkAhead was originally developed under the name CaosDB at the Max Planck Institute for Dynamics and Self-Organization in Göttingen for the management of laboratory data, because classical databases could not meet the requirements for flexible adaptability. The conceptual ideas were published here. In 2018, CaosDB was released as open source software and has since been commercially supported by IndiScale. Since then, a ready-to-use distribution of CaosDB has become available under the brand LinkAhead via subscription from IndiScale. In order to provide maximum reliability to our customers, we at IndiScale perform a thorough quality assurance, for example by employing extensive automated testing. A subscription to LinkAhead provides you with these advantages and additional benefits like reduced maintenance efforts.
Also try out the interactive demo:
We also offer LinkAhead customization and integration into existing systems, and of course consulting, support and training.
- LinkAhead simplifies the future adaptation of data models to new requirements.
- LinkAhead is a toolkit for semantic data management, putting the interlinking of data sets first.
- A powerful search language provides access not only to the data and its contents, but also to interlinked data sets at any hierarchical depth.
- LinkAhead can be fully automated so that data from any machine-readable source (files, devices, user input) can be incorporated without requiring user intervention.
- LinkAhead is open-source and therefore future-proof. Extensions and improvements developed for one user are automatically available to all other users as well.
Also check out our case studies:
- LinkAhead enables workflow management and data safety in a biological research laboratory.
- A production plant introduces LinkAhead for full traceability of the parts and production process and can thus increase customer satisfaction and efficiency.
- An academic research group benefits from LinkAhead’s flexibility and semantic data structuring to save time and costs.
When requirements change due to new circumstances, upgraded equipment, or shifting customer demands, other data management systems have trouble adapting to them, if possible at all. For LinkAhead, however, these adaptations are built in by design and easily possible at any time.
If the data model (in classic terms: the database layout) changes, LinkAhead retains the original data, including structure and links, and allows it to be linked, edited and searched along with the new data.
Integration into existing software environments
LinkAhead offers an open API (programming interface), for the connection of third party software and for easy extension and automation. Based on this API, libraries already exist (also as open source on gitlab.com) which enable the automatic integration of external data sources such as machine-readable files (Excel, CSV, …) or generic devices.
Field experience shows that users embrace laboratory management software primarily when its use comes without additional steps that are initially perceived as unnecessary. LinkAhead counteracts this by offering extensive automation possibilities.
Version history and workflow management
Mistakes happen, even in the best operating environments. Data in LinkAhead is versioned by default, which means that after stored data is changed, the original value, time of change, etc. are still accessible. This makes error correction simple, but the entire history remains traceable and thus complies with the rules of good scientific practice.
For processing and management of samples and workpieces, it can be important to know the current state of a particular sample or task and which processing steps are coming up next. LinkAhead provides the tools to represent this information and to realize a workflow management tool with it. For example, employees could quickly see in a sample processing flowchart which samples are to be processed next and how.
Semantic data structure
Data and sample management lose a lot of their value if it consists of isolated pieces of data. In LinkAhead, however, data sets are not only linked to each other, these links also represent a contextual (semantic) meaning. Data sets in LinkAhead always have a type, these types can inherit the properties of other types via an inheritance hierarchy. This way, even the most complex cases can be represented in a simple and concise way. For example, ‘experiment’ could be such a type, which would make it clear that the associated record represents an experiment.
It is the linking of datasets, such as samples, measurements, instruments and results or reports generated from them, that allows to search and analysis data in a way that would be complicated to implement in classical databases. For example, the following questions can be answered with LinkAhead in no time:
- “Which analyses done at site A have XY values greater than 20µmol/l?”
- “I need a table with analysis values A, B and C made with instruments of manufacturer Z within the last six months.”
These and similar queries can be performed in LinkAhead using a quick-to-learn search language, and of course they can be stored in customized search templates for easy reuse.
Detailed rights management
In LinkAhead, role-based rights (e.g. read or write access) can be granted on a finely grained level, down to individual properties of stored objects. In this way, LinkAhead enables personal data to be protected and shared data to be used.
For example, for a medical data set, the sample donors’ personal data could be shared with medical staff only, while the analysis results could be processed by laboratory staff. Data scientists, on the other hand, could have read-only access to the analysis results in this example, but could create comments that would in turn be accessible to their whole department.