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About

Tech Ecosystem in Switzerland is an open-source platform developed via the joint efforts of a consortium of for-profit and nonprofit analytics companies including Ecosystem Mapping-as-a-Service, Global AI Industry Ecosystem Association, Deep Knowledge Analytics, Philanthropy.International, Longevity Industry Analytics, GovTech Analytics, FemTech Analytics, Deep Pharma Intelligence and 5th Industrial Revolution Institute, sponsored by Deep Knowledge Group and powered by its AI and Data Science Division.

 

It was developed as part of a series of open-access ecosystem mapping platforms aiming to provide a data-driven snapshot of numerous regional, industrial and domain-specific tech ecosystems, including major activities and developments, current state and primary trends.

 

Developed in an open-access manner for free use by ecosystem stakeholders, decision makers and the wider public, this series of projects is motivated by a steadfast commitment to the techno-ethical principle of DeepTech for social good and a recognition of technology as the most available, economical, efficient and attainable driver of special impact.

 

The launch of this series of projects has been undertaken in an effort to promote greater transparency and access to key insights and tangible analytics, and support increased interconnectivity, synergy and collaboration among ecosystem participants, decision makers, and beneficiaries.

 

As an open-source and non-profit project, all materials on this platform are freely available for secondary use, provided that a source credit is included.

 

If you would like to learn more about our efforts, or to inquire about commissioning a custom ecosystem mapping platform or project (or a co-branded pro-bono platform, which we undertake on a case-by-case basis), please write to us at contact@ecosystem-map.info; inquiries on our deeper commercial industry and domain-specific analytics services and Market Intelligence Dashboards can be made to info@deep-innovation.tech, and inquires about techno-philanthropy projects and collaborations can be sent to info@philanthropy.international.

  • How much of your results are based on self reported data?
    Wherever possible (i.e., wherever reputable industry, region or domain-specific databases exist for a given project’s topic or theme), we utilize a combination of self-reported data (e.g., obtained directly from entity websites) and multiple open-source databases. In cases where such databases do not exist, where the methodological rigour and basis of those databases cannot be manually assessed and validated for competency, relevancy, transparency and rigour by our manual analysts, or whether platform-featured entities are absent from such databases (but otherwise qualify for inclusion on the basis of the project's manually-curated analytical framework, which defines the qualifying criteria for entity inclusion and classification), we rely on data self-reported on entity websites.
  • How do you acquire your data and what are your data sources?
    We use a combination of manual, automated and semi-automated (algorithmic) approaches to data collection, using a hybrid system of our own proprietary algorithms and open-source tools, to aggregate and parse data from a wide variety of publicly-available websites and databases, including both aggregate industry-specific databases, news sources, as well as the websites of the entities featured on the platform. The exact data sources vary depending on the specific nature of the project and the resources available. Wherever possible, we utilize open-source databases with high degrees of reputability, transparency and a clear methodological description of their inclusion criteria, in combination with proprietary algorithms that extract information directly from entity (e.g., company, investor and non-profit) websites.
  • Are we able to share your results?
    Yes. Provided that you attribute us as the source of the data, you are able to share or otherwise utilise our data on your website, regardless of commercial vs. non-commercial purpose or intent.
  • How can we challenge or provide edits to your assessment/specific results
    We welcome feedback from industry stakeholders and the public, who are encouraged to write to us at contact@ecosystem-map.info with their comments and inquiries. All feedback will be reviewed manually by our analysts for relevance and validity, and implemented in cases of legitimate error or omission.
  • How often do you update your results?
    While a number of our commercial products and services have high-frequency semi-automated updating of data, typically our open-access ecosystem mapping platforms are prepared for launch, and updated at our discretion. In many cases, on the basis of manual analysis of industry, regional and domain-specific developments and monitoring, we choose to release updated iterations of our ecosystem mapping platforms and projects, sometimes as frequently as every financial quarter for very fast-developing industries or industry-regional domains.
  • What are your main data sources and data points
    We utilize a wide variety of publicly-available websites and databases, including both aggregate industry-specific databases, news sources, as well as the websites of the entities featured on the platform. The exact data sources vary depending on the specific nature of the project and the resources available. Wherever possible, we utilize open-source databases with high degrees of reputability, transparency and a clear methodological description of their inclusion criteria, in combination with proprietary algorithms that extract information directly from entity (e.g., company, investor and non-profit) websites.
  • How is your analytics AI-driven?
    AI is utilized at numerous stages in the process of an ecosystem mapping platform development. We have a variety of internally-developed AI algorithms using machine learning, natural language processing and other techniques for data collection, cleaning and validation, as well as algorithms for automated and semi-automated entity classification (according to type, industry, subsector, etc). We also utilize internally-developed parsing, data manipulation, NLP, and classification algorithms, as well as internally-developed long and short language models (LLMs and SSMs) for entity classification, data-transformation and synthesis (e.g., creating a valid and invariant set of entity-associated data from a number of combined sources), and for more complex sub-analyses like investment trends and industrial-economic assessments.
  • How can you ensure the accuracy of your data?
    We have a stringent quality assurance pipeline in place to manually review data obtained by our proprietary algorithms. Measures in place include: Manual preparation of the analytical framework underlying a given ecosystem mapping project, which quantifies and qualifies the criteria for entity classification by type and by industry, sector or, by a qualified analyst with professional experience in the thematic domain of the project Manual review by automated and semi-automated data collection outputs by qualified analysts Deeper manual review of randomised portions of parsed data Manual cross-checking of data between two distinct sources on randomised portions of a given project-specific database for human data validation
  • What GDPR compliance do you have in place?
    Privacy and security are integral to the platform’s functionality. The platform employs advanced security measures for data protection, including encrypted transmission and secure data storage. Adherence to privacy standards ensures the confidential and ethical handling of data uploaded by users, including organisational and stakeholder information.
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