Searching in the Smart City? An Information Access Challenge Dirk Ahlers1 1 NTNU – Norwegian University of Science and Technology, Trondheim, Norway Abstract How can users use search to make sense of Smart City offers? On the one hand, of course much information is available on the Web and is supposedly easily accessible to search. On the other hand, Smart Cities aim for data-driven urban transformation, and build a variety of new systems and data sources. Yet it is not yet fully clear which (new) approaches are needed to make these accessible to search. In the attempt to break up silos and make information more open, new types of silos or inaccessible systems can come up. It is of course rather easy to find restaurants or the list of city services. But that cannot be all we want from our cities. We need support in dealing with the higher complexity of information and services, and ideally more integrated ways of accessing them. Keywords Smart Cities, IR, Information Retrieval, Search, Urban Information Access, Location-based Search, Data Integration 1. Challenge certain key areas: governance, people, living, mobility, economy, environment.” [1] For a search perspective, it There is no search engine for Smart Cities. Why is that? Is means that data should be readily available, accessible, it not necessary, too complex, too specific, or something findable, searchable, composable and useable both by else? While we don’t have a complete answer yet, we humans and other services. argue that it is a bit of all. It may not be necessary to A Smart City is not a monolithic block run only cen- have that many separate (new) systems if we can handle trally by the city (administration) itself. It rather means the complexity through integration. Integration could an overall ecosystem of various (external) systems and also be a good way to go from a user view, as universal services and stakeholders, of access, and of running the search shows in common Web search engines. There city. As an example, to a user, the city feels smart if it has are few searches that would only apply to one specific good mobility options. The public transport should be smart city, so tackling them specifically for integration efficient and cover the city well, and this should be com- can help to make sense of them. This aligns with the bined with information about it being readily available; idea and ambition of Smart City as an integration and for example by having clear maps and route information combination of systems and silos. Of course there will available on the Web, on apps, and at the bus stops, but be specific search systems for specific datasets, systems, also having it machine-readable so that it can be included or applications, but for broad user appeal, it needs easy in other services and for example integrated into the com- findability and access; and subsequent integration into mercial mapping and routing engines. Having the bus general search. tables only in a pdf or worse, only at the bus stops, would From a user or citizen perspective, a Smart City should break that integration flow and the sensation of ’smart’. be a city that makes life easier, removes barriers, focuses Online city services improve a lot if it is not behind on sustainability and quality of life, and provides access a login screen, but the main parts are available freely to existing and new services and systems, well integrated, on the Web, so they can be found through any search and data-driven. As we argued before, “the Smart City engine, and not just by knowing the right entry point concept can be understood as a convergence of digital and navigating a semi-public system from there. information and physical environment along with social So, to transfer the vision of smartness to the users, data factors within a city. The ’smartness’ from the ICT view and information needs to be easily available and findable, is usually provided by information systems and concerns and it needs to support integration across different sys- tems. This of course opens up many opportunities to DESIRES 2021 – 2nd International Conference on Design of develop the approaches and systems that do the individ- Experimental Search & Information REtrieval Systems, September ual parts well, and then do the same for the integration, 15–18, 2021, Padua, Italy which will make all parts even more valuable to the in- " dirk.ahlers@ntnu.no (D. Ahlers) habitants. ~ https://ntnu.edu/employees/dirk.ahlers (D. Ahlers)  0000-0002-6508-8184 (D. Ahlers) More complex use cases and information needs could © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). be stated and fulfilled. As an example, a more integrated CEUR Workshop Proceedings http://ceur-ws.org ISSN 1613-0073 CEUR Workshop Proceedings (CEUR-WS.org) search may not only ask for a bar, but allow users to find a bar that is accessible by public transport at night, after hiking, with a view to the fjord or the river. That would combine location-based search, mapping and understand- ing routing tables, spatial relations, and semantic web retrieval, as well as integration across silos. Many similar scenarios exist and would move further away from single-page or single-result queries. These real-life cases are often not covered by existing evalu- ation scenarios such as TREC. They may also be much more context-dependent, and their answer depends to a high degree on local information available. There may be only noisy or lacking data sources. With the slow open- ing of silos, there is still a massive amount of information that is not yet accessible on the broad Web. Information may also not be findable in the big location search en- gines (or simply be not widely sourced and grounded enough to actually show up). The best result may be a combination, for example, of crowdsourced locations in OpenStreetMap and an obscure event on social media. So also location search is still far from solved. And while commercial engines are very good at a wide range types of queries, the complex integrated queries often only are found to be addressed in research prototypes. We have previously argued a similar case for recom- mender systems [1]. There we focused more on the dif- ferent scenarios and use cases, while there is a lot of overlap in the challenges. The needs of scenario-based search, data and service integration, cross-domain com- plex search, and evaluation do provide many challenges to further research into the topic of Smart City Search. Acknowledgements We thank our colleagues at the NTNU Smart Sustainable Cities group and others for helpful discussions around the topics presented here, insights into data ecosystems and data use, and inspiration for use cases. References [1] D. Ahlers, Making Sense of the Urban Future: Rec- ommendation Systems in Smart Cities, in: Com- plexRec2020 Workshop at RecSys2020, volume 2697 of CEUR, CEUR-WS.org, 2020. URL: http://ceur-ws. org/Vol-2697/paper5_complexrec.pdf.