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Showing posts from June, 2009

Initiating a Corporate Social Media Presence – Unleash Your Inner Star Power

Social Media’s a scary animal, especially for companies or organizations that are accountable to stakeholders, policy, law or any other governing entity that exists to mitigate risk. Also, social media is an online collaboration channel and tools domain that’s most appropriately and effectively utilized by humans, i.e. individual personalities (preferably employees) – vs. corporate personas or third-party services. So how does a company begin to use social media, break into and contribute to the online dialogue, and avoid reputation issues while maintaining appropriate accountability? Find, identify, nurture, coach and ultimately unleash your employee social media stars – they’ll be the face of the company, the purveyors of online dialogue, and will most likely do a great job at it. Why and how? First of all, the social media platforms and tools are the dominion of the Internet-literate, the digerati, typically those more inclined and interested to communicate online at least as often

Government Social Media Reputation Management in the Cloud

During this morning’s IAC breakfast, discussing “Transparency, Collaboration and Web 2.0”, a panelist made a very interesting point. While the US Federal Government’s use of Internet social media services and cloud-based information-sharing applications is well underway, albeit at the very earliest of stages (mainly due to significant policy, privacy, security and simple “newness” issues), by far one of the major risks lies with accountability. Accountability in collaboration and information-sharing environments is typically achieved to some degree by association of metadata with the information packages being exchanged, or with the “containers” of online events and the trusted identities of those participating in the dialogue. With social media applications and contexts like Twitter or Facebook, however, there are far too many ways that the “information packages” (i.e. unmanaged conversation bites) get exposed, syndicated and shared – disassociated from what I’ll call the “accountabi

Probably Interesting Information

(Warning – hyper-theoretical stream of probably uninformed semi-consciousness to follow…) In considering the possible types of information that might need to included in Enterprise Information-Sharing programs, while sifting through my TweetDeck, something’s become quite clear – most of our Government information-sharing exercises are all about “Signals”, “Data”, and “Information” that are already known (at some level) to be “required”, “useful”, or “possibly interesting” – judged as so by existing processes, policies, roles, business rules and perhaps knowledgebase ontologies. I’d like to, however, receive and share more information from the government that’s “probably interesting”, but that hasn’t yet been confirmed as so by them, or me and my community. This happens all the time in social media, where I’ve subscribed to or participate in an information-exchange forum based on a particular knowledge context (and within my own agenda), and routinely view information that’s been posted

Information-Sharing with Cloud Semantic Ontologies

Quite a mouthful, the title of this post. However, this language is becoming more and more critical to the objective of cross-domain information-sharing, and is becoming more and more easy to actually use (by the public!) in building information search, discovery, fusion and correlation/analytical applications. A while ago, I was introduced to the semantic wiki technologies and communities of Knoodl (knoodl.com), which is a mechanism for like-minded persons to collaborate on building semantic vocabularies, using open standards like RDF and OWL. Basically describing the terms and language of a topic area in a manner that can be expressed, via XML, for consumption by computer applications. So when a message arrives in your system with information labeled "SAR", or a query is sent forth with the same acronym, a test of this word against the machine-readable vocabulary can determine what the likely meaning really is - "suspicious activity report", "suspect action r