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McGraw-Hill unveils SmartBook 2.0 to its McGraw-Hill Connect platform
- 26 Feb 2019

McGraw-Hill Education has announced the launch of SmartBook® 2.0 as a major enhancement of its McGraw-Hill Connect® learning platform.

SmartBook 2.0, McGraw-Hill Connect's adaptive learning engine, will become standard for users at the end of 2019. The current version of SmartBook is available for more than 90 disciplines, supporting more than 200 million student interactions per month around the world. Connect is a highly reliable, easy-to-use homework and learning management solution that applies learning science and award-winning adaptive tools to improve student results and course delivery efficiency.

Based on extensive research by McGraw-Hill's learning scientists and technologists, SmartBook 2.0's enhanced algorithms are based upon advanced learning science principles to adapt to each individual learner's needs, pinpoint and resolve knowledge gaps, and increase learning efficiency by moving knowledge into long-term memory more quickly.

SmartBook 2.0 tracks student progress and provides reports that allow instructors to identify exactly where and when students are struggling. It helps instructors easily identify students who may be at risk of failing and spend time helping them with the concepts and topics they need to learn to succeed.

With these new enhancements, instructors will also have much greater course content control, including improved alignment with their syllabus and the ability to create pre-testing assignments that are personalised and based on students' weakest areas. For students, SmartBook 2.0 includes offline and online mobile access to their course assignments and a personalised learning experience that helps them focus on areas where they need extra attention.

McGraw-Hill Connect with SmartBook 2.0 is the latest expansion to McGraw-Hill's powerful learning technology portfolio in higher education, which also includes McGraw-Hill ALEKS and McGraw-Hill SIMnet.

Brought to you by Scope e-Knowledge Center, a trusted global partner for digital content transformation solutions - Abstracting&Indexing (A&I), Knowledge Modeling (Taxonomies, Thesauri and Ontologies), and Metadata Enrichment&Entity Extraction.
   
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Figshare offers its platform as new OA publishing tool at Amsterdam University Press
- 21 Feb 2019

Amsterdam University Press (AUP) has announced a partnership with Figshare to further its commitment to open access publishing.

AUP will use the repository software to quickly and efficiently make its manuscripts and supplementary data publicly available in their branded portal, aup.figshare.com.

Users will also be able to submit their data in an easy-to-use submission system. Content published in the portal will benefit from tracked usage metrics - including Altmetrics - clear licencing information, previewed files, a citable digital object identifier (DOI), and more.

According to Jan-Peter Wissink, Managing Director of Amsterdam University Press, Figshare offers its platform as a new open access publishing tool at AUP. This will help the authors to increase the visibility and usage of their work and will enable more researchers to read these publications, including those who would otherwise not be able to access that information.

Brought to you by Scope e-Knowledge Center, a trusted global partner for digital content transformation solutions - Abstracting&Indexing (A&I), Knowledge Modeling (Taxonomies, Thesauri and Ontologies), and Metadata Enrichment&Entity Extraction.
   
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eLife invests in open-source content production tool, Texture
- 18 Feb 2019

eLife has announced its investment in the development of Texture, an open-source toolset for the editing and production of manuscripts, designed to be integrated into publishers' editorial and content-delivery systems.

Originally created by Substance Software GmbH (Substance) as a JavaScript library of tools for web-based content editing, Texture has been supported by a community of organisations collectively known as the Substance Consortium and including Érudit, the Public Knowledge Project (PKP) and SciELO. eLife has now invested in Texture's development to support its own open-source publishing platform, but - as with the organisation's other open-source projects - any new features will be added to the tool in such a way that they can be repurposed by other publishers.

First started in 2010, Substance provides building blocks for custom text editors and web-based publishing systems that are essential to establish an open-source ecosystem for knowledge creation and dissemination. The developers behind Substance - Michael Aufreiter and Oliver Buchtala - built the eLife Lens Reader in 2013 and have been working on the Reproducible Document Stack project.

The non-profit eLife invests heavily in software development, new product design, collaboration and outreach so that the potential for improvements in the digital communication of new research can start to be realised. The organisation supports the development of open-source tools with extensible capabilities that can be used, adopted and modified by others in a move towards an efficient and cost-effective ecosystem for science and scientists. By working to commoditise the infrastructure for research communication, eLife aims to help publishers and researchers avoid duplicating efforts across the sector and focus instead on accelerating the pace of discovery.

Working with Substance to introduce Texture to author proofing and staff quality checks brings the organisation closer to saving time in the production process and reducing the use of external vendors.

Brought to you by Scope e-Knowledge Center, a trusted global partner for digital content transformation solutions - Abstracting&Indexing (A&I), Knowledge Modeling (Taxonomies, Thesauri and Ontologies), and Metadata Enrichment&Entity Extraction.
   
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Wolters Kluwer, Health expands its Health Language® Interoperability and Data Normalization Solutions
- 11 Feb 2019

Wolters Kluwer, Health has expanded its Health Language® Interoperability and Data Normalization Solutions to include a suite of services designed to help payers, providers and health IT vendors leverage exponentially increasing volumes of clinical data. Health Language Data Normalization Services draws on deep terminology management knowledge and clinical expertise that is now powered by machine learning to reduce the time, resources and costs associated with harmonising data for interoperability and analytics initiatives.

Today's healthcare organisations increasingly acquire vast amounts of clinical data from disparate sources such as EHRs, practice management systems, laboratories, and pharmacies - each system encoding labs, drugs, and other clinically significant information in a different way. To overcome these widespread interoperability barriers, data must be mapped to industry standards such as LOINC®, RxNorm and SNOMED CT® to support industry initiatives like quality measures reporting, clinical decision support as well as care and disease management programs.

Health Language combines unmatched industry expertise with advanced terminology tools and finely-tuned matching algorithms powered by machine learning. Wolters Kluwer clinical experts-each offering an average of more than 25 years of healthcare terminology experience-partner with healthcare organisations to analyze use cases, create a strategic approach for their unique data normalization challenges and efficiently map disparate data across domains such as labs, medications, allergies, problems, diagnoses and procedures.

Brought to you by Scope e-Knowledge Center, a trusted global partner for digital content transformation solutions - Abstracting&Indexing (A&I), Knowledge Modeling (Taxonomies, Thesauri and Ontologies), and Metadata Enrichment&Entity Extraction.
   
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Clarivate Analytics launches integrated, scalable technology platform - Cortellis Cloud
- 05 Feb 2019

Clarivate Analytics, a global leader in providing trusted insights and analytics to accelerate the pace of innovation, has launched Cortellis Cloud, an integrated, scalable technology platform that serves as a single point of access to Cortellis, the company's suite of life science intelligence solutions. Along with hosting Cortellis, Cortellis Cloud supports direct feeds of industry-leading R&D content to customers and partners along with cloud applications that enable integration of Cortellis content into partner and third-party applications.

With the exponential proliferation of data and an increasingly complex development landscape, drug, device and diagnostic researchers need more efficient and effective methods to collect, analyse and apply information across the entire R&D lifecycle. Built on Amazon Web Services (AWS), Cortellis Cloud enables integrated data models that support seamless connectivity across Cortellis solutions, enhancing collaboration via access to on-demand, enterprise-wide R&D intelligence.

Cortellis Cloud harmonises datapoints from thousands of sources within a single unified platform, making it the industry's richest resource for data-driven insights and advanced analytics for Life Science professionals. New Cortellis features and additional data assets will be rapidly deployed as they become available, making it easy for users to immediately adopt the latest content and product enhancements. Through the platform, Cortellis delivers real-time insights, predictive analytics, and advanced intelligence solutions powered by machine learning and artificial intelligence capabilities.

The expertly-curated content in Cortellis spans drug discovery through IND and NDA submission and includes scientific, patent, regulatory, clinical trial and commercial intelligence. Key applications include: Cortellis Competitive Intelligence, Cortellis Deals Intelligence, and Cortellis Trials Intelligence; Cortellis Regulatory Intelligence; Cortellis CMC Intelligence; Newport, a Cortellis solution; Integrity, a Cortellis solution; and Metacore, a Cortellis solution.

Brought to you by Scope e-Knowledge Center, a trusted global partner for digital content transformation solutions - Abstracting&Indexing (A&I), Knowledge Modeling (Taxonomies, Thesauri and Ontologies), and Metadata Enrichment&Entity Extraction.
   
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