DATA & COLLABORATION
Data are an input. A measurable, usable output is the product.
Quantum Hive primarily conducts its own research.
This process produces data structures, measurements, indicators, monitoring and validation outputs. Some of them also have standalone value for companies, analytical teams or research organisations.
DATA & COLLABORATION
External outputs
Structured data
Precisely defined variables for an agreed set of companies, products, locations, industries or other research objects.
Measurements and indicators
Metrics designed to track change over time and compare it with history or a relevant peer group.
Monitoring
Regular tracking of predefined variables and changes that are relevant to the client.
Validation output
An analytical report addressing a precisely defined hypothesis or relationship: question, data, methodology, test, limitations and conclusion.
Internal research
Our proprietary market hypotheses, decision rules and the way they are timed and applied remain internal.
DATA & COLLABORATION
Data provenance, rights and quality
For every external project, it must be clear in advance:
where the data come from;
under which terms they may be used;
whether they may be delivered to the client or only used to create a derived output;
which methodological changes or limitations may affect their interpretation.
A published description of a particular type of data does not mean that Quantum Hive owns, or is entitled to redistribute, every dataset of that type.
Specific rights to use and deliver data are always defined within the project scope and contractual terms.
DATA & COLLABORATION
How collaboration begins
Pilot
One clear question, a precisely defined scope and one measurable output.
We define in advance what the pilot is intended to validate and how we will determine whether further collaboration makes sense.
Validation
We assess data quality, methodology and the practical usability of the output.
The client should understand not only what the number says, but also how it was produced and where its limitations lie.
Continue
If the pilot holds up, the next phase may take the form of:
- a one-off dataset;
- regularly updated measurement;
- monitoring;
- a validation or analytical project;
- a data output delivered through a technical interface.
Price, scope, frequency, delivery format and usage rights are defined for each specific project.
Data & Professional Collaboration
help@quantumhive.czDATA & COLLABORATION
Research & Academic Collaboration
We collaborate on topics with a clearly defined question, data and methodology. Each project also includes a predefined condition under which the original hypothesis could be rejected.
Data
The data framework is defined before the project begins.
It must be clear in advance:
- which data will be available for the project;
- whether they are public, provided under contract or otherwise restricted;
- in what form they may be used;
- whether outputs may be published using the original data, an aggregated form or only the publicly available portion.
Publication
Publication rights are defined at the start of the collaboration.
If a project uses non-public or licence-restricted data, it must be determined in advance which parts of the methodology, results or aggregated outputs may be published.
Project supervision
For academic work, formal academic supervision remains with the relevant university.
Depending on the collaboration, Quantum Hive may provide professional context, a research question, data or methodological input and ongoing consultation.
Forms of collaboration
- thesis projects in collaboration with the relevant academic department;
- research projects and internships;
- joint methodological or data projects;
- professional seminars and discussions.
Contact for research and academic collaboration
find@quantumhive.cz