Pub Date : 2015-01-15DOI: 10.7287/PEERJ.PREPRINTS.792V1
Martin Scharm, Dagmar Waltemath
The COMBINE archive is a digital container format for files related to a virtual experiment in computational biology. It eases the management of numerous files related to a simulation study, fosters collaboration, and ultimately enables the exchange of reproducible research results. The CombineArchive Toolkit is a software for creating, exploring, modifying, and sharing COMBINE archives. Open model repositories such as BioModels Database are a valuable resource of models and associated simulation descriptions. However, so far no tool exists to export COMBINE archives for a given simulation study from such databases. Here we demonstrate how the CombineArchive Toolkit can be used to extract reproducible simulation studies from model repositories. We use the example of Masymos, a graph database with a sophisticated link concept to connect model-related files on the storage layer.
{"title":"Extracting reproducible simulation studies from model repositories using the combinearchive toolkit","authors":"Martin Scharm, Dagmar Waltemath","doi":"10.7287/PEERJ.PREPRINTS.792V1","DOIUrl":"https://doi.org/10.7287/PEERJ.PREPRINTS.792V1","url":null,"abstract":"The COMBINE archive is a digital container format for files related to a virtual experiment in computational biology. It eases the management of numerous files related to a simulation study, fosters collaboration, and ultimately enables the exchange of reproducible research results. The CombineArchive Toolkit is a software for creating, exploring, modifying, and sharing COMBINE archives. Open model repositories such as BioModels Database are a valuable resource of models and associated simulation descriptions. However, so far no tool exists to export COMBINE archives for a given simulation study from such databases. Here we demonstrate how the CombineArchive Toolkit can be used to extract reproducible simulation studies from model repositories. We use the example of Masymos, a graph database with a sophisticated link concept to connect model-related files on the storage layer.","PeriodicalId":421643,"journal":{"name":"Datenbanksysteme für Business, Technologie und Web","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132614061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2010-05-26DOI: 10.1007/978-3-642-13073-1_1
R. Baeza-Yates
{"title":"Towards a Distributed Search Engine","authors":"R. Baeza-Yates","doi":"10.1007/978-3-642-13073-1_1","DOIUrl":"https://doi.org/10.1007/978-3-642-13073-1_1","url":null,"abstract":"","PeriodicalId":421643,"journal":{"name":"Datenbanksysteme für Business, Technologie und Web","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132953149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Peer data management systems (PDMS) are the natural extension of integrated information systems. Conventionally, a single integrating system manages an integrated schema, distributes queries to appropriate sources, and integrates incoming data to a common result. In contrast, a PDMS consists of a set of peers, each of which can play the role of an integrating component. A peer knows about its neighboring peers by mappings, which help to translate queries and transform data. Queries submitted to one peer are answered by data residing at that peer and by data that is reached along paths of mappings through the network of peers. The only restriction for PDMS to cover unbounded data is the need to formulate at least one mapping from some known peer to a new data source. We propose a Semantic Web based method that overcomes this restriction, albeit at a price. As sources are dynamically and automatically included in a PDMS, three factors diminish quality: The new source itself might store data of poor quality, the mapping to the PDMS might be incorrect, and the mapping to the PDMS might be incomplete. To compensate, we propose a quality model to measure this effect, a cost model to restrict query planning to the best paths through the PDMS, and techniques to answer queries in such Webscale PDMS efficiently. 1 An Ever-growing PDMS The step from centralized database systems (DBMS) to distributed and then to federated database systems (FDBMS) removed the assumption that data must be located at the same site as the query. A federated database provides a global schema that represents the data it can access locally and remotely. The global schema is related to the local schemata via schema mappings, which specify how the schema of a local database maps to the global schema. The federated database accepts a query against its global schema and distributes it according to the schema mappings to the different sites where the data resides. Those sites execute the partial queries and send results back to the requesting peer. Again, the schema mappings specify how data is to be translated to conform to the global schema. The results are further processed and combined to be finally fused into a single response to the user. A natural extension to this paradigm is to remove the assumption that queries are only asked against a single integrating site. Peer data management systems (PDMS) are built of multiple peers, each of which provides a schema and accepts queries against the schema. Again, the peers are connected by mappings among their schemata. However, instead of forming a tree with a single root, each peer can be connected to any number of other peers. Queries against a schema of one peer can be answered using the data of the entire PDMS, as long as appropriate mappings have been formed (see Fig. 1). In general, a query
{"title":"Self-Extending Peer Data Management","authors":"Ralf Heese, Sven Herschel, Felix Naumann, A. Roth","doi":"10.18452/9200","DOIUrl":"https://doi.org/10.18452/9200","url":null,"abstract":"Peer data management systems (PDMS) are the natural extension of integrated information systems. Conventionally, a single integrating system manages an integrated schema, distributes queries to appropriate sources, and integrates incoming data to a common result. In contrast, a PDMS consists of a set of peers, each of which can play the role of an integrating component. A peer knows about its neighboring peers by mappings, which help to translate queries and transform data. Queries submitted to one peer are answered by data residing at that peer and by data that is reached along paths of mappings through the network of peers. The only restriction for PDMS to cover unbounded data is the need to formulate at least one mapping from some known peer to a new data source. We propose a Semantic Web based method that overcomes this restriction, albeit at a price. As sources are dynamically and automatically included in a PDMS, three factors diminish quality: The new source itself might store data of poor quality, the mapping to the PDMS might be incorrect, and the mapping to the PDMS might be incomplete. To compensate, we propose a quality model to measure this effect, a cost model to restrict query planning to the best paths through the PDMS, and techniques to answer queries in such Webscale PDMS efficiently. 1 An Ever-growing PDMS The step from centralized database systems (DBMS) to distributed and then to federated database systems (FDBMS) removed the assumption that data must be located at the same site as the query. A federated database provides a global schema that represents the data it can access locally and remotely. The global schema is related to the local schemata via schema mappings, which specify how the schema of a local database maps to the global schema. The federated database accepts a query against its global schema and distributes it according to the schema mappings to the different sites where the data resides. Those sites execute the partial queries and send results back to the requesting peer. Again, the schema mappings specify how data is to be translated to conform to the global schema. The results are further processed and combined to be finally fused into a single response to the user. A natural extension to this paradigm is to remove the assumption that queries are only asked against a single integrating site. Peer data management systems (PDMS) are built of multiple peers, each of which provides a schema and accepts queries against the schema. Again, the peers are connected by mappings among their schemata. However, instead of forming a tree with a single root, each peer can be connected to any number of other peers. Queries against a schema of one peer can be answered using the data of the entire PDMS, as long as appropriate mappings have been formed (see Fig. 1). In general, a query","PeriodicalId":421643,"journal":{"name":"Datenbanksysteme für Business, Technologie und Web","volume":"149 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115858569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2001-03-07DOI: 10.1007/978-3-642-56687-5_5
T. Bauer, M. Reichert, P. Dadam
{"title":"Adaptives und verteiltes Workflow-Management","authors":"T. Bauer, M. Reichert, P. Dadam","doi":"10.1007/978-3-642-56687-5_5","DOIUrl":"https://doi.org/10.1007/978-3-642-56687-5_5","url":null,"abstract":"","PeriodicalId":421643,"journal":{"name":"Datenbanksysteme für Business, Technologie und Web","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120967537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2001-03-07DOI: 10.1007/978-3-642-56687-5_35
A. Bernhardt, S. Benner, Frank Pollmann
{"title":"DARWIN - Ein Data Warehouse Projekt der Deutschen Telekom AG","authors":"A. Bernhardt, S. Benner, Frank Pollmann","doi":"10.1007/978-3-642-56687-5_35","DOIUrl":"https://doi.org/10.1007/978-3-642-56687-5_35","url":null,"abstract":"","PeriodicalId":421643,"journal":{"name":"Datenbanksysteme für Business, Technologie und Web","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121239947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2001-03-07DOI: 10.1007/978-3-642-56687-5_10
Markus Keidl, Alexander Kreutz, Alfons Kemper, Donald Kossmann
{"title":"Verteilte Metadatenverwaltung für die Anfragebearbeitung auf Internet-Datenquellen","authors":"Markus Keidl, Alexander Kreutz, Alfons Kemper, Donald Kossmann","doi":"10.1007/978-3-642-56687-5_10","DOIUrl":"https://doi.org/10.1007/978-3-642-56687-5_10","url":null,"abstract":"","PeriodicalId":421643,"journal":{"name":"Datenbanksysteme für Business, Technologie und Web","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128286815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2001-03-07DOI: 10.1007/978-3-642-56687-5_13
Ruxandra Domenig, K. Dittrich
{"title":"Query preprocessing for integrated search in heterogeneous data sources","authors":"Ruxandra Domenig, K. Dittrich","doi":"10.1007/978-3-642-56687-5_13","DOIUrl":"https://doi.org/10.1007/978-3-642-56687-5_13","url":null,"abstract":"","PeriodicalId":421643,"journal":{"name":"Datenbanksysteme für Business, Technologie und Web","volume":"84 Pt 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129038741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2001-03-07DOI: 10.1007/978-3-642-56687-5_32
Achim Kraiss
{"title":"Hierarchische Speicherverwaltung für Informationssysteme mit Tertiärspeicher","authors":"Achim Kraiss","doi":"10.1007/978-3-642-56687-5_32","DOIUrl":"https://doi.org/10.1007/978-3-642-56687-5_32","url":null,"abstract":"","PeriodicalId":421643,"journal":{"name":"Datenbanksysteme für Business, Technologie und Web","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115653744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2001-03-07DOI: 10.1007/978-3-642-56687-5_4
Susanne Busse, C. Pons
{"title":"Schema Evolution in Federated Information Systems","authors":"Susanne Busse, C. Pons","doi":"10.1007/978-3-642-56687-5_4","DOIUrl":"https://doi.org/10.1007/978-3-642-56687-5_4","url":null,"abstract":"","PeriodicalId":421643,"journal":{"name":"Datenbanksysteme für Business, Technologie und Web","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130697240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2001-03-07DOI: 10.1007/978-3-642-56687-5_20
Timo Böhme, E. Rahm
{"title":"XMach-1: A Benchmark for XML Data Management","authors":"Timo Böhme, E. Rahm","doi":"10.1007/978-3-642-56687-5_20","DOIUrl":"https://doi.org/10.1007/978-3-642-56687-5_20","url":null,"abstract":"","PeriodicalId":421643,"journal":{"name":"Datenbanksysteme für Business, Technologie und Web","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126887160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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