Open Science时代灰预测视阈下图书馆服务CLSOS平台模型构建

通过分析Open Science已有研究成果(特别是欧盟研究成果),Open Science的由来、涵义,图书馆服务发展历程以及其在灰预测视阈下的发展趋势,建立了基于我国图书馆服务的CLSOS平台模型。Open Science时代我国图书馆服务遵循基于顶层设计、开放的科学资源、开放的科学研究、开放的科学传播、实践-反馈良性循环上升运动五大步骤的CLSOS平台模型发展,有助于我国Open Science能力实现跨越式发展。

The Roles of Female Involvement and Risk Aversion in Open Access Publishing Patterns in Vietnamese Social Sciences and Humanities

Purpose:The open-access(OA)publishing model can help improve researchers’outreach,thanks to its accessibility and visibility to the public.Therefore,the presentation of female researchers can benefit from the O A publishing model.Despite that,little is known about how gender affects OA practices.Thus,the current study explores the effects of female involvement and risk aversion on OA publishing patterns among Vietname se social sciences and humanities.Design/methodology/approach:The study employed Bayesian Mindsponge Framework(BMF)on a dataset of 3,122 Vietnamese social sciences and humanities(SS&H)publications during 2008-2019.The Mindsponge mechanism was specifically used to construct theoretical models,while Bayesian inference was utilized for fitting models.Findings:The result showed a positive association between female participation and OA publishing probability.However,the positive effect of female involvement on OA publishing probability was negated by the high ratio of female researchers in a publication.OA status was negatively associated with the JIF of the journal in which the publication was published,but the relationship was moderated by the involvement of a female researcher(s).The findings suggested that Vietnamese female researchers might be more likely to publish under the OA model in journals with high JIF for avoiding the risk of public criticism.Research limitations:The study could only provide evidence on the association between female involvement and OA publishing probability.However,whether to publish under OA terms is often determined by the first or corresponding authors,but not necessarily gender-based.Practical implications:Systematically coordinated actions are suggested to better support women and promote the OA movement in Vietnam.Originality/value:The findings show the OA publishing patterns of female researchers in Vietnamese SS&H.

Open Science时代图书馆的角色定位与发展路径

文章在简要分析Open Science时代图书馆面临的严峻挑战的基础上,从开放科学的倡导者、科学研究的协作者和知识权益的规范者三方面对图书馆角色进行了重新定位,并提出实现全新角色定位的关键因素是资源、人才和用户,最后对图书馆的发展路径做了深入探讨。

Research foresight in bridging open science and open innovation:Overview based on the complex thinking paradigm

Open innovation benefits from access to cutting-edge discoveries to increase their transformation into tangible applications for the benefit of society.Improving research quality has been proposed as a primary objective of open science by the United Nations,to increase science reproducibility,impact,and trust,leading to robust decision-making and policies.However,opening access to data and processes is insufficient for researchers to achieve open innovation in the context of globalization,for example,by gathering insights from external and internal sources.Developing the appropriate mindset to manage complexity and generate synergy among researchers in academia,industry,and the government is essential to catalyze knowledge and transform it into relevant innovations for society.To gain insights into the roles and challenges of researchers aiming to bridge the gap between open science and open innovation,a decade-plus Mapping Literature Review was conducted based on the complex thinking paradigm.Complex thinking allows for novel connections of the information collected through open science and open innovation,considering different forms of engaging with alternative means of knowledge creation that may promote innovative and critical thinking.The findings revealed:a)broad positioning of the terms in the European Union;b)open access and open data as current driving themes;c)a constant trade-off between the terms“open data”and“information protection”;d)lack of studies on researchers’complex thinking to help them manage openness;e)absence of the environmental helix in the initiatives;and(f)challenges in innovative communication and collaborative practices among public and private entities.Overall,we identified an opportunity to develop researchers’complex thinking such that the openness of information becomes a shared responsibility among partners across multiple helices.This shared responsibility can have methodological implications that permeate how open science and open innovation are theorized and,in practice,facilitate the development of fundamental collaborative research procedures.

Contribution of the Open Access Modality to the Impact of Hybrid Journals Controlling by Field and Time Effects

Purpose:Researchers are more likely to read and cite papers to which they have access than those that they cannot obtain.Thus,the objective of this work is to analyze the contribution of the Open Access(OA)modality to the impact of hybrid journals.Design/methodology/approach:The“research articles”in the year 2017 from 200 hybrid journals in four subject areas,and the citations received by such articles in the period 2017-2020 in the Scopus database,were analyzed.The hybrid OA papers were compared with the paywalled ones.The journals were randomly selected from those with share of OA papers higher than some minimal value.More than 60 thousand research articles were analyzed in the sample,of which 24%under the OA modality.Findings:We obtain at journal level that cites per article in both hybrid modalities(OA and paywalled)strongly correlate.However,there is no correlation between the OA prevalence and cites per article.There is OA citation advantage in 80%of hybrid journals.Moreover,the OA citation advantage is consistent across fields and held in time.We obtain an OA citation advantage of 50%in average,and higher than 37%in half of the hybrid journals.Finally,the OA citation advantage is higher in Humanities than in Science and Social Science.Research limitations:Some of the citation advantage is likely due to more access allows more people to read and hence cite articles they otherwise would not.However,causation is difficult to establish and there are many possible bias.Several factors can affect the observed differences in citation rates.Funder mandates can be one of them.Funders are likely to have OA requirement,and well-funded studies are more likely to receive more citations than poorly funded studies.Another discussed factor is the selection bias postulate,which suggests that authors choose only their most impactful studies to be open access.Practical implications:For hybrid journals,the open access modality is positive,in the sense that it provides a greater number of potential readers.This in turn translates into a greater number of citations and an improvement in the position of the journal in the rankings by impact factor.For researchers it is also positive because it increases the potential number of readers and citations received.Originality/value:Our study refines previous results by comparing documents more similar to each other.Although it does not examine the cause of the observed citation advantage,we find that it exists in a very large sample.

Open Peer Review in Scientific Publishing: A Web Mining Study of Peer J Authors and Reviewers

Purpose: To understand how authors and reviewers are accepting and embracing Open Peer Review(OPR), one of the newest innovations in the Open Science movement.Design/methodology/approach: This research collected and analyzed data from the Open Access journal Peer J over its first three years(2013–2016). Web data were scraped, cleaned, and structured using several Web tools and programs. The structured data were imported into a relational database. Data analyses were conducted using analytical tools as well as programs developed by the researchers.Findings: Peer J, which supports optional OPR, has a broad international representation of authors and referees. Approximately 73.89% of articles provide full review histories. Of the articles with published review histories, 17.61% had identities of all reviewers and 52.57% had at least one signed reviewer. In total, 43.23% of all reviews were signed. The observed proportions of signed reviews have been relatively stable over the period since the Journal’s inception.Research limitations: This research is constrained by the availability of the peer review history data. Some peer reviews were not available when the authors opted out of publishing their review histories. The anonymity of reviewers made it impossible to give an accurate count of reviewers who contributed to the review process. Practical implications: These findings shed light on the current characteristics of OPR. Given the policy that authors are encouraged to make their articles’ review history public and referees are encouraged to sign their review reports, the three years of Peer J review data demonstrate that there is still some reluctance by authors to make their reviews public and by reviewers to identify themselves. Originality/value: This is the first study to closely examine Peer J as an example of an OPR model journal. As Open Science moves further towards open research, OPR is a final and critical component. Research in this area must identify the best policies and paths towards a transparent and open peer review process for scientific communication.

Research e-infrastructures for open science: The national example of CSTCloud in China

This paper focuses on research e-infrastructures in the open science era.We analyze some of the challenges and opportunities of cloud-based science and introduce an example of a national solution in the China Science and Technology Cloud(CSTCloud).We selected three CSTCloud use cases in deploying open science modules,including scalable engineering in astronomical data management,integrated Earth-science resources for SDG-13 decision making,and the coupling of citizen science and artificial intelligence(AI)techniques in biodiversity.We conclude with a forecast on the future development of research e-infrastructures and introduce the idea of the Global Open Science Cloud(GOSC).We hope this analysis can provide some insights into the future development of research e-infrastructures in support of open science.

Research Data Management Implementation at Peking University Library:Foster and Promote Open Science and Open Data

Research Data Management(RDM)has become increasingly important for more and more academic institutions.Using the Peking University Open Research Data Repository(PKU-ORDR)project as an example,this paper will review a library-based university-wide open research data repository project and related RDM services implementation process including project kickoff,needs assessment,partnerships establishment,software investigation and selection,software customization,as well as data curation services and training.Through the review,some issues revealed during the stages of the implementation process are also discussed and addressed in the paper such as awareness of research data,demands from data providers and users,data policies and requirements from home institution,requirements from funding agencies and publishers,the collaboration between administrative units and libraries,and concerns from data providers and users.The significance of the study is that the paper shows an example of creating an Open Data repository and RDM services for other Chinese academic libraries planning to implement their RDM services for their home institutions.The authors of the paper have also observed since the PKU-ORDR and RDM services implemented in 2015,the Peking University Library(PKUL)has helped numerous researchers to support the entire research life cycle and enhanced Open Science(OS)practices on campus,as well as impacted the national OS movement in China through various national events and activities hosted by the PKUL.

Sentence,Phrase,and Triple Annotations to Build a Knowledge Graph of Natural Language Processing Contributions—A Trial Dataset

Purpose:This work aims to normalize the NLPCONTRIBUTIONS scheme(henceforward,NLPCONTRIBUTIONGRAPH)to structure,directly from article sentences,the contributions information in Natural Language Processing(NLP)scholarly articles via a two-stage annotation methodology:1)pilot stage-to define the scheme(described in prior work);and 2)adjudication stage-to normalize the graphing model(the focus of this paper).Design/methodology/approach:We re-annotate,a second time,the contributions-pertinent information across 50 prior-annotated NLP scholarly articles in terms of a data pipeline comprising:contribution-centered sentences,phrases,and triple statements.To this end,specifically,care was taken in the adjudication annotation stage to reduce annotation noise while formulating the guidelines for our proposed novel NLP contributions structuring and graphing scheme.Findings:The application of NLPCONTRIBUTIONGRAPH on the 50 articles resulted finally in a dataset of 900 contribution-focused sentences,4,702 contribution-information-centered phrases,and 2,980 surface-structured triples.The intra-annotation agreement between the first and second stages,in terms of F1-score,was 67.92%for sentences,41.82%for phrases,and 22.31%for triple statements indicating that with increased granularity of the information,the annotation decision variance is greater.Research limitations:NLPCONTRIBUTIONGRAPH has limited scope for structuring scholarly contributions compared with STEM(Science,Technology,Engineering,and Medicine)scholarly knowledge at large.Further,the annotation scheme in this work is designed by only an intra-annotator consensus-a single annotator first annotated the data to propose the initial scheme,following which,the same annotator reannotated the data to normalize the annotations in an adjudication stage.However,the expected goal of this work is to achieve a standardized retrospective model of capturing NLP contributions from scholarly articles.This would entail a larger initiative of enlisting multiple annotators to accommodate different worldviews into a“single”set of structures and relationships as the final scheme.Given that the initial scheme is first proposed and the complexity of the annotation task in the realistic timeframe,our intraannotation procedure is well-suited.Nevertheless,the model proposed in this work is presently limited since it does not incorporate multiple annotator worldviews.This is planned as future work to produce a robust model.Practical implications:We demonstrate NLPCONTRIBUTIONGRAPH data integrated into the Open Research Knowledge Graph(ORKG),a next-generation KG-based digital library with intelligent computations enabled over structured scholarly knowledge,as a viable aid to assist researchers in their day-to-day tasks.Originality/value:NLPCONTRIBUTIONGRAPH is a novel scheme to annotate research contributions from NLP articles and integrate them in a knowledge graph,which to the best of our knowledge does not exist in the community.Furthermore,our quantitative evaluations over the two-stage annotation tasks offer insights into task difficulty.

Open Science and the Hype Cycle

The introduction of a new technology or innovation is often accompanied by“ups and downs”in its fortunes.Gartner Inc.defined a so-called hype cycle to describe a general pattern that many innovations experience:technology trigger,peak of inflated expectations,trough of disillusionment,slope of enlightenment,and plateau of productivity.This article will compare the ongoing introduction of Open Science(OS)with the hype cycle model and speculate on the relevance of that model to OS.Lest the title of this article mislead the reader,be assured that the author believes that OS should happen and that it will happen.However,I also believe that the path to OS will be longer than many of us had hoped.I will give a brief history of the today’s“semi-open”science,define what I mean by OS,define the hype cycle and where OS is now on that cycle,and finally speculate what it will take to traverse the cycle and rise to its plateau of productivity(as described by Gartner).

EU-Citizen.Science:A Platform for Mainstreaming Citizen Science and Open Science in Europe

Citizen Science(CS)is a prominent field of application for Open Science(OS),and the two have strong synergies,such as:advocating for the data and metadata generated through science to be made publicly available[1];supporting more equitable collaboration between different types of scientists and citizens;and facilitating knowledge transfer to a wider range of audiences[2].While primarily targeted at CS,the EU-Citizen.Science platform can also support OS.One of its key functions is to act as a knowledge hub to aggregate,disseminate and promote experience and know-how;for example,by profiling CS projects and collecting tools,resources and training materials relevant to both fields.To do this,the platform has developed an information architecture that incorporates the public participation in scientific research(PPSR)-Common Conceptual Model.This model consists of the Project Metadata Model,the Dataset Metadata Model and the Observation Data Model,which were specifically developed for CS initiatives.By implementing these,the platform will strengthen the interoperating arrangements that exist between other,similar platforms(e.g.,BioCollect and SciStarter)to ensure that CS and OS continue to grow globally in terms of participants,impact and fields of application.

Semantics all the way down:the Semantic Web and open science in big earth data

Semantic technologies have emerged as a prominent research area within Big Earth Data.These technologies have provided significant benefits for data discovery and integration.Yet,the formality of the Semantic Web,in languages such as the Web Ontology Language(OWL),does not always integrate well with the numerical,statistical,and geometric methods of the geosciences.Two prominent challenges in this area are how to semantically model individual measurements and what to do when geoscience needs are not addressed by languages such as OWL.This has led to a fragmented Big Earth Data community with either no solution or incompatible semantic solutions.We use an oceanographic example to highlight the limitations and challenges surrounding the semantic encoding of observations and the use of semantics during analysis.We then present potential solutions to each challenge showing that a full end-to-end application of semantic technologies is not only feasible,but beneficial to Big Earth Data.

Politics and Open Science:How the European Open Science Cloud Became Reality (the Untold Story)

This article will document how the European Open Science Cloud(EOSC)emerged as one of the key policy intentions to foster Open Science(OS)in Europe.It will describe some of the typical,non-rational roadblocks on the way to implement EOSC.The article will also argue that the only way Europe can take care of its research data in a way that fits the European specificities fully,is by supporting EOSC.

Developing Open RDI and Education in Finnish Universities of Applied Sciences

Open Science(OS)and Research has reached mixed maturity levels in Finland.The meaning of the national project in the ecosystem of Finnish universities of applied sciences(UAS)is to enhance and elaborate OS and Open Education(OE)activities.Future actions were defined based on a survey and interviews carried out in the Finnish UAS sector during 2018 and 2019.The aim of both data collections was to evaluate the current status and attitudes towards open Research,Development,and Innovation(RDI)among staff members.Another purpose was to define the need for internal support services concerning open RDI and OE and to identify knowledge gaps.The results revealed several gaps in understanding OS and OE initiatives.Real-life actions were mostly vague,and the respondents experienced the need for support.On the other hand,the attitudes towards open RDI were positive,and the issue aroused questions and reflections.This study revealed gaps in knowledge and actions in Finnish UAS sectors.These results have been the basis of development actions such as joint workshops,educational webinars,and common instructions.The future plan includes the establishment of an experts’network for supporting open RDI and Education.

About Open Science and Autonomy of Science

This article invites us to a concise walk through the past,offering insights defined by the major challenges science encountered during the centuries.Some lessons for today and tomorrow are enumerated in the three sections of the article,and they go beyond the relatively few perspectives offered by today’s Data Science:Open Science(OS)is what has always happened and is nothing new,because science has always sought to be open.Esthetical values played a relevant role in the past.Former scientists recognized the intrinsic relation between the way they opened science and the way they followed the principles of beauty and the sense of esthetic.Their groundbreaking heritage still inspires us in being ready to open new ways in science.Whereas Latin was the original lingua franca of European science,and English is the recent lingua franca,the new lingua franca is software.Pieces of software are the filter,which connect researchers to the world,through layers of data.They assist in observing,in choosing,and in selecting.Open scientists should be aware of the fact that their autonomy in science depends on the quality of these pieces.Another lesson is that ethics-regarded as a source of innovative activities-must be a core component of innovative processes in OS,because society needs a responsible use of data and algorithms in corresponding practices that serve OS.

Implementation of an Open Science Instruction Program for Undergraduates

The scientific,social,and economic advantages that accrue from Open Science(OS)practices-ways of doing research that emphasize reproducibility,transparency,and accessibility at all stages of the research cycle-are now widely recognized in nations around the world and by international bodies such as the United Nations and the Organization for Economic Cooperation and Development.However,program wide or coordinated instruction of undergraduate students in OS practices remains uncommon.At the University of British Columbia in Canada,we have started to develop a comprehensive undergraduate OS program that can be adapted to and woven into diverse subject curricula.We report on the context and planning of the pilot module of the program,“Open Science 101”,its implementation in first-year Biology in Fall 2019,and qualitative results of an attitudinal survey of students following their course.

Open life science research,open software and the open century

At the age of knowledge explosion and mass scientific information,I highlighted the importance of conducting open science in life and medical researches through the extensive usage of open software and documents.The proposal of conducting open science is to reduce the limited repeatability of researches in life science.I outlined the essential steps for conducting open life science and the necessary standards for creating,reusing and reproducing open materials.Different Creative Commons licenses were presented and compared of their usage scope and restriction.As a conclusion,I argued that open materials should be widely adopted in doing life and medical researches.

Open Science and Data Science

Data Science(DS)as defined by Jim Gray is an emerging paradigm in all research areas to help finding non-obvious patterns of relevance in large distributed data collections.“Open Science by Design”(OSD),i.e.,making artefacts such as data,metadata,models,and algorithms available and re-usable to peers and beyond as early as possible,is a pre-requisite for a flourishing DS landscape.However,a few major aspects can be identified hampering a fast transition:(1)The classical“Open Science by Publication”(OSP)is not sufficient any longer since it serves different functions,leads to non-acceptable delays and is associated with high curation costs.Changing data lab practices towards OSD requires more fundamental changes than OSP.(2)The classical publication-oriented models for metrics,mainly informed by citations,will not work anymore since the roles of contributors are more difficult to assess and will often change,i.e.,other ways for assigning incentives and recognition need to be found.(3)The huge investments in developing DS skills and capacities by some global companies and strong countries is leading to imbalances and fears by different stakeholders hampering the acceptance of Open Science(OS).(4)Finally,OSD will depend on the availability of a global infrastructure fostering an integrated and interoperable data domain-“one data-domain”as George Strawn calls it-which is still not visible due to differences about the technological key pillars.OS therefore is a need for DS,but it will take much more time to implement it than we may have expected.

Open Science-A Question of Trust

Collaboration and the sharing of knowledge is at the heart of Open Science(OS).However,we need to know that the knowledge we find and share is really what it purports to be;and we need to know that the authors we hope to collaborate with are really the people they claim to be.In this paper,the author argues that a prerequisite for OS is trust and that persistent identifiers help to build that trust.The persistent identifier systems must themselves be trustworthy and they must be able to connect the user or their machine to the information they need now and into the future.Infrastructure is rather like plumbing:It goes unnoticed and unappreciated until it fails.This paper puts infrastructure for persistent identifiers in the spotlight as a core component of OS.