scholarly journals The Tao of Open Science for Ecology

2014 ◽  
Author(s):  
Stephanie E Hampton ◽  
Sean Anderson ◽  
Sarah C Bagby ◽  
Corinna Gries ◽  
Xueying Han ◽  
...  
Keyword(s):  
Research Process ◽  
Open Science ◽  
Open Approach ◽  
Barriers To Entry ◽  
Management Planning ◽  
Constructive Feedback ◽  
Data Life Cycle ◽  
Data Stewardship ◽  
The Many ◽  
Access To Data

The field of ecology is poised to take advantage of emerging technologies that facilitate the gathering, analyzing, and sharing of data, methods, and results. The concept of transparency at all stages of the research process, coupled with free and open access to data, code, and papers, constitutes "open science." Despite the many benefits of an open approach to science, a number of barriers to entry exist that may prevent researchers from embracing openness in their own work. Here we describe several key shifts in mindset that underpin the transition to more open science. These shifts in mindset include thinking about data stewardship rather than data ownership, embracing transparency throughout the data life-cycle and project duration, and accepting critique in public. Though foreign and perhaps frightening at first, these changes in thinking stand to benefit the field of ecology by fostering collegiality and broadening access to data and findings. We present an overview of tools and best practices that can enable these shifts in mindset at each stage of the research process, including tools to support data management planning and reproducible analyses, strategies for soliciting constructive feedback throughout the research process, and methods of broadening access to final research products.

scholarly journals The Tao of Open Science for Ecology

2014 ◽  
Author(s):  
Stephanie E Hampton ◽  
Sean Anderson ◽  
Sarah C Bagby ◽  
Corinna Gries ◽  
Xueying Han ◽  
...  
Keyword(s):  
Research Process ◽  
Open Science ◽  
Open Approach ◽  
Barriers To Entry ◽  
Management Planning ◽  
Constructive Feedback ◽  
Data Life Cycle ◽  
Data Stewardship ◽  
The Many ◽  
Access To Data

The field of ecology is poised to take advantage of emerging technologies that facilitate the gathering, analyzing, and sharing of data, methods, and results. The concept of transparency at all stages of the research process, coupled with free and open access to data, code, and papers, constitutes "open science." Despite the many benefits of an open approach to science, a number of barriers to entry exist that may prevent researchers from embracing openness in their own work. Here we describe several key shifts in mindset that underpin the transition to more open science. These shifts in mindset include thinking about data stewardship rather than data ownership, embracing transparency throughout the data life-cycle and project duration, and accepting critique in public. Though foreign and perhaps frightening at first, these changes in thinking stand to benefit the field of ecology by fostering collegiality and broadening access to data and findings. We present an overview of tools and best practices that can enable these shifts in mindset at each stage of the research process, including tools to support data management planning and reproducible analyses, strategies for soliciting constructive feedback throughout the research process, and methods of broadening access to final research products.

scholarly journals Open Science in Archaeology

2017 ◽  
Author(s):  
Ben Marwick
Keyword(s):  
Public Involvement ◽  
Research Process ◽  
Open Science ◽  
Great Effort ◽  
Journal Articles ◽  
Rigorous Analysis ◽  
Science Practices ◽  
Analysis Process ◽  
Data Stewardship ◽  
Lengthy Process

In archaeology, we are accustomed to investing great effort into collecting data from fieldwork, museum collections, and other sources, followed by detailed description, rigorous analysis, and in many cases ending with publication of our findings in short, highly concentrated reports or journal articles. Very often, these publications are all that is visible of this lengthy process, and even then, most of our journal articles are only accessible to scholars at institutions paying subscription fees to the journal publishers. While this traditional model of the archaeological research process has long been effective at generating new knowledge about our past, it is increasingly at odds with current norms of practice in other sciences. Often described as ‘open science’, these new norms include data stewardship instead of data ownership, transparency in the analysis process instead of secrecy, and public involvement instead of exclusion. While the concept of open science is not new in archaeology (e.g., see Lake 2012 and other papers in that volume), a less transparent model often prevails, unfortunately. We believe that there is much to be gained, both for individual researchers and for the discipline, from broader application of open science practices. In this article, we very briefly describe these practices and their benefits to researchers. We introduce the Society of American Archaeology’s Open Science Interest Group (OSIG) as a community to help archaeologists engage in and benefit from open science practices, and describe how it will facilitate the adoption of open science in archaeology.

scholarly journals Data Curator’s Roles and Responsibilities: An International Perspective

Libri ◽  
2019 ◽  
Vol 69 (2) ◽  
pp. 89-104 ◽  
Author(s):  
Anna Maria Tammaro ◽  
Krystyna K. Matusiak ◽  
Frank Andreas Sposito ◽  
Vittore Casarosa
Keyword(s):  
Literature Review ◽  
Research Process ◽  
Open Science ◽  
International Perspective ◽  
Research Data ◽  
Data Curation ◽  
Roles And Responsibilities ◽  
Data Intensive ◽  
Data Life Cycle

Abstract The data-intensive research environment and the movement towards open science create demand for information professionals with knowledge of the research process and skills in managing and curating data. This paper is reporting the findings from a multiyear study entitled “Data curator: who is s/he?” initiated by the Library Theory and Research (LTR) Section of the International Federation of Library Associations (IFLA). The study aimed to identify the roles and responsibilities of data curators around the world and also focused on the terminology used to describe the new professional roles. The following questions were posed: R1: How is data curation defined by practitioners / professional working in the field? R2: What terms are used to describe the roles for professionals in data curation area? R3: What are primary roles and responsibilities of data curators? R4: What are educational qualifications and competencies required of data curators? To answer the research questions, the research team performed a comprehensive literature review and vocabulary analysis and conducted an empirical study using mixed-methods design. The study consisted of three stages: 1. Literature review and vocabulary analysis 2. Content analysis of position announcements 3. Interviews with professionals working in data curation and research data management- Findings confirm the results from previous research about the lack of common terminology and a variability of the position titles. The concept of data lifecycle highlighted the important role of data curators. However this study also found that many positions in practice were held by non library professionals. The findings indicate that data curation is an evolving sociotechnical practice that involves not only technical systems and services structured around research data life cycle but also a range of social activities around community building.

scholarly journals Drawing Reproducible Conclusions from Observational Clinical Data with OHDSI

2021 ◽  
Author(s):  
George Hripcsak ◽  
Martijn J. Schuemie ◽  
David Madigan ◽  
Patrick B. Ryan ◽  
Marc A. Suchard
Keyword(s):  
Large Scale ◽  
Open Science ◽  
Positive Control ◽  
Research Literature ◽  
Observational Research ◽  
Common Data Model ◽  
Administrative Claims ◽  
Open Approach ◽  
Operating Characteristics ◽  
Software Models

Summary Objective: The current observational research literature shows extensive publication bias and contradiction. The Observational Health Data Sciences and Informatics (OHDSI) initiative seeks to improve research reproducibility through open science. Methods: OHDSI has created an international federated data source of electronic health records and administrative claims that covers nearly 10% of the world’s population. Using a common data model with a practical schema and extensive vocabulary mappings, data from around the world follow the identical format. OHDSI’s research methods emphasize reproducibility, with a large-scale approach to addressing confounding using propensity score adjustment with extensive diagnostics; negative and positive control hypotheses to test for residual systematic error; a variety of data sources to assess consistency and generalizability; a completely open approach including protocol, software, models, parameters, and raw results so that studies can be externally verified; and the study of many hypotheses in parallel so that the operating characteristics of the methods can be assessed. Results: OHDSI has already produced findings in areas like hypertension treatment that are being incorporated into practice, and it has produced rigorous studies of COVID-19 that have aided government agencies in their treatment decisions, that have characterized the disease extensively, that have estimated the comparative effects of treatments, and that the predict likelihood of advancing to serious complications. Conclusions: OHDSI practices open science and incorporates a series of methods to address reproducibility. It has produced important results in several areas, including hypertension therapy and COVID-19 research.

scholarly journals German Reproducibility Network - a new platform for Open Science in Germany

2021 ◽  
Author(s):  
Bernadette Fritzsch ◽  
Daniel Nüst
Keyword(s):  
Local Level ◽  
Scientific Work ◽  
Research Process ◽  
Open Science ◽  
Further Education ◽  
Early Career ◽  
Reproducible Research ◽  
Small Scale ◽  
Research Software

<p>Open Science has established itself as a movement across all scientific disciplines in recent years. It supports good practices in science and research that lead to more robust, comprehensible, and reusable results. The aim is to improve the transparency and quality of scientific results so that more trust is achieved, both in the sciences themselves and in society. Transparency requires that uncertainties and assumptions are made explicit and disclosed openly. <br>Currently, the Open Science movement is largely driven by grassroots initiatives and small scale projects. We discuss some examples that have taken on different facets of the topic:</p><ul><li>The software developed and used in the research process is playing an increasingly important role. The Research Software Engineers (RSE) communities have therefore organized themselves in national and international initiatives to increase the quality of research software.</li> <li>Evaluating reproducibility of scientific articles as part of peer review requires proper creditation and incentives for both authors and specialised reviewers to spend extra efforts to facilitate workflow execution. The Reproducible AGILE initiative has established a reproducibility review at a major community conference in GIScience.</li> <li>Technological advances for more reproducible scholarly communication beyond PDFs, such as containerisation, exist, but are often inaccessible to domain experts who are not programmers. Targeting geoscience and geography, the project Opening Reproducible Research (o2r) develops infrastructure to support publication of research compendia, which capture data, software (incl. execution environment), text, and interactive figures and maps.</li> </ul><p>At the core of scientific work lie replicability and reproducibility. Even if different scientific communities use these terms differently, the recognition that these aspects need more attention is commonly shared and individual communities can learn a lot from each other. Networking is therefore of great importance. The newly founded initiative German Reproducibility Network (GRN) wants to be a platform for such networking and targets all of the above initiatives. GRN is embedded in a growing network of similar initiatives, e.g. in the UK, Switzerland and Australia. Its goals include </p><ul><li>Support of local open science groups</li> <li>Connecting local or topic-centered initiatives for the exchange of experiences</li> <li>Attracting facilities for the goals of Open Science </li> <li>Cultivate contacts to funding organizations, publishers and other actors in the scientific landscape</li> </ul><p>In particular, the GRN aims to promote the dissemination of best practices through various formats of further education, in order to sensitize particularly early career researchers to the topic. By providing a platform for networking, local and domain-specific groups should be able to learn from one another, strengthen one another, and shape policies at a local level.</p><p>We present the GRN in order to address the existing local initiatives and to win them for membership in the GRN or sibling networks in other countries.</p>

scholarly journals Putting open science into practice: A social dilemma?

First Monday ◽  
2014 ◽  
Author(s):  
Kaja Scheliga ◽  
Sascha Friesike
Keyword(s):  
Scientific Community ◽  
Social Dilemma ◽  
Digital Technologies ◽  
Research Process ◽  
Open Science ◽  
Best Interest ◽  
Research Practices ◽  
Individual Scientist ◽  
The Individual ◽  
Opening Up

Digital technologies carry the promise of transforming science and opening up the research process. We interviewed researchers from a variety of backgrounds about their attitudes towards and experiences with openness in their research practices. We observe a considerable discrepancy between the concept of open science and scholarly reality. While many researchers support open science in theory, the individual researcher is confronted with various difficulties when putting open science into practice. We analyse the major obstacles to open science and group them into two main categories: individual obstacles and systemic obstacles. We argue that the phenomenon of open science can be seen through the prism of a social dilemma: what is in the collective best interest of the scientific community is not necessarily in the best interest of the individual scientist. We discuss the possibilities of transferring theoretical solutions to social dilemma problems to the realm of open science.

A Community Perspective on Research Software in the Hydrological Sciences 

2021 ◽  
Author(s):  
Robert Reinecke ◽  
Tim Trautmann ◽  
Thorsten Wagener ◽  
Katja Schüler
Keyword(s):  
Software Development ◽  
Scientific Progress ◽  
Open Science ◽  
Computer Engineering ◽  
Knowledge Community ◽  
Research Software ◽  
Software Engineering Process ◽  
First Results ◽  
Long Time ◽  
Access To Data

<div> <p>Software development has become an integral part of the earth system sciences as models and data processing get more sophisticated. Paradoxically, it poses a threat to scientific progress as the pillar of science, reproducibility, is seldomly reached. Software code tends to be either poorly written and documented or not shared at all; proper software licenses are rarely attributed. This is especially worrisome as scientific results have potential controversial implications for stakeholders and policymakers and may influence the public opinion for a long time. </p> </div><div> <p>In recent years, progress towards open science has led to more publishers demanding access to data and source code alongside peer-reviewed manuscripts. Still, recent studies find that results in hydrology can rarely be reproduced. </p> </div><div> <p>In this talk, we present first results of a poll conducted in spring 2021 among the hydrological science community. Therein, we strive to investigate the causes for that lack of reproducibility. We take a peek behind the curtain and unveil how the community develops and maintains complex code and what that entails for reproducibility. Our survey includes background knowledge, community opinion, and behaviour practices regarding reproducible software development.  </p> </div><div> <p>We postulate that this lack of reproducibility might be rooted in insufficient reward within the scientific community, insecurity regarding proper licencing of software and other parts of the research compendium as well as scientists’ unawareness about how to make software available in a way that allows for proper attribution of their work. We question putative causes such as unclear guidelines of research institutions or that software has been developed over decades by researchers' cohorts without a proper software engineering process and transparent licensing. </p> </div><div> <p>To this end, we also summarize solutions like the adaption of modern project management methods from the computer engineering community that will eventually reduce costs while increasing the reproducibility of scientific research. </p> </div>

Open Science and Its Impact on Libraries, Publishers, and Authors

2020 ◽  
pp. 97-108
Author(s):  
Josiline Phiri Chigwada
Keyword(s):  
Information Sources ◽  
Research Output ◽  
Research Process ◽  
Open Science ◽  
The Body ◽  
Digital Era ◽  
Body Of Knowledge ◽  
Structured Document ◽  
Science Movement

The open science movement enables the accessibility and reusability of research output across the globe. Researchers and other stakeholders in the research process can now easily collaborate to add to the body of knowledge. This chapter documents how open science is impacting the role of libraries, publishers, and authors in the digital era. A structured document analysis and web analysis were done to find out how authors, publishers, and librarians are affected by open science. It was found that librarians are taking advantage of open science to provide various information sources to patrons, the publishers are now charging article processing fees to make the journal articles open access upon publishing, and authors are now able to access many information sources during the research process and enjoy greater visibility of their research output. The author recommends the adoption of open science especially in the developing countries and the enactment of policies that support open science at national, regional, and international levels.

Thinking About Data With Grounded Theory

2018 ◽  
Vol 25 (8) ◽  
pp. 743-753 ◽  
Author(s):  
Kathy Charmaz ◽  
Linda Liska Belgrave
Keyword(s):  
Qualitative Research ◽  
Grounded Theory ◽  
Qualitative Data ◽  
Research Process ◽  
Individual Responsibility ◽  
Research Participants ◽  
Self Sufficiency ◽  
Access To Data ◽  
Deductive Research

This article examines qualitative data in an era of neoliberalism and focuses on the place of data in grounded theory studies. Neoliberal values of individual responsibility, self-sufficiency, competition, efficiency, and profit have entered the conduct of research. Neoliberalism fosters (a) reifying quantitative logical-deductive research, (b) imposing surveillance of types and sources of data, (c) marginalizing inductive qualitative research, and (d) limiting access to data in grounded theory studies. Grounded theory relies on data and resists current efforts to abandon data. The method resides in the space between reifying and rejecting data. Data allow us to learn from the stories of those left out and permits research participants to break silences. Data can help us look underneath and beyond our privileges, and alter our views. Grounded theory is predicated on data, but how researchers regard and render data depends on which version of the method they adopt. We propose developing a strong methodological self-consciousness to learn how we affect the research process and to counter the subtle effects of neoliberalism.

scholarly journals Open-access policy and data-sharing practice in UK academia

2019 ◽  
Vol 46 (1) ◽  
pp. 41-52 ◽  
Author(s):  
Yimei Zhu
Keyword(s):  
Open Access ◽  
Data Sharing ◽  
Secondary Data ◽  
Open Science ◽  
Research Data ◽  
Academic Disciplines ◽  
Free Access ◽  
Online Publishing ◽  
Institutional Repositories ◽  
Access To Data

Data sharing can be defined as the release of research data that can be used by others. With the recent open-science movement, there has been a call for free access to data, tools and methods in academia. In recent years, subject-based and institutional repositories and data centres have emerged along with online publishing. Many scientific records, including published articles and data, have been made available via new platforms. In the United Kingdom, most major research funders had a data policy and require researchers to include a ‘data-sharing plan’ when applying for funding. However, there are a number of barriers to the full-scale adoption of data sharing. Those barriers are not only technical, but also psychological and social. A survey was conducted with over 1800 UK-based academics to explore the extent of support of data sharing and the characteristics and factors associated with data-sharing practice. It found that while most academics recognised the importance of sharing research data, most of them had never shared or reused research data. There were differences in the extent of data sharing between different gender, academic disciplines, age and seniority. It also found that the awareness of Research Council UK’s (RCUK) Open-Access (OA) policy, experience of Gold and Green OA publishing, attitudes towards the importance of data sharing and experience of using secondary data were associated with the practice of data sharing. A small group of researchers used social media such as Twitter, blogs and Facebook to promote the research data they had shared online. Our findings contribute to the knowledge and understanding of open science and offer recommendations to academic institutions, journals and funding agencies.

Sign in / Sign up

Export Citation Format

Share Document