The benefits of integrated systems for managing both samples and experimental data: An opportunity for labs in universities and government research institutions to lead the way

Currently most biomedical labs in universities and government funded research institutions use paper lab notebooks for recording experimental data and spreadsheets for managing sample data. One consequence is that sample management and documenting experiments are viewed as separate and distinct activities, notwithstanding that samples and aliquots are an integral part of a majority of the experiments carried out by these labs

Make it better but don't change anything

With massive amounts of data being generated in electronic format, there is a need in basic science laboratories to adopt new methods for tracking and analyzing data. An electronic laboratory notebook (ELN) is not just a replacement for a paper lab notebook, it is a new method of storing and organizing data while maintaining the data entry flexibility and legal recording functions of paper notebooks. Paper notebooks are regarded as highly flexible since the user can configure it to store almost anything that can be written or physically pasted onto the pages. However, data retrieval and data sharing from paper notebooks are labor intensive processes and notebooks can be misplaced, a single point of failure that loses all entries in the volume. Additional features provided by electronic notebooks include searchable indices, data sharing, automatic archiving for security against loss and ease of data duplication. Furthermore, ELNs can be tasked with additional functions not commonly found in paper notebooks such as inventory control. While ELNs have been on the market for some time now, adoption of an ELN in academic basic science laboratories has been lagging. Issues that have restrained development and adoption of ELN in research laboratories are the sheer variety and frequency of changes in protocols with a need for the user to control notebook configuration outside the framework of professional IT staff support. In this commentary, we will look at some of the issues and experiences in academic laboratories that have proved challenging in implementing an electronic lab notebook

LabKey Server: An open source platform for scientific data integration, analysis and collaboration

<p>Abstract</p> <p>Background</p> <p>Broad-based collaborations are becoming increasingly common among disease researchers. For example, the Global HIV Enterprise has united cross-disciplinary consortia to speed progress towards HIV vaccines through coordinated research across the boundaries of institutions, continents and specialties. New, end-to-end software tools for data and specimen management are necessary to achieve the ambitious goals of such alliances. These tools must enable researchers to organize and integrate heterogeneous data early in the discovery process, standardize processes, gain new insights into pooled data and collaborate securely.</p> <p>Results</p> <p>To meet these needs, we enhanced the LabKey Server platform, formerly known as CPAS. This freely available, open source software is maintained by professional engineers who use commercially proven practices for software development and maintenance. Recent enhancements support: (i) Submitting specimens requests across collaborating organizations (ii) Graphically defining new experimental data types, metadata and wizards for data collection (iii) Transitioning experimental results from a multiplicity of spreadsheets to custom tables in a shared database (iv) Securely organizing, integrating, analyzing, visualizing and sharing diverse data types, from clinical records to specimens to complex assays (v) Interacting dynamically with external data sources (vi) Tracking study participants and cohorts over time (vii) Developing custom interfaces using client libraries (viii) Authoring custom visualizations in a built-in R scripting environment.</p> <p>Diverse research organizations have adopted and adapted LabKey Server, including consortia within the Global HIV Enterprise. Atlas is an installation of LabKey Server that has been tailored to serve these consortia. It is in production use and demonstrates the core capabilities of LabKey Server. Atlas now has over 2,800 active user accounts originating from approximately 36 countries and 350 organizations. It tracks roughly 27,000 assay runs, 860,000 specimen vials and 1,300,000 vial transfers.</p> <p>Conclusions</p> <p>Sharing data, analysis tools and infrastructure can speed the efforts of large research consortia by enhancing efficiency and enabling new insights. The Atlas installation of LabKey Server demonstrates the utility of the LabKey platform for collaborative research. Stable, supported builds of LabKey Server are freely available for download at <url>http://www.labkey.org</url>. Documentation and source code are available under the Apache License 2.0.</p

Curated Databases in the Life Sciences: The Edinburgh Mouse Atlas Project

This case study scopes and assesses the data curation aspects of the Edinburgh Mouse Atlas Project (EMAP), a programme funded by the Medical Research Council (MRC). The principal goal for EMAP is to develop an expression summary for each gene in the mouse embryo, which collectively has been named the Edinburgh Mouse Atlas Gene-Expression Database (EMAGE)

Purposive variation in recordkeeping in the academic molecular biology laboratory

This thesis presents an investigation into the role played by laboratory records in the disciplinary discourse of academic molecular biology laboratories. The motivation behind this study stems from two areas of concern. Firstly, the laboratory record has received comparatively little attention as a linguistic genre in spite of its central role in the daily work of laboratory scientists. Secondly, laboratory records have become a focus for technologically driven change through the advent of computing systems that aim to support a transition away from the traditional paper-based approach towards electronic recordkeeping. Electronic recordkeeping raises the potential for increased sharing of laboratory records across laboratory communities. However, the uptake of electronic laboratory notebooks has been, and remains, markedly low in academic laboratories. The investigation employs a multi-perspective research framework combining ethnography, genre analysis, and reading protocol analysis in order to evaluate both the organizational practices and linguistic practices at work in laboratory recordkeeping, and to examine these practices from the viewpoints of both producers and consumers of laboratory records. Particular emphasis is placed on assessing variation in the practices used by different scientists when keeping laboratory records, and on assessing the types of articulation work used to achieve mutual intelligibility across laboratory members. The findings of this investigation indicate that the dominant viewpoint held by laboratory staff other than principal investigators conceptualized laboratory records as a personal resource rather than a community archive. Readers other than the original author relied almost exclusively on the recontextualization of selected information from laboratory records into ‘public genres’ such as laboratory talks, research articles, and progress reports as the preferred means of accessing the information held in the records. The consistent use of summarized forms of recording experimental data rendered most laboratory records as both unreliable and of limited usability in the records management sense that they did not form full and accurate descriptions that could support future organizational activities. These findings offer a counterpoint to other studies, notably a number of studies undertaken as part of technology developments for electronic recordkeeping, that report sharing of laboratory records or assume a ‘cyberbolic’ view of laboratory records as a shared resource

Visualising plasmodium falciparum functional genomic data in MaGnET: malaria genome exploration tool

Malaria affects the lives of 500 million people around the world each year. The disease is caused by protozoan parasites of the genus Plasmodium, whose ability to evade the immune system and quickly evolve resistance to drugs poses a major challenge for disease control. The results of several Plasmodium genome sequencing projects have revealed how little is known about the function of their genes (over half of the approximately 5400 genes in Plasmodium falciparum, the most deadly human parasite, are annotated as hypothetical ). Recently, several large-scale studies have attempted to shed light on the processes in which genes are involved; for example, the use of DNA microarrays to profile the parasite s gene expression. With the emergence of varied types of functional genomic data comes a need for effective tools that allow biologists (and bioinformaticians) to explore these data. The goal of exploration/browsing-style analyses will typically be to derive clues towards the function of thus far uncharacterised gene products, and to formulate experimentally testable hypotheses. Graphic interfaces to individual data sets are obviously beneficial in this endeavour. However, effective visual data exploration requires also that interfaces to different functional genomic data are integrated and that the user can carry forward a selected group of genes (not merely one at a time) across a variety of data sets. Non-expert users especially benefit from workbenchlike tools offering access to the data in this way. Still, only very few of the contemporary publicly available software have implemented such functionality. This work introduces a novel software tool for the integrated visualisation of functional genomic data relating to P. falciparum: the Malaria Genome Exploration Tool (MaGnET). MaGnET consists of a light-weight Java program for effective visualisation linked to a MySQL database for data storage. In order to maximise accessibility, the program is publicly available over the World Wide Web (http://www.malariagenomeexplorer.org/). MaGnET incorporates a Genome Viewer for visualising the location of genomic features, a Protein-Protein Interaction Viewer for visualising networks of experimentally determined interactions and an Expression Data Viewer for displaying mRNA and protein expression data. Complex database queries can easily be constructed in the Data Analysis Viewer. An advantage over most other tools is that all sections are fully integrated, allowing users to carry selected groups of genes across different datasets. Furthermore, MaGnET provides useful advanced visualisation features, including mapping of expression data onto genomic location or protein-protein interaction network. The inclusion of available third-party Java software has expanded the visualisation capability of MaGnET; for example, the Jmol viewer has been incorporated for viewing 3-D protein structures. An effort has been made to only include data in MaGnET that is at least of reasonable quality. The MaGnET database collates experimental data from various public Plasmodium resources (e.g. PlasmoDB) and from published functional genomic studies, such as DNA microarrays. In addition, through careful filtering and labelling we have been able to include some predicted annotation that has not been experimentally confirmed, such as Gene Ontology and InterPro functional assignments and modelled protein structures. The application of MaGnET to malaria biology is demonstrated through a series of small studies. Initial examples show how MaGnET can be used to effectively demonstrate results from previously published analyses. This is followed up by using MaGnET to make a set of predictions about the possible functions of selected uncharacterised genes and suggesting follow-up experiments

The relationship between research data management and virtual research environments

The aim of the study was to compile a conceptual model of a Virtual Research Environment (VRE) that indicates the relationship between Research Data Management (RDM) and VREs. The outcome of this study was that VREs are ideal platforms for the management of research data. In the first part of the study, a literature review was conducted by focusing on four themes: VREs and other concepts related to VREs; VRE components and tools; RDM; and the relationship between VREs and RDM. The first theme included a discussion of definitions of concepts, approaches to VREs, their development, aims, characteristics, similarities and differences of concepts, an overview of the e-Research approaches followed in this study, as well as an overview of concepts used in this study. The second theme consisted of an overview of developments of VREs in four countries (United Kingdom, USA, The Netherlands, and Germany), an indication of the differences and similarities of these programmes, and a discussion on the concept of research lifecycles, as well as VRE components. These components were then matched with possible tools, as well as to research lifecycle stages, which led to the development of a first conceptual VRE framework. The third theme included an overview of the definitions of the concepts ‘data’ and ‘research data’, as well as RDM and related concepts, an investigation of international developments with regards to RDM, an overview of the differences and similarities of approaches followed internationally, and a discussion of RDM developments in South Africa. This was followed by a discussion of the concept ‘research data lifecycles’, their various stages, corresponding processes and the roles various stakeholders can play in each stage. The fourth theme consisted of a discussion of the relationship between research lifecycles and research data lifecycles, a discussion on the role of RDM as a component within a VRE, the management of research data by means of a VRE, as well as the presentation of a possible conceptual model for the management of research data by means of a VRE. This literature review was conducted as a background and basis for this study. In the second part of the study, the research methodology was outlined. The chosen methodology entailed a non-empirical part consisting of a literature study, and an empirical part consisting of two case studies from a South African University. The two case studies were specifically chosen because each used different methods in conducting research. The one case study used natural science oriented data and laboratory/experimental methods, and the other, human orientated data and survey instruments. The proposed conceptual model derived from the literature study was assessed through these case studies and feedback received was used to modify and/or enhance the conceptual model. The contribution of this study lies primarily in the presentation of a conceptual VRE model with distinct component layers and generic components, which can be used as technological and collaborative frameworks for the successful management of research data.Thesis (DPhil)--University of Pretoria, 2018.National Research FoundationInformation ScienceDPhilUnrestricte