Metadata

Metadata, or data about data, play a crucial rule in social sciences to ensure that high quality documentation and community knowledge are properly captured and surround the data across its entire life cycle, from the early stages of production to secondary analysis by researchers or use by policy makers and other key stakeholders. The paper provides an overview of the social sciences metadata landscape, best practices and related information technologies. It particularly focuses on two specifications - the Data Documentation Initiative (DDI) and the Statistical Data and Metadata Exchange Standard (SDMX) - seen as central to a global metadata management framework for social data and official statistics. It also highlights current directions, outlines typical integration challenges, and provides a set of high level recommendations for producers, archives, researchers and sponsors in order to foster the adoption of metadata standards and best practices in the years to come.social sciences, metadata, data, statistics, documentation, data quality, XML, DDI, SDMX, archive, preservation, production, access, dissemination, analysis

Ontoverse: Collaborative Knowledge Management in the Life Sciences Network

This paper regards the two aspects of knowledge networking: data networks for information integration and social networks for information sharing in communities. The importance of ontologies as a means for effective information integration is discussed and related to the current Web 2.0 trends. The Ontoverse ontology wiki is introduced as a tool for collaborative ontology engineering and knowledge management with particular focus on interlinking the research community within the life sciences

Knowledge Graph Completion to Predict Polypharmacy Side Effects

The polypharmacy side effect prediction problem considers cases in which two drugs taken individually do not result in a particular side effect; however, when the two drugs are taken in combination, the side effect manifests. In this work, we demonstrate that multi-relational knowledge graph completion achieves state-of-the-art results on the polypharmacy side effect prediction problem. Empirical results show that our approach is particularly effective when the protein targets of the drugs are well-characterized. In contrast to prior work, our approach provides more interpretable predictions and hypotheses for wet lab validation.Comment: 13th International Conference on Data Integration in the Life Sciences (DILS2018

Selected papers from the 16th Annual Bio-Ontologies Special Interest Group Meeting

Copyright @ 2014 Soldatova et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Over the 16 years, the Bio-Ontologies SIG at ISMB has provided a forum for vibrant discussions of the latest and most innovative advances in the research area of bio-ontologies, its applications to biomedicine and more generally in the organisation, sharing and re-use of knowledge in biomedicine and the life sciences. The six papers selected for this supplement span a wide range of topics including: ontology-based data integration, ontology-based annotation of scientific literature, ontology and data model development, representation of scientific results and gene candidate prediction

The Translational Medicine Ontology and Knowledge Base: driving personalized medicine by bridging the gap between bench and bedside

Background: Translational medicine requires the integration of knowledge using heterogeneous data from health care to the life sciences. Here, we describe a collaborative effort to produce a prototype Translational Medicine Knowledge Base (TMKB) capable of answering questions relating to clinical practice and pharmaceutical drug discovery. Results: We developed the Translational Medicine Ontology (TMO) as a unifying ontology to integrate chemical, genomic and proteomic data with disease, treatment, and electronic health records. We demonstrate the use of Semantic Web technologies in the integration of patient and biomedical data, and reveal how such a knowledge base can aid physicians in providing tailored patient care and facilitate the recruitment of patients into active clinical trials. Thus, patients, physicians and researchers may explore the knowledge base to better understand therapeutic options, efficacy, and mechanisms of action. Conclusions: This work takes an important step in using Semantic Web technologies to facilitate integration of relevant, distributed, external sources and progress towards a computational platform to support personalized medicine. Availability: TMO can be downloaded from http://code.google.com/p/translationalmedicineontology and TMKB can be accessed at http://tm.semanticscience.org/sparql

The integration of indigenous knowledge systems (IKS) in the teaching of conservation of biodiversity and natural resources : a critical case study of grade 10 life sciences educators in the Pinetown district.

Thesis (M.Ed.)-University of KwaZulu-Natal, Durban, 2009.This is a qualitative case study which sought to explore the integration of indigenous knowledge systems (IKS) in the teaching of conservation of biodiversity and natural resources by Grade 10 Life Sciences Educators in the Pinetown district. The study was done in two parts. Part one explored the Grade 10 Life Sciences educators’ understanding of the integration of indigenous knowledge in Life Sciences and the extent to which the educators integrated indigenous knowledge in their teaching of conservation of biodiversity and natural resources. The data analysed was collected through questionnaires with open ended questions. Part two interrogated how the two educators who were purposively selected from part one of the study integrated indigenous knowledge in their teaching; as well as what informed the way they integrated indigenous knowledge in their teaching. The data analysed was collected through a pre-observation interview, a lesson observation and a post-observation interview with each of the two participants. The data was analysed within the conceptual framework of teachers as cultural brokers. The National Curriculum Statement (NCS) policy document for Life Sciences explains indigenous knowledge as another way of knowing and as an alternative way of explaining concepts that are usually explained using scientific knowledge. Hence it encourages the interaction of different ways of knowing in formal schooling. The analysis of part one of the study showed that 90% of the educators that participated in the study said that they integrated indigenous knowledge in their teaching of conservation of biodiversity and natural resources. The analysis of how the educators integrated indigenous knowledge in their teaching and what they did when they integrated indigenous knowledge showed that, even though the educators verbally asserted that they integrated indigenous knowledge in their teaching, there was in fact no evidence of a proper understanding and integration of indigenous knowledge in their teaching. Instead, the educators’ integration of indigenous knowledge point to the educators using indigenous knowledge to foster and strengthen the learning of scientific knowledge and to promote the interest of their learners in the learning of science knowledge. At the core of the educators’ integration of indigenous knowledge is their concern with their learners’ learning of scientific knowledge. In this regard, the educators couldn’t be seen to function as cultural brokers in helping learners move between their indigenous knowledge and the science knowledge of the concept of the conservation of biodiversity and natural resources. The analysis showed a limited understanding of the principles and ideas upon which indigenous knowledge can be integrated into the Life Sciences curriculum

Selected papers from the 15th Annual Bio-Ontologies special interest group meeting

© 2013 Soldatova et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Over the 15 years, the Bio-Ontologies SIG at ISMB has provided a forum for discussion of the latest and most innovative research in the bio-ontologies development, its applications to biomedicine and more generally the organisation, presentation and dissemination of knowledge in biomedicine and the life sciences. The seven papers and the commentary selected for this supplement span a wide range of topics including: web-based querying over multiple ontologies, integration of data, annotating patent records, NCBO Web services, ontology developments for probabilistic reasoning and for physiological processes, and analysis of the progress of annotation and structural GO changes

South African Life Sciences teachers’ pedagogical beliefs and their influence on information communication and technology integration

Evidence suggests that learners actively construct knowledge and improve digital literacy when Information Communication and Technologies (ICTs) are used effectively. However, ICTs have not been exploited adequately in a science classroom. Early research argues that teachers’ pedagogical beliefs are potential barriers to delaying effective ICT integration in teaching and learning. In South Africa, research is silent regarding investigating Life Sciences teachers’ pedagogical beliefs translating into ICT integration. Hence, this study intended to close the knowledge gap and add to the body of knowledge. This study adopted a qualitative design to investigate three South African Life Sciences teachers pedagogical beliefs in Gauteng province. Qualitative data were collected from three Life Sciences teachers through lesson observations and semi-structured interviews. Teachers were observed teaching grade 11 Life Sciences classes. The video recordings were analyzed using the Teaching Dimension Observation Protocol (TDOP) to confirm findings from the questionnaire and establish how teachers integrate technology into teaching. Lastly, interviews were conducted to triangulate findings from lesson observations and questionnaires. The teachers integrated technology in ways that supported traditional beliefs. The results indicate the complexity of the relationship between pedagogical beliefs and ICT integration in practice. Teachers reflected on challenges in ICT integration that possibly impacted on their practices of ICT integration. They referred to a lack of learner access to smart devices and issues surrounding WiFi connectivity. In addition, teachers suggested that they needed training on innovative practices in ICT integration

Ontology as the core discipline of biomedical informatics: Legacies of the past and recommendations for the future direction of research

The automatic integration of rapidly expanding information resources in the life sciences is one of the most challenging goals facing biomedical research today. Controlled vocabularies, terminologies, and coding systems play an important role in realizing this goal, by making it possible to draw together information from heterogeneous sources – for example pertaining to genes and proteins, drugs and diseases – secure in the knowledge that the same terms will also represent the same entities on all occasions of use. In the naming of genes, proteins, and other molecular structures, considerable efforts are under way to reduce the effects of the different naming conventions which have been spawned by different groups of researchers. Electronic patient records, too, increasingly involve the use of standardized terminologies, and tremendous efforts are currently being devoted to the creation of terminology resources that can meet the needs of a future era of personalized medicine, in which genomic and clinical data can be aligned in such a way that the corresponding information systems become interoperable