オープンコミュニティ「要求開発アライアンス」(http://www.openthology.org)の2012年12月定例会発表資料です。
Open Community "Requirement Development Alliance" 2012/12 regular meeting of the presentation materials.
オープンコミュニティ「要求開発アライアンス」(http://www.openthology.org)の2012年12月定例会発表資料です。
Open Community "Requirement Development Alliance" 2012/12 regular meeting of the presentation materials.
プレゼン・ポスターで自分の研究を「伝える」 (How to do technical oral/poster presentation)Toshihiko Yamasaki
MIRU2020若手プログラム招待講演のスライドを一般公開用にアレンジしたものです。日本語で書かれています。下記の点にご注意ください
・セリフが伴ってないので内容は限定的です
・著作権等に配慮しているので中身は結構無味乾燥です。
This is an arranged version of my invited talk at MIRU 2020 young researchers' forum. This is written in Japanese.
プレゼン・ポスターで自分の研究を「伝える」 (How to do technical oral/poster presentation)Toshihiko Yamasaki
MIRU2020若手プログラム招待講演のスライドを一般公開用にアレンジしたものです。日本語で書かれています。下記の点にご注意ください
・セリフが伴ってないので内容は限定的です
・著作権等に配慮しているので中身は結構無味乾燥です。
This is an arranged version of my invited talk at MIRU 2020 young researchers' forum. This is written in Japanese.
Presented at Journal Paper Track, The Web Conference, Lyon, France, April 15, 2018
https://doi.org/10.1145/3184558.3186234
Abstract: Linked Open Data (LOD) technology enables web of data and exchangeable knowledge graphs through the Internet. However, the change in knowledge is happened everywhere and every time, and it becomes a challenging issue of linking data precisely because the misinterpretation and misunderstanding of some terms and concepts may be dissimilar under different context of time and different community knowledge. To solve this issue, we introduce an approach to the preservation of knowledge graph, and we select the biodiversity domain to be our case studies because knowledge of this domain is commonly changed and all changes are clearly documented. Our work produces an ontology, transformation rules, and an application to demonstrate that it is feasible to present and preserve knowledge graphs and provides open and accurate access to linked data. It covers changes in names and their relationships from different time and communities as can be seen in the cases of taxonomic knowledge.
We propose Crop Vocabulary(CVO) as a basis of the core vocabulary of crop names that becomes the guidelines for data interoperability between agricultural ICT systems on the food chain. Since a single species is treated in different ways, there are many different types of crop names. So, we organize the crop name discriminated by properties such as scientific name, planting method, edible part and registered cultivar information. Also, Crop Vocabulary is also linked to existing vocabularies issued by Japanese government agency and international organization such as AGROVOC. It is expected to use in the data format in the agricultural ICT system.
Presented in 45th Asia Pacific Advanced Network (APAN45) Meeting, Singapore (2018)
Presented as the invited talk at International Workshop on kNowledge eXplication for Industry (kNeXI2017). In this talk, I explain the experience and lesson learnt how to build ontologies. I am currently building the agriculture activity ontology (AAO). It describes classification and properties of various activities in the agriculture domain. It is formalized with Description Logics.
Presented at the Interest Group on Agricultural Data (IGAD) ,3 April, 2017, Barcelona, Spain
Abstract: n this talk, we present the current status of our agriculture ontologies that are developed to accelerate the data use in agriculture.
The agriculture activity ontology formalizes the activities in agriculture. We have developed it for three years. Now we are developing its applications. One application is to exchange formats between different farmer management systems. Another ontology is the crop ontology that standardizes the names of crops. The structure is simple but has links to many other standards in distribution industry, food industry and so on.
Now it is getting common for farmers to use IT systems to manage their activities. To realize incomparability among IT systems, we are building the vocabulary based on the agricultural activity ontology. The words in the vocabulary have logical definitions because the ontology is formalized based on description logic. As a result, the vocabulary has expendability to add new words and flexibility to generate custom vocabularies such like those for specific crops and regions.
More from National Institute of Informatics (NII) (20)
16. 科学におけるデータ共有のメリット
• データの早期公開はよりよい成果が期待できる
• エラーの早期発見、早いコミュニティ形成
• 一つのデータから多様な研究
• 再現可能性
• 他データとの結合
• 学際的研究の促進
• データの保全
• サイテーション
• 教育やアウトリーチ
• 社会や市民科学とのつながり
Data sharing in astronomy, Željko Ivezić, Department of Astronomy, University of Washington
http://www.astro.washington.edu/users/ivezic/Outreach/Talks/NAS2011_Ivezic.pdf
17. 科学におけるデータ共有のデメリット
• 内部利用より高度な“標準化”の必要
• キュレーション
• 維持コスト
• 横取り研究の可能性
Data sharing in astronomy, Željko Ivezić, Department of Astronomy, University of Washington
http://www.astro.washington.edu/users/ivezic/Outreach/Talks/NAS2011_Ivezic.pdf
18. データを共有すると引用は増えるか
• 概ねYES
• データ付き付き論文はそうでない論文に比べ
• Gene expression microarray論文では、少なくとも引用が9%増加
• Piwowar HA, Vision TJ. (2013) Data reuse and the open data citation
advantage. PeerJ 1:e175 https://doi.org/10.7717/peerj.175
• 天文学論文で、、引用は20%増加
• Linking to Data - Effect on Citation Rates in Astronomy, Edwin A. Henneken, Alberto Accomazzi, (Submitted on
15 Nov 2011), arXiv:1111.3618
• 宇宙天文学では、少なくとも引用28%の増加
• The data sharing advantage in astrophysics, S. B. F. Dorch, T. M. Drachen, O. Ellegaard, (Submitted on 8 Nov
2015), arXiv:1511.02512
• 古海洋学論文では 30%の増加
• Sears, J. R. (2011). Data Sharing Effect on Article Citation Rate in Paleoceanography. EOS, Transactions,
American Geophysical Union, 92(53, Fall Meet. Supp.), IN53B–1628.
http://adsabs.harvard.edu/abs/2011AGUFMIN53B1628S, https://www.slideshare.net/JonSears1/data-sharing-
effect-on-article-citation-rate-in-paleoceanography
44. 研究助成団体におけるデータ公開の義務
化
• 研究助成におけるデータの公開のポリシーやその義務化
• National Science Foundation (NSF)
• National Institutes of Health (NIH)
• NIH Data Sharing Policy (2006. 6-)
• Wellcome Trust
• Bill and Melinda Gates Foundation
• 国内
• JST戦略的創造研究推進事業
• AMED
50. 学会におけるデータポリシー
• Position Statement by AGU (American Geophysical Union)
“Earth and Space Science Data Should Be Widely Accessible in Multiple
Formats and Long‐term Preservation of Data is an Integral
Responsibility of Scientists and Sponsoring Institutions”
https://sciencepolicy.agu.org/files/2013/07/AG
U-Data-Position-Statement_March-2012.pdf
71. Core Trust Seal
• 「信頼できるデータリポジトリを認定するための中核的な統一
要件」を満たすリポジトリに対して付与される認証
• Data Seal of Approval(DSA)と国際科学会議(ICSU)世界科学データシ
ステム(WDS)がRDAのワーキンググループで策定
• 各リポジトリに対して16項目の自己評価を実施
• 各項目は5段階(0~4)で評価
• 概ね3以上のレベルであれば認証される
信頼性を高める為に必要なアイテム, 八塚 茂, https://doi.org/10.18908/joss2018.C5.s03
72. Core Trust Sealの評価(5段階)
• 0 – 適用不可(Not applicable)
• 1 – まだ考慮されていない (The repository has not considered
this yet)
• 2 – 概念上は存在する(The repository has a theoretical concept)
• 3 – 実装フェーズにある (The repository is in the implementation
phase)
• 4 – 実装済(The guideline has been fully implemented in the
repository)
信頼性を高める為に必要なアイテム, 八塚 茂, https://doi.org/10.18908/joss2018.C5.s03