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Scientists today collect, analyze, and generate TeraBytes and PetaBytes of data. These data are often shared and further processed and analyzed among collaborators. In order to facilitate sharing and data interpretations, data need to carry…
Most scientists need software to perform their research (Barker et al., 2020; Carver et al., 2022; Hettrick, 2014; Hettrick et al., 2014; Switters and Osimo, 2019), and neuroscientists are no exception. Whether we work with reaction times,…
Research papers in the biomedical field come with large and complex data sets that are shared with the scientific community as unstructured data files via public data repositories. Examples are sequencing, microarray, and mass spectroscopy…
A variety of schemas and ontologies are currently used for the machine-readable description of bibliographic entities and citations. This diversity, and the reuse of the same ontology terms with different nuances, generates inconsistencies…
The Open Access Movement has been striving to grant universal unrestricted access to the knowledge and data outputs of publicly funded research. leveraging the real time, virtually cost free publishing opportunities offered by the internet…
While the biomedical community has published several "open data" sources in the last decade, most researchers still endure severe logistical and technical challenges to discover, query, and integrate heterogeneous data and knowledge from…
Metaproteomics has become a crucial omics technology for studying microbiomes. In this area, the Unipept ecosystem, accessible at https://unipept.ugent.be, has emerged as an invaluable resource for analyzing metaproteomic data. It offers…
In the social sciences, researchers search for information on the Web, but this is most often distributed on different websites, search portals, digital libraries, data archives, and databases. In this work, we present an integrated search…
Over the past decade there has been a significant growth in bioinformatics databases, tools and resources. Although, bioinformatics is becoming more specific, increasing the number of bioinformatics-wares has made it difficult for…
Open science describes the movement of making any research artefact available to the public and includes, but is not limited to, open access, open data, and open source. While open science is becoming generally accepted as a norm in other…
Bio-loggers, electronic devices used to track animal behaviour through various sensors, have become essential in wildlife research. Despite continuous improvements in their capabilities, bio-loggers still face significant limitations in…
Today, data is a fuel for businesses to gain important insights and improve their performance. There is no industry in the world today that does not use data. But who will get this insight? Who processes all the raw data? Everything is done…
Nanoinformatics is a novel, rapidly growing area of research that involves the application of computational techniques to several aspects of research in the field of nanotechnology, especially concerned its application to biotechnology.…
The proliferation of vast quantities of available datasets that are large and complex in nature has challenged universities to keep up with the demand for graduates trained in both the statistical and the computational set of skills…
Data science has emerged from the proliferation of digital data, coupled with advances in algorithms, software and hardware (e.g., GPU computing). Innovations in structural biology have been driven by similar factors, spurring us to ask:…
The explosion in known microbial diversity in the last two decades has made it abundantly clear that microbes in the environment do not exist in isolation; they are members of communities. Accordingly, omics approaches such as metagenomics…
The twenty-first century has ushered in the age of big data and data economy, in which data DNA, which carries important knowledge, insights and potential, has become an intrinsic constituent of all data-based organisms. An appropriate…
Meta-learning, or learning to learn, has gained renewed interest in recent years within the artificial intelligence community. However, meta-learning is incredibly prevalent within nature, has deep roots in cognitive science and psychology,…
With the emerging technologies and all associated devices, it is predicted that massive amount of data will be created in the next few years, in fact, as much as 90% of current data were created in the last couple of years,a trend that will…
Software systems are increasingly depending on data, particularly with the rising use of machine learning, and developers are looking for new sources of data. Open Data Ecosystems (ODE) is an emerging concept for data sharing under public…