Towards a Domain-Specific Language for geospatial data visualization maps with Big Data sets

2015 ◽  
Author(s):  
Cleverson Ledur ◽  
Dalvan Griebler ◽  
Isabel Manssour ◽  
Luiz Gustavo Fernandes
Keyword(s):  
Big Data ◽  
Data Visualization ◽  
Geospatial Data ◽  
Domain Specific Language ◽  
Data Sets ◽  
Specific Language ◽  
Domain Specific

scholarly journals Consortial Geospatial Data Collection: Toward Standards and Processes for Shared GeoBlacklight Metadata

2018 ◽  
Author(s):  
Andrew Battista ◽  
Karen Majewicz
Keyword(s):  
Quality Control ◽  
Best Practices ◽  
Geospatial Data ◽  
Domain Specific Language ◽  
Specific Language ◽  
Domain Specific ◽  
Metadata Quality ◽  
Human Labor ◽  
Geospatial Metadata ◽  
Geospatial Data Collection

Consortial geospatial data communities, such as the OpenGeoPortal federation and the GeoBlacklight initiative, facilitate contextualized discovery and promote metadata sharing to disperse hosting and preservation responsibilities across institutions. However, the challenges of communal metadata are manifold; they include proliferating standards, varying levels of completeness, mutable technology infrastructures, and uneven availability of human labor. Drawing from literature on metadata quality control, we outline a procedure for “scoring” GeoBlacklight records to establish a Domain Specific Language for metadata best practices. We propose strategies for authorship and management conducive to functionally interoperable geospatial metadata, that is versioned and enhanceable by the collective.

scholarly journals ПРОСТОРНО - ВРЕМЕНСКИ ТИПОВИ И АНАЛИЗЕ ПОДАТАКА У BIG DATA ПАРАДИГМИ

AГГ+ ◽  
2015 ◽  
Vol 1 (3) ◽  
Author(s):  
Младен Амовић ◽  
Миро Говедарица ◽  
Владимир Пајић ◽  
Славко Васиљевић
Keyword(s):  
Big Data ◽  
Open Source ◽  
Apache Spark ◽  
Domain Specific Language ◽  
Specific Language ◽  
Domain Specific

Модел за управљање великим серијама просторно-временских података имплементиран је на Apache Spark open-source платформи за складиштење и обраду великих серија података на дистрибуираним рачунарским системима формираним од комерцијално доступних радних станица. Алгоритми за обраду просторно-временских података су дефинисани према правилима Spark SQL програмског модела, а релационе операције на DataFrame-овима (специјализованим системом оквира података) коришћењем специфичног језика домена (domain – specific – language → DSL). Увођењем просторно-временских типова података омогућава се стандардизован приступ у Big Data парадигми.

scholarly journals Efficient Search Mechanism from Large Scale Corpora for Domain-Specific Language Modeling in Speech Recognition

2019 ◽  
Vol 8 (6) ◽  
pp. 1682-1689
Keyword(s):  
Big Data ◽  
Speech Recognition ◽  
Language Model ◽  
Search Space ◽  
Document Retrieval ◽  
Language Modeling ◽  
Domain Specific Language ◽  
Specific Language ◽  
Recognition Process ◽  
Domain Specific

With the Internet and the World Wide Web revolution, large corpora in variety of forms are germinating ceaselessly that can be manifested as big data. One obligatory area for the usage of such large corpora is language modeling for large vocabulary continuous speech recognition. Language modeling is an indispensable module in speech recognition architecture, which plays a vital role in reducing the search space during the recognition process. Additionally, the language model that is contiguous to the domain of the speech can dwindle the search space and escalate the recognition accuracy. In this paper, an efficient searching mechanism for domain-specific document retrieval from the large corpora has been elucidated using Elasticsearch which is a distributed and an efficient search engine for big data. This assisted us in tuning the language model in accordance with the domain and also by reducing the search time by more than 90% in comparison to conventional search and retrieval mechanism used in our earlier work. A word level and a phrase level retrieval process for creating domain-specific language model has been implemented. The evaluation of the system is performed on the basis of word error rate (WER) and perplexity (PPL) of the speech recognition system. The results shows nearly 10% decrease on WER and a major reduction in the PPL that helped in boosting the performance of the speech recognition process. From the results, it can be consummated that Elasticsearch is an efficient mechanism for domain specific document retrieval from large corpora rather than using topic modeling toolkits

Domain-Specific Language Abstractions for Compression

2021 ◽  
Author(s):  
Jessica Ray ◽  
Ajav Brahmakshatriya ◽  
Richard Wang ◽  
Shoaib Kamil ◽  
Albert Reuther ◽  
...  
Keyword(s):  
Domain Specific Language ◽  
Specific Language ◽  
Domain Specific
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