Overall, while we’ve been promoting the use of structured data for some time (one of the reasons we were delighted Wallis could speak), the talk did a fantastic job of clearly describing not just the concepts involved but a method of execution that attendees could genuinely go back to the office and implement.ĭev time can often be difficult to obtain for SEO in many organisations – especially for something like structured data which is difficult to communicate effectively to stakeholders – but this talk provides a ready to go business case for anyone needing one, and – with a section at the end covering the future usefulness of markup, it really was a talk that SEOs and digital marketers in general should definitely spend 25 mins watching. Preferably use JSON-LD – validate with tools, Google & docs.Don’t worry about lists – marking up the individual things is more important.Markup all your entities including your Organization and link them together.Don’t just provide a name and hope Google works out who it is! Relate them to other things – the author is a Person, that needs describing.Describe the things the pages are about – as against the pages themselves.If Googlebot doesn’t find your pages useful, it’s unlikely data will be loaded.In a slide titled ‘Google Knowledge Graph – How do I get my stuff into it?’ Wallis gives two steps that can facilitate the process: Using layers of schema, Wallis presents the basic methodology used to contextualise information for the knowledge graphs. In a fictitious post on Paris as a tourist destination (which we can see as one entity), for example, he used schema to refer to the entity ‘Paris’, but also contextualises the author (another entity) – using schema to reference expertise. He presents an example – using travel blogging as an example, and laying out the various ways in which a piece of content – and the domain it’s posted on – can be connected to the wider ‘knowledge graph’. To properly fit, and to be correctly contextualised within that ontology, it needs to connect with as much of that external meaning as possible – and this can be done using markup. The argument Wallis’ talk makes for schema is that you can view your content as a piece of the jigsaw that is the wider ontology of your industry. The reason being, I was touching on schema and structured data and sat in the front row, directly in my line of sight, was Richard Wallis – one of the original community and a consultant to Google amongst others on the topic of information architecture. My obsession with structured data has developed to the point where it is now a running joke within the marketing department – so when I gave my talk at Benchmark this year, I did so with an extra helping of nerves. Image modification for adjustment (edge detection, blur, sharpen, etc.With more than 20 years working in and advising on information architecture, Wallis is a leading voice in what has become one of the most important web developments to have emerged in the last decade – structured data The idea is very simple, but its usefulness is likely to become essential.Īutomatic detection of curves (solid, dotted or dashed), symbols, bar charts, or perimeters of areasĪlmost all file formats recognized (PDF, JPEG, GIF, TIFF, Photoshop, etc.)įrame-by-frame digitization of QuickTime movies You have the picture of a graph but not the corresponding data? You want to retrieve the trajectory of an object from a QuickTime movie? GraphClick is then simply the best way to solve the problem! You just have to click on the image and the obtained coordinates of the points can be directly exported into any other application. GraphClick is a graph digitizer software which allows to automatically retrieve the original (x,y)-data from the image of a scanned graph or from a QuickTime movie.
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