科学论文语义增强的研究进展与趋势研判

doi:10.13266/j.issn.0252-3116.2021.01.013

图书情报工作 ›› 2021, Vol. 65 ›› Issue (1): 82-90.DOI: 10.13266/j.issn.0252-3116.2021.01.013

所属专题：图书情报与档案管理前沿热点专辑

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科学论文语义增强的研究进展与趋势研判

宋宁远¹, 裴雷¹, 王春迎²

1. 南京大学信息管理学院南京 210023;
2. 郑州大学信息管理学院郑州 450001

收稿日期:2020-01-18 修回日期:2021-01-19 出版日期:2021-01-05 发布日期:2021-01-05
通讯作者: 裴雷(ORCID:0000-0003-4754-4112),教授,博士,博士生导师,通讯作者,E-mail:plei@nju.edu.cn
作者简介:宋宁远(ORCID:0000-0001-5601-1487),博士后;王春迎(ORCID:0000-0003-4767-4523),讲师,博士。

The Survey and Tendency of Semantic Enrichment for Scientific Papers

Song Ningyuan¹, Pei Lei¹, Wang Chunying²

1. School of Information Management, Nanjing University, Nanjing 210023;
2. School of Information Management, Zhengzhou University, Zhengzhou 450001

Received:2020-01-18 Revised:2021-01-19 Online:2021-01-05 Published:2021-01-05

摘要/Abstract

摘要： [目的/意义] 随着科学交流体系向电子媒介迁移，传统的科学论文内容组织及呈现方式带来了诸多弊端。科学论文语义增强能够创新科学论文内容的组织与呈现方式，是解决这些问题的关键，得到了来自科研机构与学术出版商的重视，形成了一系列理论与实践成果。对这些成果进行梳理、归纳，发现其中的优势与不足，能够为后续推动科学论文语义增强的进一步发展起到指导作用。[方法/过程] 从语义增强的概念入手，着重分析科学论文语义增强的核心目标、实现路径与关键问题，随后，梳理对科学论文中正文本与副文本内容进行语义增强的理论与实践成果，并围绕科学论文语义增强路径上的三个阶段：语义标注、语义组织与可视化呈现进行对比分析。[结果/结论] 研究进一步归纳总结现阶段科学论文语义增强的特点，并对科学论文语义增强的未来发展及研究提出4点意见。

关键词: 科学论文, 语义增强, 语义标注, 语义组织, 可视化

Abstract: [Purpose/significance] With the transfer of scientific communication system to electronic media, the content organization and presentation of traditional scientific papers have brought many disadvantages. Semantic enhancement of scientific papers can innovate the organization and presentation of scientific papers, which is the key to solve these problems. It has been paid attention by scientific research institutions and academic publishers and formed a series of theoretical and practical achievements. Combing and summing up these achievements and finding the advantages and disadvantages can play a guiding role in promoting the further development of semantic enhancement of scientific papers. [Method/process] Starting from the concept of semantic enhancement, this paper focused on the analysis of the core objectives, implementation paths and key issues of semantic enhancement in scientific papers. Then, the paper combed the theoretical and practical results of semantic enhancement of structured and unstructured data in scientific papers and made a comparative analysis by using three stages in the path of semantic enhancement of scientific papers: semantic annotation, semantic organization and visual presentation. [Result/conclusion] This research summarizes the characteristics of semantic enhancement of scientific papers at this stage, provides the four suggestions for the future development and research of semantic enhancement in scientific papers.

Key words: scientific papers, semantic enrichment, semantic annotation, semantic organization, visualization

中图分类号:

G255

宋宁远, 裴雷, 王春迎. 科学论文语义增强的研究进展与趋势研判[J]. 图书情报工作, 2021, 65(1): 82-90.

Song Ningyuan, Pei Lei, Wang Chunying. The Survey and Tendency of Semantic Enrichment for Scientific Papers[J]. LIS, 2021, 65(1): 82-90.

参考文献

[1] RENEAR A H, CAROLE L P, Strategic reading, ontologies, and the future of scientific publishing[J]. Science, 2009,325(5492):828-832.
[2] SHOTTON D. Semantic publishing:the coming revolution in scientific journal publishing[J]. Learned publishing, 2009, 22(2):85-94.
[3] SHOTTON D. The five stars of online journal articles:a framework for article evaluation[EB/OL].[2020-12-20].https//purl.pt/302/dlib/january12/shotton/olshotton.html.
[4] SHOTTON D, PORTWIN K, KLYNE G, et al. Adventures in semantic publishing:exemplar semantic enhancements of a research article[J]. PLoS computational biology, 2009, 5(4):e1000361.
[5] 翁彦琴, 李苑, 彭希珺. 英国皇家化学会(RSC)——科技期刊语义出版模式的研究[J]. 中国科技期刊研究, 2013, 24(5):825-829.
[6] 翁彦琴, 彭希珺. 爱思唯尔(Elsevier)语义出版模式研究[J]. 中国科技期刊研究, 2014, 25(10):1256-1261.
[7] KURZ T, DAMJANOVIC V, GUNTNER G, et al. Semantic enhancement for media asset management systems[J]. Multimedia tools & applications, 2014, 70(2):949-975.
[8] Europeana semantic enrichment[EB/OL].[2020-02-23]. https://pro.europeana.eu/page/europeana-semantic-enrichment.
[9] ZENG M L. Semantic enrichment for enhancing LAM data and supporting digital humanities. review article[J]. El profesional de la informacion, 2019, 28(1):1-35.
[10] WOUTERSEN-WINDHOUWER S, BRANDSMA R, HOGENAAR A, et al. Enhanced publications:linking publications and research data in digital repositories[M]. Amsterdam:Amsterdam University Press, 2009.
[11] HOOGERWERF M. Durable enhanced publications[EB/OL].[2021-01-03]. https://www.researchgate.net/publication/242732066_Durable_Enhanced_Publications.
[12] BREURE L, VOORBIJ H, HOOGERWERF M. Rich internet publications:show what you tell[J]. Journal of digital information, 2010, 12(1):1.
[13] PRASAD A R D, GIUNCHIGLIA F, DEVIKA P M. DERA:from document centric to entity centric knowledge modelling[C]//SLAVIC A, GNOLI C. Faceted classification today:theory, technology and end users:proceedings of the International UDC Seminar 2017. Würzburg:Ergon Verlag, 2017:169-179.
[14] Bibliographic ontology specification[EB/OL].[2021-01-02]. http://www.bibliontology.com.
[15] PERONI S, SHOTTON D. FaBiO and CiTO:ontologies for describing bibliographic resources and citations[J]. Web semantics:science, services and agents on the World Wide Web, 2012, 17(17):33-43.
[16] 张艳侠, 齐飞, 毕强. 关联数据的语义互联应用研究——以VIVO为实例[J]. 图书情报工作, 2013,57(17):17-21.
[17] 喻琪琛, 王晓光. 科学论文摘要语义增强形式调查研究[J]. 数字图书馆论坛, 2017(8):8-15.
[18] CICCARESE P, SHOTTON D, PERONI S, et al. CiTO+SWAN:the Web semantics of bibliographic records, citations, evidence and discourse relationships[J]. Semantic Web, 2014,5(4):295-311.
[19] Citation counting and context characterization ontology[EB/OL].[2019-12-20]. http://purl.org/spar/c4o.
[20] OpenCitation[EB/OL].[2020-12-05]. http://opencitations.net/.
[21] SciGraph[EB/OL].[2020-05-15]. http://www.springernature.com/cn/researchers/scigraph.
[22] Aminer[EB/OL].[2020-05-15]. https://www.aminer.cn.
[23] Microsoft academic graph[EB/OL].[2020-05-15]. https://www.microsoft.com/en-us/research/project/microsoft-academic-graph/.
[24] Open academic graph[EB/OL].[2020-05-15]. https://www.openacademic.ai/oag/.
[25] WANG R, YAN Y, WANG J, et al. AceKG:a large-scale knowledge graph for academic data mining[C]//Proceedings of the 27th ACM international conference on information and knowledge management. New York:Association for Computing Machinery, 2018:1487-1491.
[26] 任海英, 石彤. 科技论文微观概念地图的构建及研究思路的挖掘[J]. 图书情报工作, 2016,60(4):115-124.
[27] 丁君军,郑彦宁,化柏林. 基于规则的学术概念属性抽取[J]. 情报理论与实践, 2011,34(12):10-14,33.
[28] 乐小虬, 张帆, 何远标. 学术论文大纲中关键术语抽取方法研究[J]. 现代图书情报技术, 2014, 30(3):73-79.
[29] 吴思竹, 李峰, 张智雄. 知识资源的语义表示和出版模式研究——以Nanopublication为例[J]. 中国图书馆学报, 2013(4):102-109.
[30] KING R D, ROWLAND J, OLIVER S G,et al. The automation of science[J]. Science, 2009, 324(5923):85-89.
[31] LIAKATA M, SAHA S, DOBNIK S, et al. Automatic recognition of conceptualization zones in scientific articles and two life science applications[J]. Bioinformatics, 2012, 28(7):991-1000.
[32] DE WAARD A, TEL G. The ABCDE format enabling semantic conference proceedings[EB/OL].[2021-01-01].https://www.researchgate.net/publication/220706582_The_ABCDE_Format_Enabling_Semantic_Conference_Proceedings.
[33] DE WAARD A, BUITELAAR P, EIGNER T. Identifying the epistemic value of discourse segments in biology texts[C]//Proceedings of the eighth international conference on computational semantics. Stroudsburg:Association for Computational Linguistics, 2009:351-354.
[34] ZHANG L, KOPAK R, FREUND L, et al. A taxonomy of functional units for information use of scholarly journal articles[J]. Proceedings of the American Society for Information Science and Technology, 2010, 47(1):1-10.
[35] TEUFEL S. Argumentative zoning:information extraction from scientific text[D]. Edinburgh:University of Edinburgh, 1999.
[36] TEUFEL S. The structure of scientific articles:applications to citation indexing and summarization[M]. Stanford,CA:CSLI Publications (CSLI Studies in Computational Linguistics), 2010.
[37] GREEN N L. Representation of argumentation in text with rhetorical structure theory[J]. Argumentation, 2010, 24(2):181-196.
[38] GREEN N. Identifying argumentation schemes in genetics research articles[C]//Proceedings of the 2nd workshop on argumentation mining. Denver:Association for Computational Linguistics, 2015:12-21.
[39] GREEN N. Argumentation mining in scientific discourse[C]//Proceedings of the 18th workshop on computational models of natural argument. London:Association for Computational Linguistics, 2017:7-13.
[40] GREEN N. Implementing argumentation schemes as logic programs[C]//Proceedings of the 16th Workshop on computational models of natural argument. New York:Association for Computational Linguistics, 2017:1-7.
[41] SHUM S B, MOTTA E, DOMINGUE J. ScholOnto:an ontology-based digital library server for research documents and discourse[J]. International journal on digital libraries, 2000, 3(3):237-248.
[42] BUCKINGHAM SHUM S J, UREN V, LI G, et al. Modeling naturalistic argumentation in research literatures:representation and interaction design issues[J]. International journal of intelligent systems, 2007, 22(1):17-47.
[43] UREN V, BUCKINGHAM SHUM S, BACHLER M, et al. Sensemaking tools for understanding research literatures:design, implementation and user evaluation[J]. International journal of human-computer studies, 2006, 64(5):420-445.
[44] THOMPSON P, NAWAZ R, MCNAUGHT J, et al. Enriching a biomedical event corpus with meta-knowledge annotation[J]. BMC bioinformatics, 2011, 12(1). doi:10.1186/1471-2105-12-393.
[45] ANANIADOU S, THOMPSON P, NAWAZ R. Enhancing search:events and their discourse context[C]//GELBUKH A. Proceedings of the 14th international conference on computational linguistics and intelligent text processing. Berlin:Springer-Verlag, 2013:318-334.
[46] DE WAARD A, MAAT H P. Epistemic modality and knowledge attribution in scientific discourse:a taxonomy of types and overview of features[C]//Proceedings of the workshop on detecting structure in scholarly discourse. Stroudsburg:Association for Computational Linguistics, 2012:47-55.
[47] BLAKE C. Beyond genes, proteins, and abstracts:identifying scientific claims from full-text biomedical articles[J]. Journal of biomedical informatics, 2010, 43(2):173-189.
[48] TUDOR G, SIEGFRIED H, KNUD M, et al. SALT-Semantically annotated LaTeX for scientific publications[C]//Proceedings of the 4th European semantic Web on the semantic Web:research and applications. Berlin:Springer-Verlag, 2007:518-532.
[49] 马雨萌, 祝忠明. 科学篇章修辞块本体标准及其应用分析[J]. 情报杂志, 2012(10):112-116.
[50] The discourse element ontology[EB/OL].[2020-05-15]. http://purl.org/spar/deo.
[51] CONSTANTIN A, PERONI S, PETTIFER S, et al. The document components ontology (DoCO)[J]. Semantic Web, 2016, 7(2):167-181.
[52] The argument model ontology[EB/OL].[2020-10-23]. http://www.essepuntato.it/2011/02/argumentmodel.
[53] 王晓光, 李梦琳, 宋宁远. 科学论文功能单元本体设计与标引应用实验[J]. 中国图书馆学报, 2018, 236(4):75-90.
[54] 王晓光, 周慧敏, 宋宁远. 科学论文论证本体设计与标注实验[J]. 情报学报, 2020, 39(9):885-895.
[55] FATHALLA S, VAHDATI S, AUER S, et.al. SemSur:a core ontology for the semantic representation of research findings[C]//Proceedings of the 14th international conference on semantic systems. Vienna:Elsevier B.V., 2018:151-162.
[56] JEONG S, KIM H G. SEDE:an ontology for scholarly event description[J]. Journal of information science, 2010, 36(2):209-227.
[57] FATHALLA S, VAHDAT S, LANGE C, et al. SEO:a scientific events data model[EB/OL].[2020-11-12]. https://www.researchgate.net/publication/336594094_SEO_A_Scientific_Events_Data_Model.
[58] CLARK T, CICCARESE P, GOBLE C. Micropublications:a semantic model for claims, evidence, arguments and annotations in biomedical communications[J]. Journal of biomedical semantics, 2014, 5(1):28.
[59] BOLLING C, WEIDLICH M, HOLZHUTTER H G. SEE:structured representation of scientific evidence in the biomedical domain using semantic Web techniques[J]. Journal of biomedical semantics, 2014, 5(S1):S1.
[60] HETTNE K M, DHARURI H, ZHAO J, et al. Structuring research methods and data with the research object model:genomics workflows as a case study[J]. Journal of biomedical semantics, 2014, 5(1):41.

科学论文语义增强的研究进展与趋势研判

The Survey and Tendency of Semantic Enrichment for Scientific Papers

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