Proficient in Information System Design used to the development of Business Intelligence Platforms and Semantic Web Ontologies. With experience in the benefits of the knowledge extraction by integrating LinkedData Technologies and OpenData Sources.
"It’s not all ‘Moneyball’ and to hope that data scientists alone will help solve talent challenges is naïve. Data-based insights can only act as indicators by themselves. Domain experts like hiring managers, HR professionals, and recruiters involved must be able to identify the problem and ask the right questions before applying analytics."
By W. Brian Arthur; External Professor, Santa Fe Institute; Visiting Researcher, Palo Alto Research Center.
Economics is a stately subject, one that has altered little since its modern foundations were laid in Victorian times. Now it is changing radically. Standard economics is suddenly being challenged by a number of new approaches: behavioral economics, neuroeconomics, new institutional economics. One of the new approaches came to life at the Santa Fe Institute: complexity economics.
Complexity economics got its start in 1987 when a now-famous conference of scientists and economists convened by physicist Philip Anderson and economist Kenneth Arrow met to discuss the economy as an evolving complex system. That conference gave birth a year later to the Institute’s first research program – the Economy as an Evolving Complex System – and I was asked to lead this. That program in turn has gone on to lay down a new and different way to look at the economy.
"Where does complexity economics find itself now? Certainly, many commentators see it as steadily moving toward the center of economics. And there’s a recognition that it is more than a new set of methods or theories: it is a different way to see the economy. It views the economy not as machine-like, perfectly rational, and essentially static, but as organic, always exploring, and always evolving – always constructing itself."
The BBC Things website is designed to be used by anyone who works with our data at a technical or editorial level. From an editorial perspective, the website makes it easy for content editors, producers and creators to discover concepts that exist in our platform.
Fàtima Galan's insight:
"The new website provides public access to data stored in our platform and, importantly, provides a public reference for all of the things that the BBC creates content about. "
"The CERN Open Data portal is the access point to a growing range of data produced through the research performed at CERN. It disseminates the preserved output from various research activities, including accompanying software and documentation which is needed to understand and analyze the data being shared."
the information that is annotated inside the document;the annotation itself;a predicate, that establishes a relationship amongst the two points above;the context in which the annotation has been made (who made it, when, its reliability, a possible limit for its validity, etc).
"Tenemos que trabajar para que el ciudadano se conecte con los otros stakeholders para determinar servicios y proponer soluciones. Son laspersonas las que toman el poder para proponer soluciones que pueden tener forma de negocio si el sector empresarial está conectado y atento."
Microsoft has signed a letter of intent to buy Equivio, an Israeli developer of text-analysis software used for corporate/legal e-discovery and information governance applications. The WSJ reports the price is around $200M. Equivio's software relies on machine learning algorithms to analyze and group together documents. Potential use cases include grouping near-duplicates, reconstructing e-mail threads, and data mining.
Today Open Knowledge and the Open Definition Advisory Council are pleased to announce the release of version 2.0 of the Open Definition. The Definition “sets out principles that define openness in relation to data and content” and plays a key role in supporting the growing open data ecosystem.
Open Data " benefits are at significant risk both from quality problems such as “open-washing” (non-open data being passed off as open) and from fragmentation of the open data ecosystem due to incompatibility between the growing number of “open” licenses.
The Open Definition eliminates these risks and ensures we realize the full benefits of open by guaranteeing quality and preventing incompatibility.See this recent post for more about why the Open Definition is so important.
GB Rowing’s senior sports scientist Mark Homer shares how his team is analysing data to improve their chances of success (RT @Timothy_Hughes: How the GB Rowing Team is mining big data http://t.co/EJU7tJ9QQX...
Below is a glossary of words, concepts and tools that have been important to the R&D Fund projects so far. 10 Basic Terms Software is the general name for the programs and other operating information that run on a computer or device. Hardware is the general name for any of the physical components of a...
Big data and the “internet of things”—in which everyday objects can send and receive data—promise revolutionary change to management and society. But their success rests on an assumption: that all the data being generated by internet companies and devices scattered across the planet belongs to the organizations collecting it. What if it doesn’t?
Alex “Sandy” Pentland, the Toshiba Professor of Media Arts and Sciences at MIT, suggests that companies don’t own the data, and that without rules defining who does, consumers will revolt, regulators will swoop down, and the internet of things will fail to reach its potential. To avoid this, Pentland has proposed a set of principles and practices to define the ownership of data and control its flow. He calls it the New Deal on Data. ...
"We’ve set up some safe-harbor areas in Europe—cities that run by different rules than the rest of Europe. In Trento, Italy, hundreds of families are living with the New Deal on Data. They get notification and control of data generated about them. It’s securely shared in an auditable way. And guess what? These people share a lot more than people who don’t live under New Deal rules, because they trust the system and recognize the value in sharing. Being confident about your personal data makes for a better economy, not a worse one."
It’s been said that we’re living in the golden age of data visualization. And why shouldn’t we be? Every move we make is potential fodder for a bar chart or line graph. Regardless of how you feel about our constant quantification, its been a boon for designers who have made some exceptional infographics—and some not…
"What are the differences between data science, data mining, machine learning, statistics, operations research, and so on?
Here I compare several analytic disciplines that overlap, to explain the differences and common denominators. Sometimes differences exist for nothing else other than historical reasons. Sometimes the differences are real and subtle. I also provide typical job titles, types of analyses, and industries traditionally attached to each discipline. Underlined domains are main sub-domains. It would be great if someone can add an historical perspective to my article."
"This survey intends to reflect the opinion of various stakeholders working in different industry verticals about the status of Linked Data technologies. The main question is: Is Linked Data perceived as mature enough to be used on a large scale in enterprises? The results will contribute to the development of the Linked Data market by reporting how enterprises currently think."
Over the past few years, major enterprises have shown interest in combining semantic web technology with big data for added value. Let's take a look at what enterprises are seeking and why they think semantic web can make big data smarter. Topic: Featured Articles.
Fàtima Galan's insight:
* Provides end-users increased ability to self-manage data from varied sources * Addresses varying user needs and changing business environments * Manages terminology, concepts and relationships while connecting diverse data from varied data sources As you create a semantic layer over your big data initiative, be sure to include the following elements: 1. Flexible, universal data model based on industry standards 2. Use of semantic RDF standards to make the data “self-describing” 3. Graph representation and management of data 4. Service-Oriented Architecture (SOA) infrastructure 5. Post-ingestion data characterization
Every day we face challenges – from the personal, such as the quickest way to get to work, or what we should eat, to global ones like climate change and how to sustainably feed and educate seven billion people on this planet, writes Rufus Pollock, Founder, Open Knowledge
At Open Knowledge we believe that opening up data – and turning that data into insight – can be crucial to addressing these challenges, and building a society in which is everyone – not just the few – are empowered with the knowledge they need to understand and effect change.
"Data is everywhere and we commonly talk of ‘digital economies’ now, of a ‘networked society’. But making sense of data – turning it into knowledge if you like – and then using it wisely, is still one of the greatest challenges we face as a global and increasingly interlinked society.
Reuse and redistribution: the data must be provided under terms that permit reuse and redistribution including the intermixing with other datasets. The data must be machine-readable.
Personal data should never be ‘open’ and freely accessible to everyone. Rather, we strongly believe that each of us should control our personal data – both to have access to it and to know (and decide) how it is used.
With digital technology – from mobiles to the Internet – increasingly everywhere, we are seeing a data revolution. We are living this revolution both in the amount of data available and in our ability to use, and share, that data. And it is changing everything we do – from how we travel home from work to how scientists do research, to how governments set policy.