jump to search:/  select search:K  navigate results:/  navigate suggestions:/  close suggestions:esc

    public health inspection signs as potential search seeds

    This is a provocation.

    You see a health inspection sign posted at a restaurant and what do you do? What does it mean?

    Maybe it has a QR code, but where does that go?

    I use “search seeds” to refer to the keywords or terms presented to the searcher that the searcher in turn uses in a search query. I want to be able to refer to the suggestions or opportunities to search. These are the strings of text someone comes to think to send to the web search engine as a search term. Or, these are components in the larger environment (spoken words or printed strings of text) that a potential searcher, situated with appropriate resources, may perceive to afford a successful search. This text may be in a code comment, function or method name, the error message, overheard in workplace conversation, or found on the web. [internal footnotes omitted]
    Ch. 4. Extending searching: Search seeds
    Griffin. “Situating Web Searching in Data Engineering: Admissions, Extensions, Repairs, and Ownership” (2022)

    Speculative design?

    This ppost was inspired by thinking about search seeds and seeking a ‘material sign’ that might be made searchable—and building on some other food & pathogen related musings on search (TK).

    If not a QR code, perhaps you could take a photo and be led directly to the report through something like Google Lens or Apple’s Visual Look Up. What processes do these companies currently go through as they consider which features to support? Does “societal relevance” (Sundin et al., 2021) play a role? Or some recognition of “the corporate responsibility to respect human rights” (Secretary-General, 2011)?

    Such an aggregated search is somewhat complicated in the United States by such inspections being managed at the local level (though an app, HDScores, claims to have “built a database that covers 73% of the entire United States”2).3



    1. Speaking of ratings systems, is there a rating system for how searcher friendly a search user interface is? Not something like TREC evaluations, though see Ch. 2: THE EVALUATION OF SEARCH USER INTERFACES in Hearst (2009). Shah & Bender (2022) present an “desiderata for building an ideal search system” (p. 230):

      • The system must support all 16 information seeking strategies (ISS) [4] as well as transitions between them.
      • There must be a clear way for the user to carry interactions with the system with iterations of request-response that carry the knowledge from previous interactions to the next.
      • These interactions must be supported through various modalities and modes of communication, including different types of devices, interfaces, languages, and expression of information need (keywords-based queries, questions, gestures, etc.)
      • The system must support all of the 20 search intentions[51].
      • The system should provide sufficient transparency about the sources where the information objects are coming from, as well as the process through which they are either ranked or consolidated and presented.
      • The system should support users in increasing their information literacy [64].
      • The system should be free of economic structures that support and even incentivize the monetization of concepts (such as identity terms) and allow commercial interests to masquerade as ‘objective’ information [54].

      1. Nicholas J Belkin, Colleen Cool, Adelheit Stein, and Ulrich Thiel. 1995. Cases, Scripts, and Information-Seeking Strategies: On the Design of Interactive Information Rretrieval Systems. Expert systems with applications 9, 3 (1995), 379–395.
        51. Matthew Mitsui, Jiqun Liu, Nicholas J Belkin, and Chirag Shah. 2017. Predicting Information Seeking Intentions from Search Behaviors. In Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval. 1121–1124.
        54. Safiya Umoja Noble. 2018. Algorithms of Oppression: How Search Engines Reinforce Racism. NYU Press.
        64. Catherine L. Smith and Soo Young Rieh. 2019. Knowledge-Context in Search Systems: Toward Information-Literate Actions. In Proceedings of the 2019 Con- ference on Human Information Interaction and Retrieval (Glasgow, Scotland UK) (CHIIR ’19). Association for Computing Machinery, New York, NY, USA, 55–62. https://doi.org/10.1145/3295750.3298940

      They also acknowledge that “One size does not fit all for search.”↩︎

    2. What does 73% of the entire United States mean in this context? 73% of restaurants, jurisdictions, patrons, land-area?↩︎

    3. @searchbound recently posted on Twitter:

      one time, I tried to build a service that aggregated restaurant health inspection scores into a central database…

      that project was a [total disaster]

      Whereas in the replies @sacha_vyzz linked to “a live map of every filthy food outlet in the UK” (scrapped from Google Business Profiles). Such maps, here is a static one for New York City, recently shared on reddit.com/r/MapPorn/, serve a different purpose than what I’m speculating about.↩︎

    4. As I look at the inspection reports for my favorite restaurants I wonder also about prospective search, being able to sign up for an alert for new ratings from restaurants I may frequent. It doesn’t look like I can do that in this interface.

      On this, per HDScores

      The HDScores App will allow you to “favorite” establishments and receive notifications on the their newest health inspection ratings. You will be able to search by your current location as well as nationwide.

      While perhaps useful, given the opacity reported above I’m not sure this approach as a whole achieves the utility I’m contemplated. I don’t want another app (thought perhaps this app can serve useful forcing functions on restaurants and health departments). I want to navigate my lived environment in ways that let me use material signs to link to reputable resources. Now, maybe I also don’t really want to sign up for notifications from my local health department.↩︎


    Awasthi, B. (2021). Does the food safety ranking system act as a nudge? 10(4), 42–58. https://doi.org/10.4018/IJABE.2021100104

    Dunne, A., & Raby, F. (2013). Speculative everything: Design, fiction, and social dreaming (the mit press). The MIT Press.

    Fox, S., Howell, N., Wong, R., & Spektor, F. (2019). Vivewell: Speculating near-future menstrual tracking through current data practices. Proceedings of the 2019 on Designing Interactive Systems Conference, 541–552. https://doi.org/10.1145/3322276.3323695

    Hearst, M. A. (2009). Search user interfaces. Cambridge University Press.

    Park, K., & Kong, K. (2022). Certification paradox: Reverse response on the non-hygiene restaurant certification. Journal of Hospitality and Tourism Management, 51, 268–278. https://doi.org/10.1016/j.jhtm.2022.03.017

    Secretary-General, S. R. of the. (2011). Guiding principles on business and human rights: Implementing the united nations “protect, respect and remedy” framework. U.N. Doc. A/HRC/17/31, Annex. https://www.ohchr.org/sites/default/files/documents/publications/guidingprinciplesbusinesshr_en.pdf

    Shah, C., & Bender, E. M. (2022, March). Situating search. ACM SIGIR Conference on Human Information Interaction and Retrieval. https://doi.org/10.1145/3498366.3505816

    Sundin, O., Lewandowski, D., & Haider, J. (2021). Whose relevance? Web search engines as multisided relevance machines. Journal of the Association for Information Science and Technology. https://doi.org/10.1002/asi.24570

    Wong, R. Y., Van Wyk, E., & Pierce, J. (2017). Real-fictional entanglements: Using science fiction and design fiction to interrogate sensing technologies. Proceedings of the 2017 Conference on Designing Interactive Systems, 567–579. https://doi.org/10.1145/3064663.3064682