[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-117341-en":3,"doc-seo-117341-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},117341,1099514068035,"Ezra","https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c",8,"Research & Report","A Declarative Query Language for Scientific Machine Learning","Data science’s growing importance and industrial impact require machine learning to be accessible to broader communities, not only specialists. Current workforce training and ML frameworks depend on low-level statistical and algorithmic details, creating a high barrier for scientists with limited computational background. This work proposes MQL, a declarative query language inspired by SQL, to express prediction, classification, and clustering at a conceptual level. It also outlines implementation over relational databases and demonstrates materials science experiments using MQL on MatFlow.","A Declarative Query Language for Scientific Machine Learning  \nHasan M. Jamil  \nUniversity of Idaho, USA  \n[jamil@uidaho.edu](jamil@uidaho.edu)  \narXiv :2405 . 16159v1 [ cs .LG] 25 May 2024  \nABSTRACT  \nThe popularity of data science as a discipline and its importance in the emerging economy and industrial progress dictate that machine learning be democratized for the masses. This also means that the current practice of workforce training using machine learning tools, which requires low-level statistical and algorithmic details, is a barrier that needs to be addressed. Similar to data management languages such as SQL, machine learning needs to be practiced ata conceptual level to help make it a staple tool for general users. In particular, the technical sophistication demanded by existing machine learning frameworks is prohibitive for many scientists who are not computationally savvy or well versed in machine learning techniques. The learning curve to use the needed machine learning tools is also too high for them to take advantage of these powerful platforms to rapidly advance science. In this paper, we introduce a new declarative machine learning query language, called MQL, for naive users. We discuss its merit and possible ways of implementing it over a traditional relational database system. We discuss two materials science experiments implemented using MQL on a materials science workflow system called MatFlow.  \nCCS CONCEPTS  \n• Computing methodologies → Machine learning; Artificial intelligence; • Information systems → Query languages; Database design and models; • Human-centered computing;  \nKEYWORDS  \nTranslational semantics, declarative query language.  \nACM Reference Format:  \nHasan M. Jamil. 2024. A Declarative Query Language for Scientific Machine Learning. In Proceedings of ACM Conference (Conference’17) . ACM, New York, NY, USA, Article 4, 12 pages. [https://doi.org/10.1145/xxxxxxxxxx](https://doi.org/10.1145/xxxxxxxxxx)  \n1 INTRODUCTION  \nIn this paper, we ask the question, how difficult it is to design a declarative query language for machine learning (ML) analysis by pointing to how difficult and arcane it is to write code segments in popular ML platforms such as SciKit-Learn, Pytorch, R or TensorFlow by non ML experts? By declarative, we mean that ifa language for ML that is as simple and as powerful as SQL can be designed,  \nPermission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions [from permissions@acm.org](from permissions@acm.org).  \nConference’17, July 2017, Washington, DC, USA © 2024 Association for Computing Machinery.  \nACM ISBN xxxxxxxxxxxx. . . $15.00 [https://doi.org/10.1145/xxxxxxxxxx](https://doi.org/10.1145/xxxxxxxxxx)  \ncan it perform the most complex analysis a modern ML algorithm can?  \nThe current state of ML is not accessible to most of potential users of data science [29], scientists in particular, and we concur with many researchers who believe that a significant barrier exists towards exploiting ML without a declarative platform [47] . In the absence of a language similar to SQL, it is extremely difficult and unlikely for naive users and scientists alike to comprehend, let alone devise, a simple regression analysis code fragment easily executable on a machine. For example, the process to perform a clustering analysis [55] (or classification [46]) on the Boston housing dataset on Kaggle [50] is by no means an easy task even for a good computational scientist, without adequate proficiency in regression anal","cbCaiiTj5bsKAMLR","https://ap.wps.com/l/cbCaiiTj5bsKAMLR","pdf",1040267,1,12,"English","en",105,"# Abstract\n# Introduction\n## Access barrier for machine learning in practice\n## Goal: declarative SQL-like querying for ML\n## Proposed solution: MQL and its task coverage","[{\"question\":\"What problem does the paper address in scientific machine learning adoption?\",\"answer\":\"The paper argues that existing ML training and tools require low-level statistical and algorithmic details, making them difficult for non–computationally savvy scientists to use effectively.\"},{\"question\":\"What is MQL and what tasks does it support?\",\"answer\":\"MQL is a declarative machine learning query language. It is designed to support three core ML task classes: prediction, classification, and clustering.\"},{\"question\":\"How does the paper suggest implementing MQL?\",\"answer\":\"It discusses ways to implement MQL over a traditional relational database system and considers how a query processor could handle optimization and analysis selection similar to SQL engines.\"}]","A Declarative Query Language for Scientific Machine Learning | PDF",1785675273,30,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"a-declarative-query-language-for-scientific-machine-learning","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/a-declarative-query-language-for-scientific-machine-learning/117341/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-02",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What problem does the paper address in scientific machine learning adoption?","Question",{"text":75,"@type":76},"The paper argues that existing ML training and tools require low-level statistical and algorithmic details, making them difficult for non–computationally savvy scientists to use effectively.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What is MQL and what tasks does it support?",{"text":80,"@type":76},"MQL is a declarative machine learning query language. 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