{"title":"协同科学工作流组合即服务:支持协同数据分析工作流设计和管理的基础设施","authors":"Jia Zhang, Q. Bao, Xiaoyi Duan, Shiyong Lu, Lijun Xue, Runyu Shi, P. Tang","doi":"10.1109/CIC.2016.039","DOIUrl":null,"url":null,"abstract":"The need for collaborative data analytics increases significantly when confronted with the challenges of big data. Although workflow tools offer a formal way to define, automate, and repeat multi-step computational procedures, designing complex data processing workflow requires collaboration from multiple people with complementary expertise. Existing tools are not suitable to support collaborative design of comprehensive workflows. To address such a challenge, this paper reports the design and development of a software infrastructure with the capability of supporting collaborative data-oriented workflow composition and management, adding a key component to existing cyberinfrastructure that will support big data collaboration through the Internet. A collaborative provenance query model (CPM) is presented together with graph-based patterns and algebra. A hypergraph theory-based provenance mining technique is reported. The research extends an existing open-source workflow tool, by adding system-level facilities to support human interaction and cooperation that are essential for an effective and efficient scientific collaboration.","PeriodicalId":438546,"journal":{"name":"2016 IEEE 2nd International Conference on Collaboration and Internet Computing (CIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Collaborative Scientific Workflow Composition as a Service: An Infrastructure Supporting Collaborative Data Analytics Workflow Design and Management\",\"authors\":\"Jia Zhang, Q. Bao, Xiaoyi Duan, Shiyong Lu, Lijun Xue, Runyu Shi, P. Tang\",\"doi\":\"10.1109/CIC.2016.039\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The need for collaborative data analytics increases significantly when confronted with the challenges of big data. Although workflow tools offer a formal way to define, automate, and repeat multi-step computational procedures, designing complex data processing workflow requires collaboration from multiple people with complementary expertise. Existing tools are not suitable to support collaborative design of comprehensive workflows. To address such a challenge, this paper reports the design and development of a software infrastructure with the capability of supporting collaborative data-oriented workflow composition and management, adding a key component to existing cyberinfrastructure that will support big data collaboration through the Internet. A collaborative provenance query model (CPM) is presented together with graph-based patterns and algebra. A hypergraph theory-based provenance mining technique is reported. The research extends an existing open-source workflow tool, by adding system-level facilities to support human interaction and cooperation that are essential for an effective and efficient scientific collaboration.\",\"PeriodicalId\":438546,\"journal\":{\"name\":\"2016 IEEE 2nd International Conference on Collaboration and Internet Computing (CIC)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE 2nd International Conference on Collaboration and Internet Computing (CIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIC.2016.039\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 2nd International Conference on Collaboration and Internet Computing (CIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIC.2016.039","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Collaborative Scientific Workflow Composition as a Service: An Infrastructure Supporting Collaborative Data Analytics Workflow Design and Management
The need for collaborative data analytics increases significantly when confronted with the challenges of big data. Although workflow tools offer a formal way to define, automate, and repeat multi-step computational procedures, designing complex data processing workflow requires collaboration from multiple people with complementary expertise. Existing tools are not suitable to support collaborative design of comprehensive workflows. To address such a challenge, this paper reports the design and development of a software infrastructure with the capability of supporting collaborative data-oriented workflow composition and management, adding a key component to existing cyberinfrastructure that will support big data collaboration through the Internet. A collaborative provenance query model (CPM) is presented together with graph-based patterns and algebra. A hypergraph theory-based provenance mining technique is reported. The research extends an existing open-source workflow tool, by adding system-level facilities to support human interaction and cooperation that are essential for an effective and efficient scientific collaboration.