Twitter data analytics – or : the pleasures and perils of studying Twitter

It might still sound strange to dedicate an entire journal issue exclusively to a single internet platform. But it is not the company Twitter Inc. that draws our attention; this issue is not about a platform and its features and services. It is about its users and the ways in which they interact with one another via the platform, about the situations that motivate people to share their thoughts publicly, using Twitter as a means to reach out to one another. And it is about the digital traces people leave behind when interacting with Twitter, and most of all about the ways in which these traces – as a new type of research data – can also enable new types of research questions and insights.

Doctoral research training : encouraging timely completion – case study reflections of one university on how it supports a vibrant research training culture

This is a case study of a young university striving to generate and sustain a vibrant Research Training culture. The university’s research training framework is informed by a belief in a project management approach to achieving successful research candidature. This has led to the definition and reporting of key milestones during candidature. In turn, these milestones have generated a range of training programs to support Higher Degree Research (HDR) students to meet these milestones in a timely fashion. Each milestone focuses on a specific set of skills blended with supporting the development of different parts of the doctoral thesis. Data on student progress and completion has provided evidence in highlighting the role that the milestones and training are playing in supporting timely completion. A university-wide reporting cycle generated data on the range of workshops and training provided to Higher Degree Research students and supervisors. The report provided details of thesis topic and format, as well as participation in research training events and participant evaluation of those events. Analysis of the data led to recommendations and comments on the strengths and weaknesses of the current research training program. Discussion considered strategies and drivers for enhancements into the future. In particular, the paper reflects on the significant potential role of centrally curated knowledge systems to support HDR student and supervisor access, and engagement and success. The research training program was developed using blended learning as a model. It covered face-to-face workshops as well as online modules. These were supplemented by web portals that offered a range of services to inform and educate students and supervisors and included opportunities for students to interact with each other. Topics ranged from the research life cycle, writing and publication, ethics, managing research data, managing copyright, and project management to use of software and the University’s Code of Conduct for Research. The challenges discussed included: How to reach off campus students and those studying in external modes? How best to promote events to potential participants? How long and what format is best for face-to-face sessions? What online resources best supplement face-to-face offerings? Is there a place for peer-based learning and what form should this take? These questions are raised by a relatively young university seeking to build and sustain a vibrant research culture. The rapid growth in enrolments in recent years has challenged previous one-to-one models of support. This review of research training is timely in seeking strategies to address changing research training support capacity and student needs. Part of the discussion will focus on supervisory training, noting that good supervision is the one remaining place where one-to-one support is provided. Ensuring that supervisors are appropriately equipped to address student expectations is considered in the context of the research training provisions. The paper concludes with reflection on the challenges faced, and recommended ways forward as the number of research students grows into the future.

Straightforward data management at QUT

QUT Library Research Support has simplified and streamlined the process of research data management planning, storage, discovery and reuse through collaboration and the use of integrated and tailored online tools, and a simplification of the metadata schema. This poster presents the integrated data management services a QUT, including QUT’s Data Management Planning Tool, Research Data Finder, Spatial Data Finder and Software Finder, and information on the simplified Registry Interchange Format – Collections and Services (RIF-CS) Schema. The QUT Data Management Planning (DMP) Tool was built using the Digital Curation Centre’s DMP Online Tool and modified to QUT’s needs and policies. The tool allows researchers and Higher Degree Research students to plan how to handle research data throughout the active phase of their research. The plan is promoted as a ‘live’ document’ and researchers are encouraged to update it as required. The information entered into the plan can be made private or shared with supervisors, project members and external examiners. A plan is mandatory when requesting storage space on the QUT Research Data Storage Service. QUT’s Research Data Finder is integrated with QUT’s Academic Profiles and the Data Management Planning Tool to create a seamless data management process. This process aims to encourage the creation of high quality rich records which facilitate discovery and reuse of quality data. The Registry Interchange Format – Collections and Services (RIF-CS) Schema that is used in the QUT Research Data Finder was simplified to “RIF-CS lite” to reflect mandatory and optional metadata requirements. RIF-CS lite removed schema fields that were underused or extra to the needs of the users and system. This has reduced the amount of metadata fields required from users and made integration of systems a far more simple process where field content is easily shared across services making the process of collecting metadata as transparent as possible.

Leveraging the repository infrastructure to curate institutional heritage materials, learning objects and data assets

Developing and maintaining a successful institutional repository for research publications requires a considerable investment by the institution. Most of the money is spent on developing the skill-sets of existing staff or hiring new staff with the necessary skills. The return on this investment can be magnified by using this valuable infrastructure to curate collections of other materials such as learning objects, student work, conference proceedings and institutional or local community heritage materials. When Queensland University of Technology (QUT) implemented its repository for research publications (QUT ePrints) over 11 years ago, it was one of the first institutional repositories to be established in Australia. Currently, the repository holds over 29,000 open access research publications and the cumulative total number of full-text downloads for these document now exceeds 16 million. The full-text deposit rate for recently-published peer reviewed papers (currently over 74%) shows how well the repository has been embraced by QUT researchers. The success of QUT ePrints has resulted in requests to accommodate a plethora of materials which are ‘out of scope’ for this repository. QUT Library saw this as an opportunity to use its repository infrastructure (software, technical know-how and policies) to develop and implement a metadata repository for its research datasets (QUT Research Data Finder), a repository for research-related software (QUT Software Finder) and to curate a number of digital collections of institutional and local community heritage materials (QUT Digital Collections). This poster describes the repositories and digital collections curated by QUT Library and outlines the value delivered to the institution, and the wider community, by these initiatives.

Open access spatial data and collaboration

On 19 June 2015, representatives from over 40 Australian research institutions gathered in Canberra to launch their Open Data Collections. The one day event, hosted by the Australian National Data Service (ANDS), showcased to government and a range of national stakeholders the rich variety of data collections that have been generated through the Major Open Data Collections (MODC) project. Colin Eustace attended the showcase for QUT Library and presented a poster that reflected the work that he and Jodie Vaughan generated through the project. QUT’s Blueprint 4, the University’s five-year institutional strategic plan, outlines the key priorities of developing a commitment to working in partnership with industry, as well as combining disciplinary strengths with interdisciplinary application. The Division of Technology, Information and Learning Support (TILS) has undertaken a number of Australian National Data Service (ANDS) funded projects since 2009 with the aim of developing improved research data management services within the University to support these strategic aims. By leveraging existing tools and systems developed during these projects, the Major Open Data Collection (MODC) project delivered support to multi-disciplinary collaborative research activities through partnership building between QUT researchers and Queensland government agencies, in order to add to and promote the discovery and reuse of a collection of spatially referenced datasets. The MODC project built upon existing Research Data Finder infrastructure (which uses VIVO open source software, developed by Cornell University) to develop a separate collection, Spatial Data Finder (https://researchdatafinder.qut.edu.au/spatial) as the interface to display the spatial data collection. During the course of the project, 62 dataset descriptions were added to Spatial Data Finder, 7 added to Research Data Finder and two added to Software Finder, another separate collection. The project team met with 116 individual researchers and attended 13 school and faculty meetings to promote the MODC project and raise awareness of the Library’s services and resources for research data management.

Constructing a traditional Chinese medicine data warehouse application

The explosive growth in the development of Traditional Chinese Medicine (TCM) has resulted in the continued increase in clinical and research data. The lack of standardised terminology, flaws in data quality planning and management of TCM informatics are preventing clinical decision-making, drug discovery and education. This paper argues that the introduction of data warehousing technologies to enhance the effectiveness and durability in TCM is paramount. To showcase the role of data warehousing in the improvement of TCM, this paper presents a practical model for data warehousing with detailed explanation, which is based on the structured electronic records, for TCM clinical researches and medical knowledge discovery.

Next Generation SHRM Research: From Covariation to Causation

[Excerpt] In response to the longstanding and repeated criticisms that HR does not add value to organizations, the past 10 years has seen a burgeoning of research attempting to demonstrate that progressive HR practices result in higher organizational performance. Huselid’s (1995)groundbreaking study demonstrated that a set of HR practices he referred to as High Performance Work Systems (HPWS) were related to accounting profits and market value of firms. Since then, a number of studies have shown similar positive relationships between HR practices and various measures of firm performance. While the studies comprising what I refer to as “first generation SHRM research” have added to what is becoming a more convincing body of evidence of the positive relationship between HR and performance, this body tends to lack sufficient data to demonstrate that the relationship is actually causal in the sense that HR practices, when instituted, lead to higher performance. This next generation of SHRM research will begin (and, in fact has begun) to focus on designing more rigorous tests of the hypothesis that employing progressive HRM systems actually results in higher organizational performance. This generation of research will focus on two aspects: demonstrating the HRM value chain, and proving causality as opposed to merely covariation.

Scientific Data Application Profile Scoping Study

This study was undertaken by UKOLN on behalf of the Joint Information Systems Committee (JISC) in the period April to September 2008. Application profiles are metadata schemata which consist of data elements drawn from one or more namespaces, optimized for a particular local application. They offer a way for particular communities to base the interoperability specifications they create and use for their digital material on established open standards. This offers the potential for digital materials to be accessed, used and curated effectively both within and beyond the communities in which they were created. The JISC recognized the need to undertake a scoping study to investigate metadata application profile requirements for scientific data in relation to digital repositories, and specifically concerning descriptive metadata to support resource discovery and other functions such as preservation. This followed on from the development of the Scholarly Works Application Profile (SWAP) undertaken within the JISC Digital Repositories Programme and led by Andy Powell (Eduserv Foundation) and Julie Allinson (RRT UKOLN) on behalf of the JISC. Aims and Objectives 1.To assess whether a single metadata AP for research data, or a small number thereof, would improve resource discovery or discovery-to-delivery in any useful or significant way. 2.If so, then to:a.assess whether the development of such AP(s) is practical and if so, how much effort it would take; b.scope a community uptake strategy that is likely to be successful, identifying the main barriers and key stakeholders. 3.Otherwise, to investigate how best to improve cross-discipline, cross-community discovery-to-delivery for research data, and make recommendations to the JISC and others as appropriate. Approach The Study used a broad conception of what constitutes scientific data, namely data gathered, collated, structured and analysed using a recognizably scientific method, with a bias towards quantitative methods. The approach taken was to map out the landscape of existing data centres, repositories and associated projects, and conduct a survey of the discovery-to-delivery metadata they use or have defined, alongside any insights they have gained from working with this metadata. This was followed up by a series of unstructured interviews, discussing use cases for a Scientific Data Application Profile, and how widely a single profile might be applied. On the latter point, matters of granularity, the experimental/measurement contrast, the quantitative/qualitative contrast, the raw/derived data contrast, and the homogeneous/heterogeneous data collection contrast were discussed. The Study report was loosely structured according to the Singapore Framework for Dublin Core Application Profiles, and in turn considered: the possible use cases for a Scientific Data Application Profile; existing domain models that could either be used or adapted for use within such a profile; and a comparison existing metadata profiles and standards to identify candidate elements for inclusion in the description set profile for scientific data. The report also considered how the application profile might be implemented, its relationship to other application profiles, the alternatives to constructing a Scientific Data Application Profile, the development effort required, and what could be done to encourage uptake in the community. The conclusions of the Study were validated through a reference group of stakeholders.

IPR POLICY AND SCIENTIFIC RESEARCH KNOWLEDGE EXCHANGE REPORT FOR SCIENTIFIC POLICY MAKERS

The report provides recommendations to policy makers in science and scholarly research regarding IPR policy to increase the impact of research and make the outcomes more available. The report argues that the impact of publicly-funded research outputs can be increased through a fairer balance between private and public interest in copyright legislation. This will allow for wider access to and easier re-use of published research reports. The common practice of authors being required to assign all rights to a publisher restricts the impact of research outputs and should be replaced by wider use of a non-exclusive licence. Full access and re-use rights to research data should be encouraged through use of a research-friendly licence.

Open Access Business Models for Research Funders and Universities

This briefing paper offers insight into various open access business models, from institutional to subject repositories, from open access journals to research data and monographs. This overview shows that there is a considerable variety in business models within a common framework of public funding. Open access through institutional repositories requires funding from particular institutions to set up and maintain a repository, while subject repositories often require contributions from a number of institutions or funding agencies to maintain a subject repository hosted at one institution. Open access through publication in open access journals generally requires a mix of funding sources to meet the cost of publishing. Public or charitable research funding bodies may contribute part of the cost of publishing in an open access journal but institutions also meet part of the cost, particularly when the author does not have a research grant from a research funding body

Jisc Briefing Document on Data Citations

Commissioned paper from Cameron Neylon (Curtin University) on citation practices for research data. Includes information on current (2016) global activity in the field, parallels with traditional citation, and recommendations.

Science incubators: synthesis centers and their role in the research ecosystem.

How should funding agencies enable researchers to explore high-risk but potentially high-reward science? One model that appears to work is the NSF-funded synthesis center, an incubator for community-led, innovative science.

Toward interoperable bioscience data.

To make full use of research data, the bioscience community needs to adopt technologies and reward mechanisms that support interoperability and promote the growth of an open 'data commoning' culture. Here we describe the prerequisites for data commoning and present an established and growing ecosystem of solutions using the shared 'Investigation-Study-Assay' framework to support that vision.

A model for analysing data portal performance: The biodiversity case

Currently, many museums, botanic gardens and herbariums keep data of biological collections and using computational tools researchers digitalize and provide access to their data using data portals. The replication of databases in portals can be accomplished through the use of protocols and data schema. However, the implementation of this solution demands a large amount of time, concerning both the transfer of fragments of data and processing data within the portal. With the growth of data digitalization in institutions, this scenario tends to be increasingly exacerbated, making it hard to maintain the records updated on the portals. As an original contribution, this research proposes analysing the data replication process to evaluate the performance of portals. The Inter-American Biodiversity Information Network (IABIN) biodiversity data portal of pollinators was used as a study case, which supports both situations: conventional data replication of records of specimen occurrences and interactions between them. With the results of this research, it is possible to simulate a situation before its implementation, thus predicting the performance of replication operations. Additionally, these results may contribute to future improvements to this process, in order to decrease the time required to make the data available in portals. © Rinton Press.

Effectiveness of integrated psychological therapy (IPT) for schizophrenia patients: a research update

Standardized recovery criteria go beyond symptom remission and put special emphasis on personal and social functioning in residence, work, and leisure. Against this background, evidence-based integrated approaches combining cognitive remediation with social skills therapy show promise for improving functional recovery of schizophrenia patients. Over the past 30 years, research groups in 12 countries have evaluated integrated psychological therapy (IPT) in 36 independent studies. IPT is a group therapy program for schizophrenia patients. It combines neurocognitive and social cognitive interventions with social skills and problem-solving approaches. The aim of the present study was to update and integrate the growing amount of research data on the effectiveness of IPT. We quantitatively reviewed the results of these 36 studies, including 1601 schizophrenia patients, by means of a meta-analytic procedure. Patients undergoing IPT showed significantly greater improvement in all outcome variables (neurocognition, social cognition, psychosocial functioning, and negative symptoms) than those in the control groups (placebo-attention conditions and standard care). IPT patients maintained their mean positive effects during an average follow-up period of 8.1 months. They showed better effects on distal outcome measures when all 5 subprograms were integrated. This analysis summarizes the broad empirical evidence indicating that IPT is an effective rehabilitation approach for schizophrenia patients and is robust across a wide range of sample characteristics as well as treatment conditions. Moreover, the cognitive and social subprograms of IPT may work in a synergistic manner, thereby enhancing the transfer of therapy effects over time and improving functional recovery.