## 7 Conclusions and Future Work  
The objective of this paper was to address the challenge of a lack of a comprehensive Arabic language-sensitive NLP crowdsourcing platforms. The review of existing approaches to crowdsourcing platforms, including the internationally popular crowdsourcing platforms, or to individually designed platforms, highlighted that there was a need to build an Arabic language-sensitive NLP crowdsourcing platform. Accordingly, the platform, named Tashkeel, was built and evaluated via SUS. The score was 72.5, i.e., well above the accepted usability average. Against this backdrop, a case was made that, if further developed and popularized, this crowdsourcing platform might encourage research requiring this tool of research to connect researchers and users in the linguistic domain of the Arabic language. Indeed, the crowdsourcing platform developed in this paper allows Arabic speakers with different levels of proficiency and qualifications to be identified and invited to participate in a research project from its inception. Any Arabic dialects can be chosen and dedicated to the project. In this regard, on the one hand, this crowdsourcing platform provides NLP researchers with new spaces to interact with a highly diversified, and thus,'representative' 'crowd', and to perform specific HITs. Hence, research utilizing this NLP crowdsourcing platform acquires validity, relevance, and usability. This feature of the NLP crowdsourcing platform introduced in this paper defines this platform's value-added in the field of data-driven decision-making and policy processes in general. Certainly, the road from this NLP crowdsourcing platform to the decision-making process is a long one; however, without the platform, masses of important pieces of information might be ignored. We are aware that further work needs to be done to address the issue of quality control as regards the specific HITs, e.g., by means of an algorithm that measures the quality by testing the accuracy of the participants' answers. Nevertheless, we also want to stress that there is an urgent need to pursue, in parallel, research on the value-added of crowdsourcing platforms for the decision-making process. These two issues shall be addressed in our future research.  
\begin{table}
\begin{tabular}{p{34.1 pt} p{227.6 pt}} \hline \hline
1. & I think that I would like to use this system frequently. \\ \hline
2. & I found the system unnecessarily complex. \\ \hline
3. & I thought the system was easy to use. \\ \hline
4. & I think that I would need the support of a technical person to be able to use this system. \\ \hline
5. & I found the various functions in this system were well integrated. \\ \hline
6. & I thought there was too much inconsistency in this system. \\ \hline
7. & I would imagine that most people would learn to use this system very quickly. \\ \hline
8. & I found the system very cumbersome to use. \\ \hline
9. & I felt very confident using the system. \\ \hline
10. & I needed to learn a lot of things before I could get going with this system. \\ \hline \hline \end{tabular} Source: Authors.  
\end{table}
Table 2: System Usability Scale (SUS) questions used in the survey [31].  
**Author Contributions:** Conceptualization, D.A., A.B., K.S., and A.V.; methodology, D.A., A.B., and K.S.; software D.A., A.B., and K.S.; validation, D.A., A.B., and K.S.; writing--original draft preparation, D.A., A.B., and K.S., writing--review and editing, D.A., A.B., K.S., and A.V. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This project was funded by the Deanship of Scientific Research (DSR), King Abdulaziz University, Jeddah, Saudi Arabia, under grant G: 1473-612-1440 and grant No. 62467. The authors [PERSON], A.B., and K.S. therefore gratefully acknowledge the DSR technical and financial support.  
**Conflicts of Interest:** The authors declare no conflict of interest.