Pub Date : 2023-10-30DOI: 10.1007/s13222-023-00460-3
Alex El-Shaikh, Bernhard Seeger
Abstract Over the past decade, DNA has emerged as a new storage medium with intriguing data volume and durability capabilities. Despite its advantages, DNA storage also has crucial limitations, such as intricate data access interfaces and restricted random accessibility. To overcome these limitations, DNAContainer has been introduced with a novel storage interface for DNA that spans a very large virtual address space on objects and allows random access to DNA at scale. In this paper, we substantially improve the first version of DNAContainer, focusing on the update capabilities of its data structures and optimizing its memory footprint. In addition, we extend the previous set of experiments on DNAContainer with new ones whose results reveal the impact of essential parameters on the performance and memory footprint.
{"title":"An Extension of DNAContainer with a Small Memory Footprint","authors":"Alex El-Shaikh, Bernhard Seeger","doi":"10.1007/s13222-023-00460-3","DOIUrl":"https://doi.org/10.1007/s13222-023-00460-3","url":null,"abstract":"Abstract Over the past decade, DNA has emerged as a new storage medium with intriguing data volume and durability capabilities. Despite its advantages, DNA storage also has crucial limitations, such as intricate data access interfaces and restricted random accessibility. To overcome these limitations, DNAContainer has been introduced with a novel storage interface for DNA that spans a very large virtual address space on objects and allows random access to DNA at scale. In this paper, we substantially improve the first version of DNAContainer, focusing on the update capabilities of its data structures and optimizing its memory footprint. In addition, we extend the previous set of experiments on DNAContainer with new ones whose results reveal the impact of essential parameters on the performance and memory footprint.","PeriodicalId":72771,"journal":{"name":"Datenbank-Spektrum : Zeitschrift fur Datenbanktechnologie : Organ der Fachgruppe Datenbanken der Gesellschaft fur Informatik e.V","volume":"231 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136102931","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 : 2023-10-16DOI: 10.1007/s13222-023-00457-y
Sven Langenecker, Christoph Sturm, Christian Schalles, Carsten Binnig
Abstract Table corpora such as VizNet or TURL which contain annotated semantic types per column are important to build machine learning models for the task of automatic semantic type detection. However, there is a huge discrepancy between corpora and real-world data lakes since they contain a huge fraction of numerical data which are not present in existing corpora. Hence, in this paper, we introduce a new corpus that contains a much higher proportion of numerical columns than existing corpora. To reflect the distribution in real-world data lakes, our corpus SportsTables has on average approx. 86% numerical columns, posing new challenges to existing semantic type detection models which have mainly targeted non-numerical columns so far. To demonstrate this effect, we show in this extended version paper of [18] the results of an extensive study using four different state-of-the-art approaches for semantic type detection on our new corpus. Overall, the results demonstrate significant performance differences in predicting semantic types for textual and numerical data.
{"title":"SportsTables: A New Corpus for Semantic Type Detection (Extended Version)","authors":"Sven Langenecker, Christoph Sturm, Christian Schalles, Carsten Binnig","doi":"10.1007/s13222-023-00457-y","DOIUrl":"https://doi.org/10.1007/s13222-023-00457-y","url":null,"abstract":"Abstract Table corpora such as VizNet or TURL which contain annotated semantic types per column are important to build machine learning models for the task of automatic semantic type detection. However, there is a huge discrepancy between corpora and real-world data lakes since they contain a huge fraction of numerical data which are not present in existing corpora. Hence, in this paper, we introduce a new corpus that contains a much higher proportion of numerical columns than existing corpora. To reflect the distribution in real-world data lakes, our corpus SportsTables has on average approx. 86% numerical columns, posing new challenges to existing semantic type detection models which have mainly targeted non-numerical columns so far. To demonstrate this effect, we show in this extended version paper of [18] the results of an extensive study using four different state-of-the-art approaches for semantic type detection on our new corpus. Overall, the results demonstrate significant performance differences in predicting semantic types for textual and numerical data.","PeriodicalId":72771,"journal":{"name":"Datenbank-Spektrum : Zeitschrift fur Datenbanktechnologie : Organ der Fachgruppe Datenbanken der Gesellschaft fur Informatik e.V","volume":"223 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136115593","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 : 2023-10-13DOI: 10.1007/s13222-023-00458-x
{"title":"Dissertationen","authors":"","doi":"10.1007/s13222-023-00458-x","DOIUrl":"https://doi.org/10.1007/s13222-023-00458-x","url":null,"abstract":"","PeriodicalId":72771,"journal":{"name":"Datenbank-Spektrum : Zeitschrift fur Datenbanktechnologie : Organ der Fachgruppe Datenbanken der Gesellschaft fur Informatik e.V","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135858367","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 : 2023-10-10DOI: 10.1007/s13222-023-00456-z
Alexander Baumstark, Muhammad Attahir Jibril, Kai-Uwe Sattler
Abstract Today’s systems are capable of storing large amounts of data in main memory. Particularly, in-memory DBMSs benefit from this development. However, the processing of data from the main memory necessarily has to run via the CPU. This creates a bottleneck, which affects the possible performance of the DBMS. Processing-In-Memory (PIM) is a paradigm to overcome this problem, which was not available in commercial systems for a long time. With the availability of UPMEM, a commercial product is finally available that provides PIM technology in hardware. In this work, we focus on the acceleration of the table scan, a fundamental database query operation. We show and investigate an approach that can be used to optimize this operation by using PIM. We evaluate the PIM scan in terms of parallelism and execution time in benchmarks with different table sizes and compare it to a traditional CPU-based table scan. The result is a PIM table scan that outperforms the CPU-based scan significantly.
{"title":"Accelerating Large Table Scan Using Processing-In-Memory Technology","authors":"Alexander Baumstark, Muhammad Attahir Jibril, Kai-Uwe Sattler","doi":"10.1007/s13222-023-00456-z","DOIUrl":"https://doi.org/10.1007/s13222-023-00456-z","url":null,"abstract":"Abstract Today’s systems are capable of storing large amounts of data in main memory. Particularly, in-memory DBMSs benefit from this development. However, the processing of data from the main memory necessarily has to run via the CPU. This creates a bottleneck, which affects the possible performance of the DBMS. Processing-In-Memory (PIM) is a paradigm to overcome this problem, which was not available in commercial systems for a long time. With the availability of UPMEM, a commercial product is finally available that provides PIM technology in hardware. In this work, we focus on the acceleration of the table scan, a fundamental database query operation. We show and investigate an approach that can be used to optimize this operation by using PIM. We evaluate the PIM scan in terms of parallelism and execution time in benchmarks with different table sizes and compare it to a traditional CPU-based table scan. The result is a PIM table scan that outperforms the CPU-based scan significantly.","PeriodicalId":72771,"journal":{"name":"Datenbank-Spektrum : Zeitschrift fur Datenbanktechnologie : Organ der Fachgruppe Datenbanken der Gesellschaft fur Informatik e.V","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136294585","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 : 2023-09-18DOI: 10.1007/s13222-023-00453-2
Christian Beilschmidt, Johannes Drönner, Michael Mattig, Bernhard Seeger
Geo data portals play a key role in the distribution and exploitation of domain-specific geo data. While such portals are highly specialized, they share a number of common requirements that span from data access and processing to UI components. Geo Engine is able to provide all the necessary parts for portal building. We demonstrate this on a real data portal we built for the dragonfly community and on a Data Science application. In addition, we show its general architecture and outline future improvements.
{"title":"Geo Engine: Workflow-driven Geospatial Portals for Data Science","authors":"Christian Beilschmidt, Johannes Drönner, Michael Mattig, Bernhard Seeger","doi":"10.1007/s13222-023-00453-2","DOIUrl":"https://doi.org/10.1007/s13222-023-00453-2","url":null,"abstract":"Geo data portals play a key role in the distribution and exploitation of domain-specific geo data. While such portals are highly specialized, they share a number of common requirements that span from data access and processing to UI components. Geo Engine is able to provide all the necessary parts for portal building. We demonstrate this on a real data portal we built for the dragonfly community and on a Data Science application. In addition, we show its general architecture and outline future improvements.","PeriodicalId":72771,"journal":{"name":"Datenbank-Spektrum : Zeitschrift fur Datenbanktechnologie : Organ der Fachgruppe Datenbanken der Gesellschaft fur Informatik e.V","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135153496","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 : 2023-09-11DOI: 10.1007/s13222-023-00454-1
Elena Volkanovska, Sherry Tan, Changxu Duan, Sabine Bartsch, Wolfgang Stille
Abstract The discourse on climate change has become a centerpiece of public debate, thereby creating a pressing need to analyze the multitude of messages created by the participants in this communication process. In addition to text, information on this topic is conveyed multimodally, through images, videos, tables and other data objects that are embedded within documents and accompany the text. This paper presents the process of building a multimodal pilot corpus to the InsightsNet Climate Change Corpus (ICCC) and using natural language processing (NLP) tools to enrich corpus (meta)data, thus creating a dataset that lends itself to the exploration of the interplay between the various modalities that constitute the discourse on climate change. We demonstrate how the pilot corpus can be queried for relevant information in two types of databases, and how the proposed data model promotes a more comprehensive sentiment analysis approach.
{"title":"The InsightsNet Climate Change Corpus (ICCC)","authors":"Elena Volkanovska, Sherry Tan, Changxu Duan, Sabine Bartsch, Wolfgang Stille","doi":"10.1007/s13222-023-00454-1","DOIUrl":"https://doi.org/10.1007/s13222-023-00454-1","url":null,"abstract":"Abstract The discourse on climate change has become a centerpiece of public debate, thereby creating a pressing need to analyze the multitude of messages created by the participants in this communication process. In addition to text, information on this topic is conveyed multimodally, through images, videos, tables and other data objects that are embedded within documents and accompany the text. This paper presents the process of building a multimodal pilot corpus to the InsightsNet Climate Change Corpus (ICCC) and using natural language processing (NLP) tools to enrich corpus (meta)data, thus creating a dataset that lends itself to the exploration of the interplay between the various modalities that constitute the discourse on climate change. We demonstrate how the pilot corpus can be queried for relevant information in two types of databases, and how the proposed data model promotes a more comprehensive sentiment analysis approach.","PeriodicalId":72771,"journal":{"name":"Datenbank-Spektrum : Zeitschrift fur Datenbanktechnologie : Organ der Fachgruppe Datenbanken der Gesellschaft fur Informatik e.V","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135982535","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 : 2023-07-12DOI: 10.1007/s13222-023-00446-1
Michael Beurskens, Stefanie Scherzinger
{"title":"Datenbankherstellerrecht und Datenbankforschung","authors":"Michael Beurskens, Stefanie Scherzinger","doi":"10.1007/s13222-023-00446-1","DOIUrl":"https://doi.org/10.1007/s13222-023-00446-1","url":null,"abstract":"","PeriodicalId":72771,"journal":{"name":"Datenbank-Spektrum : Zeitschrift fur Datenbanktechnologie : Organ der Fachgruppe Datenbanken der Gesellschaft fur Informatik e.V","volume":"115 1","pages":"143-152"},"PeriodicalIF":0.0,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80560222","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 : 2023-07-01DOI: 10.1007/s13222-023-00447-0
Wolfgang Lehner
{"title":"Datenbank-Community vernetzt sich in Dresden","authors":"Wolfgang Lehner","doi":"10.1007/s13222-023-00447-0","DOIUrl":"https://doi.org/10.1007/s13222-023-00447-0","url":null,"abstract":"","PeriodicalId":72771,"journal":{"name":"Datenbank-Spektrum : Zeitschrift fur Datenbanktechnologie : Organ der Fachgruppe Datenbanken der Gesellschaft fur Informatik e.V","volume":"29 1","pages":"153-158"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88291927","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 : 2023-06-30DOI: 10.1007/s13222-023-00449-y
Carsten Gröger
{"title":"Steuerrechtliche Herausforderungen datengetriebener Geschäftsmodelle am Beispiel des Connected-Car-Geschäftsmodells","authors":"Carsten Gröger","doi":"10.1007/s13222-023-00449-y","DOIUrl":"https://doi.org/10.1007/s13222-023-00449-y","url":null,"abstract":"","PeriodicalId":72771,"journal":{"name":"Datenbank-Spektrum : Zeitschrift fur Datenbanktechnologie : Organ der Fachgruppe Datenbanken der Gesellschaft fur Informatik e.V","volume":"99 1","pages":"133-142"},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90064809","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 : 2023-06-30DOI: 10.1007/s13222-023-00450-5
Corinna Giebler, Eva Hoos
{"title":"A Systematic Approach to Consuming Data in Complex Data Management Landscapes Using Data Consumption Patterns","authors":"Corinna Giebler, Eva Hoos","doi":"10.1007/s13222-023-00450-5","DOIUrl":"https://doi.org/10.1007/s13222-023-00450-5","url":null,"abstract":"","PeriodicalId":72771,"journal":{"name":"Datenbank-Spektrum : Zeitschrift fur Datenbanktechnologie : Organ der Fachgruppe Datenbanken der Gesellschaft fur Informatik e.V","volume":"55 1","pages":"117-122"},"PeriodicalIF":0.0,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74588244","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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