Wikipedia:Articles for deletion/MashQL

The following discussion is an archived debate of the proposed deletion of the article below. Please do not modify it. Subsequent comments should be made on the appropriate discussion page (such as the article's talk page or in a deletion review). No further edits should be made to this page.

The result was merge to SPARQL. (non-admin closure) (t · c) buidhe 04:50, 15 July 2020 (UTC)[reply]

MashQL[edit]

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Exists, but doesn't meet WP:NOTABILITY. Boleyn (talk) 16:14, 21 June 2020 (UTC)[reply]

Note: This discussion has been included in the list of Computing-related deletion discussions. Shellwood (talk) 20:55, 21 June 2020 (UTC)[reply]

Delete Eleven years of collecting tags on Wikipedia seems to be about the most notable thing this has got going for it. Mccapra (talk) 06:46, 28 June 2020 (UTC)[reply]

*Delete per above. Does not meet WP:GNG. Red Phoenix ^talk 12:01, 29 June 2020 (UTC)[reply]

Keep per the significant coverage in multiple independent reliable sources.

Sumalatha, M.R.; Parvathy, M. (2013). "Keyword Search Retrieval for Structured Data using RDF for E-Learning Application". 2013 Fifth International Conference on Advanced Computing (ICoAC). Institute of Electrical and Electronics Engineers. doi:10.1109/ICoAC.2013.6921959. Retrieved 2020-06-29.
Kalou, Aikaterini K.; Koutsomitropoulos, Dimitrios A. (2016). "Chapter 31: Towards Semantic Mashups: Tools, Methodologies, and State of the Art". Mobile Computing and Wireless Networks: Concepts, Methodologies, Tools, and Applications: Concepts, Methodologies, Tools, and Applications. Hershey, Pennsylvania: Information Resources Management Association. pp. 712–713. ISBN 978-1-4666-8751-6. Retrieved 2020-06-29.
Medhe, Shrutika; Phalke, D.A. (2013). "RDF data retrieval in structured format using aggregate function and keyword search in MashQL". Third International Conference on Computational Intelligence and Information Technology. Institution of Engineering and Technology: 287–294. doi:10.1049/cp.2013.2604. Retrieved 2020-06-29.
Nguyen, Thanh; Nguyen, Dung T.; Cao, Thi H. (2014). "Acceptance and Use of Information System: E-Learning Based on Cloud Computing in Vietnam". In Neuhold, Erich J.; Tjoa, A Min; You, Ilsun (eds.). Information and Communication Technology: Second IFIP TC 5/8 International Conference, ICT-EurAsia 2014, Bali, Indonesia, April 14-17, 2014, Proceedings. Berlin: Springer Berlin Heidelberg. pp. 134–135. ISBN 978-3-642-55031-7. Retrieved 2020-06-29.

Sources with quotes

Sumalatha, M.R.; Parvathy, M. (2013). "Keyword Search Retrieval for Structured Data using RDF for E-Learning Application". 2013 Fifth International Conference on Advanced Computing (ICoAC). Institute of Electrical and Electronics Engineers. doi:10.1109/ICoAC.2013.6921959. Retrieved 2020-06-29.
The abstract notes:
E-learning is an interactive learning system with a computer through Internet connection. The retrieval of book details by e-learning users is generally difficult, since those data are structured. The structured data face the challenging issues in retrieval process. The schema of the data is not known to the user in order to query, which is also user friendly to the end users. Here E-Iearning materials may be schema-free or poorly-schematized. In this proposed work, a graphical query formulation language, called MashQL, is used in order to easily query structured data in E-Iearning application. Even, when the end users have limited technical background they can query and explore multiple data sources. This is the main significance of MashQL. This work aims in introducing semantic keyword search to retrieve the structured data.
Kalou, Aikaterini K.; Koutsomitropoulos, Dimitrios A. (2016). "Chapter 31: Towards Semantic Mashups: Tools, Methodologies, and State of the Art". Mobile Computing and Wireless Networks: Concepts, Methodologies, Tools, and Applications: Concepts, Methodologies, Tools, and Applications. Hershey, Pennsylvania: Information Resources Management Association. pp. 712–713. ISBN 978-1-4666-8751-6. Retrieved 2020-06-29.
The book notes:
MashQL

The remarkable success of Yahoo Pipes (Jarrar & Dikaiakos, 2008, Le Phuoc, Polleres, Morbidoni, Hauswirth, & Tummarello, 2009) in regard to other mashup editors motivated Jarrar et al (Jarrar & Dikaiakos, 2008) to propose MashQL, an interactive query formulation language. The idea of combining different data sources into mashups, in a graphical and user-friendly way without having to write code, as proposed by Yahoo Pipes application, was adopted by the inspirators of MashQL. So, the goal of MashQL is to enable non-experienced end-users to create their data mashups diagrammatically.
The main assumptions that have been made are that Internet is supposed to be a database and each internet data source is seen as a table and represented in RDF. Next, a mashup is considered as a query on these tables and the query is expressed by SPARQL. The novelty of MashQL is that no knowledge about RDF/SPARQL technologies nor any prior understanding of the schema or the structure of the consumed source are required in order to create the mashup.
Medhe, Shrutika; Phalke, D.A. (2013). "RDF data retrieval in structured format using aggregate function and keyword search in MashQL". Third International Conference on Computational Intelligence and Information Technology. Institution of Engineering and Technology: 287–294. doi:10.1049/cp.2013.2604. Retrieved 2020-06-29.
The abstract notes:
In this paper we refer the method to retrieve the web data in structured format using MashQL approach with the help of SPARQL language which allows user to query, navigate, and mash-up a data source(s) without knowing schema and how the data is stored into the database. Assuming web data as input in RDF format used to represent the metadata of the Web applications in structured manner. We can query by using SPARQL language which is the recent recommendation by the W3C.
By using this approach we mentioned how user having less technical knowledge is able to retrieve the data in structured format using drop down operations and interactive methods. We mentioned that how retrieval results will be faster by providing keyword search and then use MashQL approach. We also mentioned an aggregate function (e.g. sum, avg, max etc) in MashQL so user can perform a calculation on a set of values and return a single value.
Nguyen, Thanh; Nguyen, Dung T.; Cao, Thi H. (2014). "Acceptance and Use of Information System: E-Learning Based on Cloud Computing in Vietnam". In Neuhold, Erich J.; Tjoa, A Min; You, Ilsun (eds.). Information and Communication Technology: Second IFIP TC 5/8 International Conference, ICT-EurAsia 2014, Bali, Indonesia, April 14-17, 2014, Proceedings. Berlin: Springer Berlin Heidelberg. pp. 134–135. ISBN 978-3-642-55031-7. Retrieved 2020-06-29.
The book notes:
MashQL

This tool enables users to exploit the benefits of Web of Data without prior knowledge of semantic web technologies such as RDF and SPARQL. By using the query-by diagram paradigm, it allows users to query and mash up a massive amount of structured data on the web intuitively.
The core element of MashQL system is a visual editor that processes the input data and generate the required output. Here, the users merely choose the attributes of input concepts that should appear in the widgets output. It also enables the users to filter data with some arithmetic and relational operators for string and numeric attributes. The widget output can then be piped as a new input for other MashQL widgets and mashed up with other data inputs as shown in Fig. 4. The system then translates this process into a SPARQL query which is transparent to the users.

There is sufficient coverage in reliable sources to allow MashQL to pass Wikipedia:Notability#General notability guideline, which requires "significant coverage in reliable sources that are independent of the subject".

Cunard (talk) 18:37, 29 June 2020 (UTC)[reply]

Relisted to generate a more thorough discussion and clearer consensus.
Please add new comments below this notice. Thanks, MBisanz ^talk 03:46, 30 June 2020 (UTC)[reply]

Interesting refs Cunard has turned up. I couldn’t find those at all on a WP:BEFORE, but I had not considered that more scholarly material might exist. I have stricken my delete !vote for now, and may consider a keep !vote upon further review. Red Phoenix ^talk 13:27, 30 June 2020 (UTC)[reply]

Merge into SPARQL. The existence of the technology is of interest to people in SPARQL, but I don't think the refs Cunard has found will sustain a strong article. — Charles Stewart (talk) 18:14, 6 July 2020 (UTC)[reply]

Relisted to generate a more thorough discussion and clearer consensus.
Please add new comments below this notice. Thanks, North America¹⁰⁰⁰ 12:38, 7 July 2020 (UTC)[reply]

Merge to SPARQ per above. Coverage does NOT warrant an independent article. If in doubt, it has less than 1 view per day and has been tagged for a number of years. ≫ Lil-Unique1 -{ Talk }- 21:05, 14 July 2020 (UTC)[reply]
Merge as others have said already. -Kj cheetham (talk) 22:02, 14 July 2020 (UTC)[reply]

The above discussion is preserved as an archive of the debate. Please do not modify it. Subsequent comments should be made on the appropriate discussion page (such as the article's talk page or in a deletion review). No further edits should be made to this page.