Maker spaces and maker activities offering access to low-cost digital fabrication equipment are rapidly proliferating, evolving phenomena at the interface of lay and professional design. They also come in many varieties and change fast, presenting a difficult target for, for instance, public authorities, who would like to cater for them but operate in much slower planning cycles. As part of participatory planning of Helsinki Central Library, we experimented with a form of collaborative futuring with and by makers. By drawing elements from both lead-user workshops and participatory design, we conducted a futuring workshop, which allowed us to engage the local maker communities in identifying the issues relevant for a public maker space in 2020. It further engaged the participants in envisioning a smaller prototype maker space and invited them into realising its activities collaboratively. Our results indicate that particularly the information about future solutions was of high relevance, as was the opportunity to trial and elaborate activities on a rolling basis in the prototype space. Insights about more general trends in making were useful too, but to a lesser extent, and it is likely that these could have been gained just as easily with more traditional means for futuring.

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Users play an increasingly important role in product and service innovation. Finding the right users can require substantial search effort. Network searches are increasingly popular in searching for rare lead users. In these searches, implicit and inexact referrals have been found to comprise a substantial number of network referrals; numbers as high as 70% of the most important referrals to sought people have been reported. To aid handling such referrals during network searches, we explicate their status as intermediate referral types, and how these referral types relate to known search methods. The constraints set by intermediate referrals could potentially be overcome and their potential be capitalized through more extensive method combination in network searches than has been trialed to date. We proceed to offer a proof of concept for such searches through documenting how we ran them in four realworld searches and chart future research avenues.

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