Nine Best Practices for Research Software Registries and Repositories: a Concise Guide
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Article Incidences of problematic cell lines are lower in papers that use RRIDs to identify cell lines BABIC, Zeljana, et al. Abstract The use of misidentified and contaminated cell lines continues to be a problem in biomedical research. Research Resource Identifiers (RRIDs) should reduce the prevalence of misidentified and contaminated cell lines in the literature by alerting researchers to cell lines that are on the list of problematic cell lines, which is maintained by the International Cell Line Authentication Committee (ICLAC) and the Cellosaurus database. To test this assertion, we text-mined the methods sections of about two million papers in PubMed Central, identifying 305,161 unique cell-line names in 150,459 articles. We estimate that 8.6% of these cell lines were on the list of problematic cell lines, whereas only 3.3% of the cell lines in the 634 papers that included RRIDs were on the problematic list. This suggests that the use of RRIDs is associated with a lower reported use of problematic cell lines. Reference BABIC, Zeljana, et al. Incidences of problematic cell lines are lower in papers that use RRIDs to identify cell lines. eLife, 2019, vol. 8, p. e41676 DOI : 10.7554/eLife.41676 PMID : 30693867 Available at: http://archive-ouverte.unige.ch/unige:119832 Disclaimer: layout of this document may differ from the published version. 1 / 1 FEATURE ARTICLE META-RESEARCH Incidences of problematic cell lines are lower in papers that use RRIDs to identify cell lines Abstract The use of misidentified and contaminated cell lines continues to be a problem in biomedical research. -
Introduction to Linked Data and Its Lifecycle on the Web
Introduction to Linked Data and its Lifecycle on the Web Sören Auer, Jens Lehmann, Axel-Cyrille Ngonga Ngomo, Amrapali Zaveri AKSW, Institut für Informatik, Universität Leipzig, Pf 100920, 04009 Leipzig {lastname}@informatik.uni-leipzig.de http://aksw.org Abstract. With Linked Data, a very pragmatic approach towards achieving the vision of the Semantic Web has gained some traction in the last years. The term Linked Data refers to a set of best practices for publishing and interlinking struc- tured data on the Web. While many standards, methods and technologies devel- oped within by the Semantic Web community are applicable for Linked Data, there are also a number of specific characteristics of Linked Data, which have to be considered. In this article we introduce the main concepts of Linked Data. We present an overview of the Linked Data lifecycle and discuss individual ap- proaches as well as the state-of-the-art with regard to extraction, authoring, link- ing, enrichment as well as quality of Linked Data. We conclude the chapter with a discussion of issues, limitations and further research and development challenges of Linked Data. This article is an updated version of a similar lecture given at Reasoning Web Summer School 2011. 1 Introduction One of the biggest challenges in the area of intelligent information management is the exploitation of the Web as a platform for data and information integration as well as for search and querying. Just as we publish unstructured textual information on the Web as HTML pages and search such information by using keyword-based search engines, we are already able to easily publish structured information, reliably interlink this informa- tion with other data published on the Web and search the resulting data space by using more expressive querying beyond simple keyword searches. -
Linked Data Services for Internet of Things
International Conference on Recent Advances in Computer Systems (RACS 2015) Linked Data Services for Internet of Things Jaroslav Pullmann, Dr. Yehya Mohamad User-Centered Ubiquitous Computing department Fraunhofer Institute for Applied Information Technology FIT Sankt Augustin, Germany {jaroslav.pullmann, yehya.mohamad}@fit.fraunhofer.de Abstract — In this paper we present the open source “LinkSmart Resource Framework” allowing developers to II. LINKSMART RESOURCE FRAMEWORK incorporate heterogeneous data sources and physical devices through a generic service facade independent of the data model, A. Rationale persistence technology or access protocol. We particularly consi- The Java Data Objects standard [2] specifies an interface to der the integration and maintenance of Linked Data, a widely persist Java objects in a technology agnostic way. The related accepted means for expressing highly-structured, machine reada- ble (meta)data graphs. Thanks to its uniform, technology- Java Persistence specification [3] concentrates on object-rela- agnostic view on data, the framework is expected to increase the tional mapping only. We consider both specifications techno- ease-of-use, maintainability and usability of software relying on logy-driven, overly detailed with regards to common data ma- it. The development of various technologies to access, interact nagement tasks, while missing some important high-level with and manage data has led to rise of parallel communities functionality. The rationale underlying the LinkSmart Resour- often unaware of alternatives beyond their technology bounda- ce Platform is to define a generic, uniform interface for ries. Systems for object-relational mapping, NoSQL document or management, retrieval and processing of data while graph-based Linked Data storage usually exhibit complex, maintaining a technology and implementation agnostic facade. -
Using Shape Expressions (Shex) to Share RDF Data Models and to Guide Curation with Rigorous Validation B Katherine Thornton1( ), Harold Solbrig2, Gregory S
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Repositorio Institucional de la Universidad de Oviedo Using Shape Expressions (ShEx) to Share RDF Data Models and to Guide Curation with Rigorous Validation B Katherine Thornton1( ), Harold Solbrig2, Gregory S. Stupp3, Jose Emilio Labra Gayo4, Daniel Mietchen5, Eric Prud’hommeaux6, and Andra Waagmeester7 1 Yale University, New Haven, CT, USA [email protected] 2 Johns Hopkins University, Baltimore, MD, USA [email protected] 3 The Scripps Research Institute, San Diego, CA, USA [email protected] 4 University of Oviedo, Oviedo, Spain [email protected] 5 Data Science Institute, University of Virginia, Charlottesville, VA, USA [email protected] 6 World Wide Web Consortium (W3C), MIT, Cambridge, MA, USA [email protected] 7 Micelio, Antwerpen, Belgium [email protected] Abstract. We discuss Shape Expressions (ShEx), a concise, formal, modeling and validation language for RDF structures. For instance, a Shape Expression could prescribe that subjects in a given RDF graph that fall into the shape “Paper” are expected to have a section called “Abstract”, and any ShEx implementation can confirm whether that is indeed the case for all such subjects within a given graph or subgraph. There are currently five actively maintained ShEx implementations. We discuss how we use the JavaScript, Scala and Python implementa- tions in RDF data validation workflows in distinct, applied contexts. We present examples of how ShEx can be used to model and validate data from two different sources, the domain-specific Fast Healthcare Interop- erability Resources (FHIR) and the domain-generic Wikidata knowledge base, which is the linked database built and maintained by the Wikimedia Foundation as a sister project to Wikipedia. -
Linked Data Vs Schema.Org: a Town Hall Debate About the Future of Information
Linked Data vs Schema.org: A Town Hall Debate about the Future of Information Schema.org Resources Schema.org Microdata Creation and Analysis Tools Schema.org Google Structured Data Testing Tool http://schema.org/docs/full.html http://www.google.com/webmasters/tools/richsnippets The entire hierarchy in one file. Microdata Parser Schema.org FAQ http://tools.seomoves.org/microdata http://schema.org/docs/faq.html This tool parses HTML5 microdata on a web page and displays the results in a graphical view. You can see the full details of each microdata type by clicking on it. Getting Started with Schema.org http://schema.org/docs/gs.html Drupal module Includes information about how to mark up your content http://drupal.org/project/schemaorg using microdata, using the schema.org vocabulary, and advanced topics. A drop-in solution to enable the collections of schemas available at schema.org on your Drupal 7 site. Micro Data & Schema.org: Guide To Generating Rich Snippets Wordpress plugins http://seogadget.com/micro-data-schema-org-guide-to- http://wordpress.org/extend/plugins/tags/schemaorg generating-rich-snippets A list of Wordpress plugins that allow you to easily insert A very comprehensive guide that includes an schema.org microdata on your site. introduction, a section on integrating microdata (use cases) schema.org, and a section on tools and useful Microdata generator resources. http://www.microdatagenerator.com A simple generator that allows you to input basic HTML5 Microdata and Schema.org information and have that info converted into the http://journal.code4lib.org/articles/6400 standard schema.org markup structure. -
EN125-Web.Pdf
ercim-news.ercim.eu Number 125 April 2021 ERCIM NEWS Special theme: Brain-inspired Computing Also in this issue Research and Innovation: Human-like AI JoinCt ONTENTS Editorial Information JOINT ERCIM ACTIONS ERCIM News is the magazine of ERCIM. Published quarterly, it reports 4 ERCIM-JST Joint Symposium on Big Data and on joint actions of the ERCIM partners, and aims to reflect the contribu - Artificial Intelligence tion made by ERCIM to the European Community in Information Technology and Applied Mathematics. Through short articles and news 5 ERCIM “Alain Bensoussan” Fellowship Programme items, it provides a forum for the exchange of information between the institutes and also with the wider scientific community. This issue has a circulation of about 6,000 printed copies and is also available online. SPECIAL THEME ERCIM News is published by ERCIM EEIG The special theme “Brain-inspired Computing” has been BP 93, F-06902 Sophia Antipolis Cedex, France coordinated by the guest editors Robert Haas (IBM +33 4 9238 5010, [email protected] Research Europe) and Michael Pfeiffer (Bosch Center for Director: Philipp Hoschka, ISSN 0926-4981 Artificial Intelligence) Contributions Introduction to the Special Theme Contributions should be submitted to the local editor of your country 6 Brain-inspired Computing by Robert Haas (IBM Research Europe) and Michael Copyrightnotice Pfeiffer (Bosch Center for Artificial Intelligence) All authors, as identified in each article, retain copyright of their work. ERCIM News is licensed under a Creative Commons Attribution -
FAIR Linked Data
FAIR Linked Data - Towards a Linked Data backbone for users and machines Johannes Frey Sebastian Hellmann [email protected] Knowledge Integration and Linked Data Technologies (KILT/AKSW) & DBpedia Association InfAI, Leipzig University Leipzig, Germany ABSTRACT scientific and open data. While the principles became widely ac- Although many FAIR principles could be fulfilled by 5-star Linked cepted and popular, they lack technical details and clear, measurable Open Data, the successful realization of FAIR poses a multitude criteria. of challenges. FAIR publishing and retrieval of Linked Data is still Three years ago a dedicated European Commission Expert Group rather a FAIRytale than reality, for users and machines. In this released an action plan for "turning FAIR into reality" [1] empha- paper, we give an overview on four major approaches that tackle sizing the need for defining "FAIR for implementation". individual challenges of FAIR data and present our vision of a FAIR In this paper, we argue that Linked Data as a technology in Linked Data backbone. We propose 1) DBpedia Databus - a flex- combination with the Linked Open Data movement and ontologies ible, heavily automatizable dataset management and publishing can be seen as one of the most promising approaches for managing platform based on DataID metadata; that is extended by 2) the scholarly metadata as well as representing and connecting research novel Databus Mods architecture which allows for flexible, uni- results (RDF knowledge graphs) across the web. Although many fied, community-specific metadata extensions and (search) overlay FAIR principles could be fulfilled by 5-star Linked Open Data [5], systems; 3) DBpedia Archivo an archiving solution for unified han- the successful realization of FAIR principles for the Web of Data in dling and improvement of FAIRness for ontologies on publisher and its current state is a FAIRytale. -
Linked Data Search and Browse Application
IT 17 019 Examensarbete 30 hp Maj 2017 Linked Data Search and Browse Application Chao Cai Fatemeh Shirazi Nasab Institutionen för informationsteknologi Department of Information Technology Abstract Linked Data Search and Browse Application Chao Cai and Fatemeh Shirazi Nasab Teknisk- naturvetenskaplig fakultet UTH-enheten In order to achieve the ISO 26262 standard on the perspective of requirements traceability, a huge volume of data has been converted into RDF format, and been Besöksadress: stored in a Triple store. The need to have a web application to search and browse Ångströmlaboratoriet Lägerhyddsvägen 1 that RDF data has been raised. In order to build this application, several open- Hus 4, Plan 0 source components such as Apache Solr, Apache Jena, Fuseki and Technologies such as Java, HTML, CSS, and Javascript have been used. The application has Postadress: been evaluated with SUS method, an industry standard and reliable tool for Box 536 751 21 Uppsala measuring the system usability, by six engineers from Scania, the evaluation result in general is positive, five out of six participants successfully retrieved their desired Telefon: search results. 018 – 471 30 03 Telefax: Keyword: ISO 26262, Traceability, Triple store, Web application 018 – 471 30 00 Hemsida: http://www.teknat.uu.se/student Handledare: Mattias Nyberg Ämnesgranskare: Tore Risch Examinator: Mats Daniels IT 17 019 Tryckt av: Reprocentralen ITC Acknowledgement We wish to extend our deepest gratitude to our advisors, Dr. Mat- tias Nyberg and Dr. Tore Risch, for their thoughtful guidance throughout our master thesis. We appreciate many fruitful discus- sions and helpful advice from the members of the Scania RESA group. -
The NIDDK Information Network: a Community Portal for Finding Data, Materials, and Tools for Researchers Studying Diabetes, Digestive, and Kidney Diseases
RESEARCH ARTICLE The NIDDK Information Network: A Community Portal for Finding Data, Materials, and Tools for Researchers Studying Diabetes, Digestive, and Kidney Diseases Patricia L. Whetzel1, Jeffrey S. Grethe1, Davis E. Banks1, Maryann E. Martone1,2* 1 Center for Research in Biological Systems, University of California, San Diego, San Diego, California, a11111 United States of America, 2 Dept of Neurosciences, University of California, San Diego, San Diego, California, United States of America * [email protected] Abstract OPEN ACCESS The NIDDK Information Network (dkNET; http://dknet.org) was launched to serve the needs Citation: Whetzel PL, Grethe JS, Banks DE, Martone of basic and clinical investigators in metabolic, digestive and kidney disease by facilitating ME (2015) The NIDDK Information Network: A access to research resources that advance the mission of the National Institute of Diabe- Community Portal for Finding Data, Materials, and Tools for Researchers Studying Diabetes, Digestive, tes and Digestive and Kidney Diseases (NIDDK). By research resources, we mean the and Kidney Diseases. PLoS ONE 10(9): e0136206. multitude of data, software tools, materials, services, projects and organizations available to doi:10.1371/journal.pone.0136206 researchers in the public domain. Most of these are accessed via web-accessible data- Editor: Chun-Hsi Huang, University of Connecticut, bases or web portals, each developed, designed and maintained by numerous different UNITED STATES projects, organizations and individuals. While many of the large government funded data- Received: February 17, 2015 bases, maintained by agencies such as European Bioinformatics Institute and the National Accepted: July 30, 2015 Center for Biotechnology Information, are well known to researchers, many more that have been developed by and for the biomedical research community are unknown or underuti- Published: September 22, 2015 lized. -
Creating a Linked Data-Friendly Metadata Application Profile for Archival Description Poster
Proc. Int’l Conf. on Dublin Core and Metadata Applications 2017 Creating a Linked Data-Friendly Metadata Application Profile for Archival Description Poster Matienzo, Mark A. Roke, Elizabeth Russey Carlson, Scott Stanford University, U.S.A. Emory University, U.S.A. Rice University, U.S.A. [email protected] [email protected] [email protected] Keywords: archival description; linked data; archives; Schema.org; metadata mapping Abstract We provide an overview of efforts to apply and extend Schema.org for archives and archival description. The authors see the application of Schema.org and extensions as a low barrier means to publish easily consumable linked data about archival resources, institutions that hold them, and contextual entities such as people and organizations responsible for their creation. Rationale and Objectives Schema.org has become one of the most widely recognized and adopted mechanisms for publishing structured data on the World Wide Web, and has incorporated extensions to address the needs of specialist communities (Guha, et al., 2016). It has been used with some success in cultural heritage sector through libraries and digital collections platforms using both Schema.org core types and properties, as well as SchemaBibExtend, an extension for bibliographic information (bib.schema.org, n.d.). These uses include leveraging it as a means to improve search engine rankings (Scott, 2014), to publish library staff directories (Clark and Young, 2017) and to expose linked data about collections materials (Lampron, et al., 2016). However, the adoption of Schema.org in the context of archives has been somewhat limited. Our project focuses on identifying pragmatic methods to publish linked data about archives, archival resources, and their relationships, and to identify gaps between existing models. -
Entity Linking with a Knowledge Base: Issues, Techniques, and Solutions Wei Shen, Jianyong Wang, Senior Member, IEEE, and Jiawei Han, Fellow, IEEE
1 Entity Linking with a Knowledge Base: Issues, Techniques, and Solutions Wei Shen, Jianyong Wang, Senior Member, IEEE, and Jiawei Han, Fellow, IEEE Abstract—The large number of potential applications from bridging Web data with knowledge bases have led to an increase in the entity linking research. Entity linking is the task to link entity mentions in text with their corresponding entities in a knowledge base. Potential applications include information extraction, information retrieval, and knowledge base population. However, this task is challenging due to name variations and entity ambiguity. In this survey, we present a thorough overview and analysis of the main approaches to entity linking, and discuss various applications, the evaluation of entity linking systems, and future directions. Index Terms—Entity linking, entity disambiguation, knowledge base F 1 INTRODUCTION Entity linking can facilitate many different tasks such as knowledge base population, question an- 1.1 Motivation swering, and information integration. As the world HE amount of Web data has increased exponen- evolves, new facts are generated and digitally ex- T tially and the Web has become one of the largest pressed on the Web. Therefore, enriching existing data repositories in the world in recent years. Plenty knowledge bases using new facts becomes increas- of data on the Web is in the form of natural language. ingly important. However, inserting newly extracted However, natural language is highly ambiguous, es- knowledge derived from the information extraction pecially with respect to the frequent occurrences of system into an existing knowledge base inevitably named entities. A named entity may have multiple needs a system to map an entity mention associated names and a name could denote several different with the extracted knowledge to the corresponding named entities. -
Data Extraction Using NLP Techniques and Its Transformation to Linked Data
Vincent Kríž, Barbora Hladká, Martin Nečaský, Tomáš Knap Data Extraction using NLP techniques and its Transformation to Linked Data MICAI 2014 Mexico, Tuxtla Gutiérrez Institute of Formal and Applied Linguistics Faculty of Mathematics and Physics Charles University in Prague [email protected] Czech Republic http://ufal.mff.cuni.cz/intlib Kríž, Hladká, Nečaský, Knap: Data Extraction using NLP techniques and its Transformation to Linked Data | MICAI2014 Motivation ● large collections of documents ● efficient browsing & querying ● typical approaches – full-text search no semantics – metadata search ● semantic interpretation of documents → suitable DB & query language → user-friendly browsing & querying Kríž, Hladká, Nečaský, Knap: Data Extraction using NLP techniques and its Transformation to Linked Data | MICAI2014 Scenario ● Cooperation between – Information Extraction – Semantic Web Kríž, Hladká, Nečaský, Knap: Data Extraction using NLP techniques and its Transformation to Linked Data | MICAI2014 Scenario ● Extracting knowledge base – set of entities and relations between them – linguistic analysis (RExtractor) ● Knowledge base representation – Linked Data Principles – Resource Description Framework (RDF) Kríž, Hladká, Nečaský, Knap: Data Extraction using NLP techniques and its Transformation to Linked Data | MICAI2014 Scenario ● Extracting knowledge base – set of entities and relations between them – linguistic analysis (RExtractor) ● Knowledge base representation – Linked Data Principles – Resource Description Framework (RDF) Kríž,