情報組織化研究グループ 2014年10月月例会発表資料
国際連合食糧農業機関(FAO)においては、文献データベースAGRISやシソーラスAGROVOCの提供をはじめとする農業関連の科学技術情報の提供を行っており、近年ではLinked Open Data(LOD)を活用した事例も見られる。
本発表においては、FAOによる書誌データのLOD化への勧告、LODE-BD(Linked Open Data(LOD)-enabled bibliographical data)などの事例を紹介するほか、国内の書誌データ、研究データ等との連係の可能性について検討する。
情報組織化研究グループ 2014年10月月例会発表資料
国際連合食糧農業機関(FAO)においては、文献データベースAGRISやシソーラスAGROVOCの提供をはじめとする農業関連の科学技術情報の提供を行っており、近年ではLinked Open Data(LOD)を活用した事例も見られる。
本発表においては、FAOによる書誌データのLOD化への勧告、LODE-BD(Linked Open Data(LOD)-enabled bibliographical data)などの事例を紹介するほか、国内の書誌データ、研究データ等との連係の可能性について検討する。
ACM SIGMOD日本支部第56回支部大会でお話しした、ICDE 2014の参加報告についての資料です。以下のような6部構成になっています。全190ページです。
・ICDE 2014を俯瞰してみる(5p~)
・ビッグデータ時代の新発想:もうデータは蓄えない(32p~)
Keynote, Running with Scissors: Fast Queries on Just-in-Time Databases
・見えない相手と協調作業:センサネットワーク上のデータ集約(64p~)
10 Year Most Influential Paper, Approximate Aggregation Techniques for Sensor Databases
・メインメモリデータベースがハードウェアトランザクショナルメモリを使ったら…(96p~)
Best Paper, Exploiting Hardware Transactional Memory in Main-Memory Databases
・過去の結果を再利用:ビューを用いた大規模グラフからのパターン発見(126p~)
Best Paper Runner-up, Answering Graph Pattern Queries Using Views
・アルゴリズムでゴリゴリ解決:大量のベクトルから類似ペアを厳密に見つけたい(155p~)
気になる論文, L2AP: Fast Cosine Similarity Search With Prefix L-2 Norm Bounds
This document discusses the concept of "dividual" or "fragmented person" and proposes a "dividual-type society". It explains that in anthropology, a dividual refers to a person composed of multiple, overlapping relationships and identities, rather than a single, fixed individual. It also discusses how philosophers like Deleuze have analyzed modern society as fragmenting people into dividuals through constant monitoring and data collection. The document argues that a dividual-type society is one where relationships and connections between people are prioritized over ideas of single, independent individuals. It proposes that understanding people as dividuals composed of multiple aspects could make society more inclusive and flexible.
1. The document appears to be a collection of various information on different topics including taxonomy, concepts, papers, events, statistics, and more.
2. It includes definitions of concepts, taxonomic classifications of species over time, bibliographic information on papers, event details, usage statistics of ontology types, and other miscellaneous information.
3. The document touches on a wide range of subjects in a disorganized manner, compiling unrelated facts and references from different domains.
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.
The Japan Link Center (JaLC) was founded in 2012 and is operated by four national organizations to register DOIs for academic content produced in Japan or Japanese. It provides DOI registration services through various methods to accommodate different types of content holders. Over 1.5 million DOIs have been registered since 2013 across various content categories like journal articles, books, theses, and research data. JaLC aims to connect different content producers and users through DOI assignment and resolution. It also engages in outreach activities to promote adoption of DOIs nationwide in a way that fits the local scholarly communication environment and business models in Japan.
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.
The document describes the design process of the Agricultural Activity Ontology (AAO) in Japan. It involved surveying existing vocabularies, analyzing agricultural activity data, proposing an initial hierarchical structure, introducing description logics to define properties and relationships, and getting feedback from domain experts. The goal was to standardize vocabulary for agricultural IT systems to improve data sharing and integration. The AAO continues to be expanded with new terms and linkages based on additional data sources through a collaborative and iterative design process.
- Scientific names for species can change over time as taxonomy knowledge evolves
- An event-centric ontology model represents names and changes through time using different URIs for taxon concepts at different times
- Transition and snapshot models can then simplify the descriptions by linking concepts over time or just showing current names
- This approach allows integrated representation of taxonomy knowledge and its revisions in a computable way
The document discusses using metadata to find researchers within and across organizations. It provides an example of analyzing data from the CiNii and KAKEN databases to find collaborators of researchers at the National Institute of Informatics in Japan. Network analysis was performed and revealed 61 researchers with 1,832 collaborators based on CiNii data and 37 researchers with 421 collaborators based on KAKEN data. The analysis also examined collaboration networks within the Graduate University for Advanced Studies, which includes researchers from diverse domains across its 21 departments. The document emphasizes that while the data provides opportunities to explore collaboration, making services to easily support researchers remains important.
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.
The document summarizes the experimental project of registering Digital Object Identifiers (DOIs) for research data at the Japan Link Center (JaLC). The project aims to establish workflows for registering DOIs for research data and test the registration of data DOIs. It involves 9 research projects and 14 organizations registering and integrating DOIs for their data through the JaLC system. The project addresses several issues in registering DOIs for dynamic research data, such as data lifecycles, granularity, persistence, and handling changes over time.
More from National Institute of Informatics (NII) (20)
7. 科学のタイプと再現性
• 第1の科学:理論科学
– 演繹
• 第2の科学:実験科学
– 再実験による仮説検証
• 第3の科学:シミュレーション科学
– 再シミュレーションによる検証?
• 第4の科学:データ中心科学
– ??(再プロセスによる検証?)
Maleki, A., Rahman, I., Shahram, M., & Stodden, V. (2008). 15 years of reproducible research in
computational harmonic analysis. Department of Statistics, Stanford University.