The 2019 Publishing Landscape Technological Horizons 从技术的 …gb.oversea.cnki.net/Seminar/2019Seminar/bg/images/hypdf/... · 2019-09-12 · The 2019 Publishing Landscape: Technological

The 2019 Publishing Landscape:Technological Horizons 从技术的视角看学术出版的现状

丁海珈

亚太科研服务与学术关系主管

Taylor & Francis Group

Information Classification: General

Today’s agenda 今日议程

• Publishing landscape: technological advancements 互联网与技术的发展，使得国际学术出版与科

研生命周期全面融合渗透，而不是只关注出版这一个环节！

– New technologies in publishing 出版的新技术

– Artificial intelligence 人工智能

• What exactly is Artificial Intelligence? 什么是人工智能？

• Artificial Intelligence and the R&D Ecosystem 人工智能与科研生态系

统

• Artificial Intelligence and Taylor & Francis 人工智能在TF出版集团

• Where we’re heading with Artificial Intelligence 人工智能带向何方 2


2018

After Hargroves & Smith, The Natural Advantage of Nations, Routledge 2006

Artificial Intelligence (AI)

这是一个信息技术、知识和全球电信化的时代，技术进步正在加速


Digital Workflow and New Players科研工作流程和新进入者

4


Digital technology facilitates discoverability & visibility 在出版环节数字技术促进发现性和能见度

5

Funder Registry

Submit. Review. Accept

Submitted manuscript

Published Content

它突出了研究人员和出版商现在正在使用的一些日常工具，以确保研究，推动出版过程，并确保共享和记录影响


WHAT IS ARTIFICIAL INTELLIGENCE?

何为人工智能？


What is artificial intelligence? 何为人工智能？

Machine Learning: Arthur Samuel (1959) defined it as the field of study that gives computers the ability to learn without being explicitly programmed. 将其定义为使计算机无需明确编程即可学习，让机器理解

事物而不是听指令行事

John McCarthy first coined the term “artificial intelligence” (AI) in 1956 at a conference in Dartmouth. Mirror the functions of the human brain...镜像人类大脑的功能。基本原

理是允许智能系统或计算机处理大量数据，学习如何完成任务而无需明确编程如何执行

It is not a robot apocalypse, at least not yet... 并非机器人大灾难

Neural Networks 1980-90s: 机器学习模型之一的神经网络


ARTIFICIAL INTELLIGENCE AND THE R&D ECOSYSTEM

人工智能与科研生态系统


Artificial Intelligence and the wider R&D Ecosystem4

Information Classification: GeneralResearch Cycle Image: http://staff.napier.ac.uk/services/information-services/research-cycle/Pages/home.aspx

The research cycle 科研生态系统


Automated labs: AI doing robust science


Automated labs: 70,000 papers on p53 - AI can handle large dataset 处理大量数据






● Despite noble intentions, neither publishers nor researchers are able to keep up with the pace of discovery.

● Human intelligence combined with artificial intelligence may be the answer.

Can we trust human intelligence alone for the progress of humanity? 我们能否仅仅相信人类的智慧才能促进人类的进步？如何甄别无法重复的实验以及错误的结论？


ARTIFICIAL INTELLIGENCE AND TAYLOR & FRANCIS

人工智能在TF的应用


Artificial Intelligence and Taylor & Francis图书与期刊的应用正在起步

Aug 2017 - came to an agreement with UNSILO to use their machine learning technology to extract concepts from our content.

Jan 2018 - Related book recommendations based on machine learning go live on newly launched eBooks platform.

May 2018 - ML Concepts to be delivered within Onix feeds to Amazon

We are really only just getting started!...AI translations, automated formatting, automated submission and much, much more! 人工智能辅助的自动翻译、自动排版、投稿

以及更多

May 2017 - Announced the acquisition of Colwiz.


Journal recommendation tool推荐期刊的工具

Using NLP algorithms to assess submission 使用自然语言处理算法来分析提交的稿件

Scan manuscripts and previously accepted

articles 扫描稿件和过

去已经接受的文章

Review Journal suitability 审视期刊的

适用性

Journal Recommendations


Streamlining the submission process简化投稿流程

21This Photo by Unknown Author is licensed under CC BY

Author uploads paper to Peer Review

System

System auto extracts co-author and

associated metadata

Author approves what has been generated


Duplication and data fabrication checking检查复制的和虚构数据 • Identify similar sounding paragraphs or

sentences 识别发音相似的段落或句子

• Through Natural Language Processing we can identify semantically similar outputs通过自然语言处理，识别语义相似性

• Improve reporting 改进报告

• Spot statistical errors 发现统计错误

• Moving to look at data for potential fabrication 检测数据是否是虚构的

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AI in Peer Review 人工智能用于同行评审

Automation of Reviewer selection自动筛选推荐审稿人

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Submitted manuscript

Reviewers


Increasing efficiency (and satisfaction) 机器编辑

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9%

17%

25%

33%

66%

49%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

S&T (n=8771)

SSH (n=8304)

Score 1–4 Score 5–7 Score 8–107.5

8

8.5

9

Editor Author

Editor and author satisfaction with copyediting, 2017

Mechanical Offshore Onshore


Contextualized Copyediting Workflow 新排版流程

Track Intervention

Track A Pre-editing only; no copyediting interventionTrack B Guided copyedit performed by vendor team

Track C Full-read copyedit performed by vendor team or freelancer

NLP check自然语言检查

Quality score质量评分

Pre-edited manuscript

Track A

Track B

Track C

Typeset proof

Guided edit

Full-read edit


Curation of content 内容策划

• Machine learning of text to automatically extract or classify bibliographic info into– ontologies 本体

– taxonomies 分类法

– Systems 系统

• Virtual special issues• Virtual librarian?• Concept recognition• Automatic abstracts/Summaries/ Translation

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Increasing discoverability AI辅助提高内容可发现性的推荐阅读功能

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-基于搜索模式的关键字自动相关-建议相关内容-行为建议-评论审核


Increasing engagement定制客户需要的内容增加用户粘性

28

Lannette Heast @LannetteIt’s 6 months since @tandfonline published my article! Can you believe it’s had nearly 2,000 views. WOW!!!


Artificial Intelligence and Taylor & Francis通过机器学习和AI技术，内容流动的每个环节都可改善

Readers

• Increase discoverability• Increase engagement

Authors

• Simplify submission• Improve peer review

Taylor & Francis

• Improve efficiency• Improve targeting

- Automatically complete submission forms based on manuscripts

- Recommendation of journals for submission based on manuscripts

- Detect plagiarism - Detect conflict of

interest during peer review

- Automatically extract or classify bibliographic info into ontologies, taxonomies and systems

- Concept recognition- Automatic

abstracts/Summaries/ Translation

- Auto-correlation of keywords based search patterns

- Suggestions of related content

- Behavioral recommendations

- Review Moderation

CONTENT


WHERE WE’RE HEADING…走向未来

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Information Classification: GeneralResearch Cycle Image: http://staff.napier.ac.uk/services/information-services/research-cycle/Pages/home.aspx

• Suggest papers to read• Suggest funding/grants• Identify emerging areas and

research trends

• Automated summarisation• Find targets for drug

development• Find collaborators and connect

researchers

• Optimise reaction time/costs• Automated data analysis• Automated hypothesis

generation• Scanning to spot errors in

reporting

• Suggest missing references• Find target journals• Automated submission• Find peer reviewers• Automated

data/protocol/algorithm validation (reproducibility)

• Automated paper writing??

• Increased visibility through auto-correlation of keywords based search patterns

• Suggestions of related content• Trust in reproducibility

Accelerated research cycle技术渗透加快科研生命周期


Artificial Intelligence and the wider R&D Ecosystem4


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Questions?

Documents

The 2019 Publishing Landscape Technological Horizons 从技术的 …gb.oversea.cnki.net/Seminar/2019Seminar/bg/images/hypdf/... · 2019-09-12 · The 2019 Publishing Landscape: Technological