Allotrope foundation vanderwall_and_little_bio_it_world_2016OSTHUS
Allotrope Foundation is building a framework (a software toolkit) to embed a set of federated, public, non-proprietary standards for analytical data in software utilized throughout the entire analytical chemistry data lifecycle, and serves as a basis for providing controlled vocabularies and taxonomies for a variety of pharmaceutical and biotech R&D applications. This framework provides extended capabilities to build in business rules and other analytics on top of the standardized vocabularies allowing companies enhanced abilities to classify and manage their data. Legacy systems can be maintained more easily and new technologies including cloud databases, Big Data Analytics, or reasoning engines can be employed to allow researchers unprecedented access to important contextualized data, because the foundational class structure is common and highly extensible to new and expanding domains. We will briefly describe some of the current data integration and management challenges facing the industry, e.g., utilization of legacy data warehouses, the creation of new data lakes, integration of existing semantic models, cloud-scale applications and how the Allotrope Framework provides a semantic basis for improved metadata and master data management through the use of modularized semantic models that capture the most pertinent entities, attributes and relationships needed to capture the plethora of laboratory data. We will provide an update on the rapid progress of development and the release of the Allotrope Framework 1.0, including: the Allotrope Data Format (for data and semantically-described metadata), Allotrope Taxonomies, and the first release of APIs (application programming interfaces), and how Allotrope Member companies have begun to integrate these into their internal environments. We will then discuss some of the potential extensions of this framework, which in the future, could enable state-of-the-art data integration and analytics capabilities for various applications.
Мобильная разработка и IoT, machine learning, VR. Специфика проектов с точки ...MobileUp
Сергей Денисюк, CEO MobileUp, поделился опытом разработки проектов в сфере IoT, machine learning и VR на конференции MAC2016.
Тезисы:
- Существующие решения и наши кейсы.
- А есть ли спрос?
- Куда развивать студию мобильной разработки.
Go through the seven quality tools training quiz and compare, how much you have learnt from this online training of 7QC tools? The quiz has 15 multiple choice questions based on seven quality tools. Choose one answer out of the given choices for every question write these choices on a paper. After completing the quiz compare yourself with answer key in the end of quiz. Find yourself where you are in learning of 7 QC Tools. If you find your performance is not up to the mark then go again for the training of seven QC tools. You may do it as many times as you want. Improve your performance every time you go through the training.