# Chatbot-Based Natural Language Interfaces for Data Visualisation: A Scoping Review
## 4 Results
### Interactive Space of a V-NLI  
Table 4 summarises the chatbot input categories in related work. Among the existing work, 50% (10/20) integrated **Chatbot-based V-NLIs**[63; 80; 81; 82; 83; 86; 87; 89; 91; 92]. These V-NLIs have a chat window in which users can engage in conversations with a bot to analyse data visualisations. In some tools, the chat window is separated from the main visualisation dashboard [63; 80; 87; 91; 92], and in others, the visualisations are displayed in the chat windows [81; 82; 83; 86; 89]. For instance, both Iris [89] and Ava [81] were developed to help users perform complex data science tasks such as statistical analysis. While [89] displays visualisations in a single chat window, Ref. [81] has two windows, one containing the chatbot and the other showing the actions the chatbot performs, such as displaying visualisations. Moreover, we consider half of the approaches to be **Form-based V-NLIs**[15; 39; 40; 64; 69; 70; 84; 85; 88; 90]. When we explored different **Query Types**, we found that most of the previous research presented V-NLIs that support only low-level queries (90% (18/20)) [15; 39; 40; 63; 69; 70; 80; 81; 82; 84; 85; 86; 87; 88; 90; 91; 92]. For instance, in Refs. [40; 69; 70; 80; 82; 84; 85; 88; 90; 91; 92], users can ask direct queries and receive answers such as filtered or highlighted data points on visualisations or new visualisations. Moreover, there are V-NLIs that have more specific datasets and the chatbot is designed to ask users questions or give prompts to perform the analysis [63; 81; 86; 87; 89]. For example, Ref. [86] asks users questions to show them visualisations about basketball or football games, and [87] does this to help users extract genomics data into tables. Moreover, Refs. [81; 89] both ask users questions to complete data science tasks. Finally, two V-NLIs support both low and high level queries, Talk2 Data, which is form-based [64] and Chat2 Vis, which is chatbot-based [83]. Specifically, Talk2 Data [64] uses high-level questions to interact with data using basic interaction techniques such as filtering, and they split high-level queries into smaller sub queries to find answers. An example from Talk2 Data is, \"_Which \begin{table}
\begin{tabular}{l l l l l l l} \hline \hline  & \multicolumn{2}{c}{**V-NLI Interface**} & \multicolumn{2}{c}{**Input**} & \\ \cline{2-6}
**V-NLI** & **Chatbot** & **Form** & **Query T.** & **Follow-Up** & **Convesational Guidance** & **Multimodal.** \\ \cline{2-6}  & & & & **Help** & **Autocom.** & **Recom.** \\ \hline ACUI [80] & ✓ & & low & & & \\ \hline Ava [81] & ✓ & & low & & Hint/help & \(\mathrm{D},\mathrm{N}\) & \\ \hline Boomerang [82] & ✓ & & low & & & \\ \hline Chat2 Vis [83] & ✓ & & low \& high & & \\ \hline ConVisQA [69] & & ✓ & low & & ✓ & WIMP \\ \hline DataHand [84] & ✓ & low & & & & D & Touch \\ \hline DataBreeze [85] & ✓ & low & ✓ & & & Touch \\ \hline Evizeon [39] & & ✓ & low & ✓ & ✓ & & WIMP \\ \hline FlowNLL [70] & & ✓ & low & & ✓ & & WIMP \\ \hline GameBot [86] & ✓ & & low & & & & WIMP \\ \hline GeCoAgent [87] & ✓ & & low & & ✓ & \\ \hline InChorus [88] & & ✓ & low & & & Touch \\ \hline Iris [89] & ✓ & & low & & & \\ \hline MIVA [90] & & ✓ & low & & & \\ \hline ONYX [91] & ✓ & & low & & data-based & & WIMP \\ \hline Orko [15] & & ✓ & low & ✓ & & N & Touch \\ \hline Snowy [40] & & ✓ & low & ✓ & data-based & \(\mathrm{D},\mathrm{N},\mathrm{W}\) & WIMP \\ \hline Talk2 Data [64] & ✓ & low \& high & & & D \\ \hline TransVis [63] & ✓ & & low & user-based & & WIMP \\ \hline Valetto [92] & ✓ & & low & & user-based & Gestures \\ \hline \hline \hline \end{tabular}
\end{table} 
Table 4: Summary of input chatbot categories of V-NLIs. V-NLI interface (chatbot-based or form-based), Query Type (low or high), Follow-up query, Conversational Guidance: Help (data-based, user-based: based on what the user can ask), Auto-complete and Recommendation (recommend next action from D: Data, N: previous NL intent, W: previous WIMP interaction), and Input Modality.