Datico® Evidence Lab
Research
From data collection to evidence – faster, more structured, scalable.
The Datico® LIFE HUB connects your study, measurement and device data and, with validated models, distils it into a reliable statement for the individual participant (n = 1) – traceable, with confidence, carried through to the decision.
NO SOLUTION FOR STRUCTURED, SYNCHRONOUS DATA COLLECTION – AND HOW THE DATICO® LIFE HUB CREATES IT.
Challenge and solution side by side
Challenges in research
Different collection tools, inconsistent formats and manual Excel analyses make the comparability and reuse of data considerably more difficult.
Data collection, validation and preparation often require enormous personnel effort – resources that are then missing from the actual research.
Whether diagnostic devices, questionnaires or wearables – many systems operate in isolation. A central, connected data foundation for analysis and evaluation is missing.
Especially with health-related data, compliance with legal requirements (GDPR, ethics committees) is time-consuming and error-prone – particularly with manually managed processes.
The Datico® solution
The Datico® LIFE HUB provides a digital platform for standardized data collection, flexible capture modules and automated analysis. This makes sport-, health- and operations-related studies easier, more structured and more resource-efficient to conduct.
The platform is highly adaptable to study design, ethics requirements and data types. Whether physiology, diagnostics, questionnaires or training data – Datico® integrates diverse data sources and consolidates them into a consistent research data structure.
Smart dashboards and automated reports create analytical value at an early stage. Results can be interpreted faster, hypotheses tested on a data-driven basis and projects managed more efficiently.
The Datico® LIFE HUB is GDPR-compliant, research-proven and interoperable. The platform supports open interfaces, enables scalable data management and meets the highest requirements for data protection, hosting and scientific traceability.
- Heterogeneous data sources and formats
- Lack of standardization and structure
- Missing interoperability and connectivity options
- Uncertainty regarding data protection and ethics requirements
- No central control for chambers, sensors and wearables
- Time-shifted, manually merged datasets
- Technically isolated systems without data interfaces
- Lack of traceability in multiparametric experimental setups
- Missing infrastructure for interdisciplinary research data models
- Standardized collection of sport- & health-related research data
- Flexible integration of external data sources & devices
- Automated analysis & reporting functions
- Faster data analysis & evidence generation
- Data capture from altitude, climate and cold chambers
- Central capture of real-time physiological data
- Integration of wearables and diagnostic systems
- API for statistics tools such as R, SPSS, MATLAB
- Unified data model for interdisciplinary research teams
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