Posts by Melody Smith
Regulating Data
Data integrity is a broad discipline that informs how data is collected, stored, accessed, and used. The idea of integrity is a central element of many regulatory compliance frameworks, such as the General Data Protection Regulation (GDPR). It is the assurance that digital information is uncorrupted and can only be accessed or modified by those authorized to…
Read MoreChanging Culture with Taxonomies
When it comes to employees, organizations need to remember the various levels of learning of individuals in the workforce and offer reskilling to their employees in effort to keep up with changing technology and culture. Taxonomies can help. This interesting topic came to us from ATD Education in their article, “Putting Taxonomies to Work: Skills…
Read MoreMeasuring the Impact
Evaluating scientific quality is a notoriously difficult problem which has no standard solution. Ideally, published scientific results should be scrutinized by true experts in the field and given scores for quality and quantity according to established rules. Journal impact is usually a synonym for Impact Factors and other scores based on the average number of…
Read MoreMaking Content Accessible
Digital accessibility refers to the usability of a website, app, or other digital experience for all possible users, regardless of their economic status, ability, or disability. Your digital accessibility means ensuring all of your online properties are available to everyone and optimized for people with disabilities and/or impairments. It has never been more important. The Scholarly…
Read MoreIntegrity Through Governance
All organizations need to plan how they use data, so that it is handled consistently throughout for good business outcomes. Organizations that accomplish this successfully consider the who, what, how, when, where, and why of data, not only insuring security and compliance but extracting maximum value from all the information collected and stored. Federal Times…
Read MoreCollaboration and Access
Transparency, openness, verification, and reproducibility are important features of research and innovation. Open research helps to support and uphold these features across the whole lifecycle of research – improving public value, research integrity, re-use, and innovation. The Scholarly Kitchen brought this interesting information to our attention in their article, “Guest Post — Why Interoperability Matters for…
Read MoreRegister Today for SSP2023 and Save
Catch up on industry trends and network with scholarly communications colleagues at the Society for Scholarly Publishing (#SSP2023) – scheduled for May 31-June 2, 2023 with a theme of Transformation, Trust, and Transparency. This 45th annual meeting offers a program full of informational and thought-provoking presentations, covering the biggest issues and questions in the industry…
Read MoreDriven by the Data
A data-driven company requires a clear data integration strategy and a solid data culture. Tech Republic brought this interesting information to our attention in their article, “How to create a data integration strategy for your organization.” Big data and analytics have climbed to the top of the corporate agenda. Together they are poised to transform…
Read MoreUsing AI and Analytics
New artificial intelligence (AI) solutions are improving many processes and functions. Natural language processing (NLP) is a branch of AI used by search engines to understand the text people type in when they make a search. Semantic query understanding is an AI function that then helps the search engine understand the intent of the query.…
Read MoreThe Science of Learning
Data science, data analytics, and machine learning are terms that are often used interchangeably when talking about making sense of big data. But this is wrong. Data science is a field that studies data and how to extract meaning from it, whereas machine learning is a field devoted to understanding and building methods that utilize data to improve…
Read More