open data

Artificial intelligence and open data


In the policies promoted by the European Union, an intimate connection between artificial intelligence and open data has been considered. In this regard, as we highlighted, open data is essential for the proper functioning of artificial intelligence, since the algorithms must be fed by data whose quality and availability is essential for its continuous improvement, as well as to audit its correct operation. Artificial intelligence entails an increase in the sophistication of data processing, since it requires greater precision, updating and quality, which, on the other hand, must be obtained from very diverse sources to increase the quality of the algorithms results. Likewise, an added difficulty is the fact that processing is carried out in an automated way and must offer precise answers immediately to face changing circumstances. Therefore, a dynamic perspective that justifies the need for data -not only to be offered in open and machine-readable format, but also with the highest levels of precision and disaggregation- is needed.

Speculative Data Futures: Karima


I am Karima, which means the generous. It always reminds me of my home, Syria, a generous country destroyed by war. I was born and raised in a refugee camp populated by 5000 Syrians. It is not easy to be born Syrian in a refugee camp, especially if you are a woman. Hunger for a loaf of bread in the refugee camp is connected to a hunger for bodies.

Deep Dive: How a Health Tech Sprint Pioneered an AI Ecosystem


When we began our 14-week tech health sprint in October 2018, we did not realize the profound lessons we would learn in just a few months. Together with federal agencies and private sector organizations, we demonstrated the power of applying artificial intelligence (AI) to open federal data. Through this collaborative process, we showed that federal data can be turned into products for real-world health applications with the potential to help millions of Americans have a better life. Joshua Di Frances, the executive director of the Presidential Innovation Fellows (PIF) program, says that this collaboration across agencies and private companies represents a new way of approaching AI and federal open data. "Through incentivizing links between government and industry via a bidirectional AI ecosystem, we can help promote usable, actionable data that benefits the American people," Di Frances said.

Open Data for Machine Learning


The P2P Foundation includes the definition of Open Data as the philosophy and practice requiring that certain data be freely available to everyone, without restrictions from copyright. In recent years as an exercise of transparency governments and city councils create open data portals where the authorities push a lot of data to be freely accessible to citizens. Nowadays is easy to find a dataset of almost everything, in a few clicks you can find, as for instance datasets related to territory (parking spaces of a city), population (Level of education), governance (electoral results)... The benefits of Open Data from an ethical movement essentially focus on empowering the resident with data that somehow can be used for his own profit. Clearly stated in the article "5 benefits of open government data" [3] we found: As Stated Before Open Data can unlock the potential of Machine Learning.

AI Making Ancient Japanese Texts More Accessible NVIDIA Blog


Natural disasters aren't just threats to people and buildings, they can also erase history -- by destroying rare archival documents. As a safeguard, scholars in Japan are digitizing the country's centuries-old paper records, typically by taking a scan or photo of each page. But while this method preserves the content in digital form, it doesn't mean researchers will be able to read it. Millions of physical books and documents were written in an obsolete script called Kuzushiji, legible to fewer than 10 percent of Japanese humanities professors. "We end up with billions of images which will take researchers hundreds of years to look through," said Tarin Clanuwat, researcher at Japan's ROIS-DS Center for Open Data in the Humanities.

ArCo: the Italian Cultural Heritage Knowledge Graph Artificial Intelligence

ArCo is the Italian Cultural Heritage knowledge graph, consisting of a network of seven vocabularies and 169 million triples about 820 thousand cultural entities. It is distributed jointly with a SPARQL endpoint, a software for converting catalogue records to RDF, and a rich suite of documentation material (testing, evaluation, how-to, examples, etc.). ArCo is based on the official General Catalogue of the Italian Ministry of Cultural Heritage and Activities (MiBAC) - and its associated encoding regulations - which collects and validates the catalogue records of (ideally) all Italian Cultural Heritage properties (excluding libraries and archives), contributed by CH administrators from all over Italy.

8 factors shaping the future of big data, machine learning and AI


I've just spent a couple of days at O'Reilly's Strata Data Conference in London and got a much better idea where the world of big data, machine learning (ML) and AI may be heading. These sectors have developed rapidly over the last 5 years with new technologies, processes and applications changing the way organisations are managing their data. The Strata conference provides a good barometer of what the state-of-the-art is in big data manipulation as well as the concerns of developers and users. Eight key points emerged for me from the event. I spoke with O'Reilly's Chief Data Scientist and Strata organiser, Ben Lorica about this and he sees the increased bandwidth and flexibility of 5G as well as the move to edge computing as key enablers.

AI and Open Data: a crucial combination - European strong Data Portal /strong - European Data Portal


Artificial Intelligence (AI) technology has the capacity to extract deeper insights from datasets than other techniques. Examples of AI are: speech recognition, natural language, processing, chatbots or voice bots. To get AI applications to work, big sets of high quality (open) data are necessary. But what requirements does this data have to meet? To answer this question, we need to look more closely at what requirements data need to have to enable successful AI applications.

Working on AI? Get these Free Public Data Sources for 2019 Analytics Insight


High-quality data is the oil that moves the AI wheel to new heights, and the machine learning community cannot get enough of it. Organisations and individuals working on disruptive technologies like AI need datasets to fuel up their ML, Deep Learning and NLP algorithms. In a 2018 research, IBM performed poorly when it was assigned the task to identify dark-skinned female subjects with only 65.3% accuracy. Since then the tech giant has pulled up its socks to improve its research efforts against AI bias with releasing the world largest facial attribute dataset called Diversity in Faces (DiF). DiF comprises one million human facial images which were compiled from the YFCC-100M Creative Commons dataset.

Facebook hackathon applies machine learning to Seattle data to solve civic challenges


October 6, 2017 at 12:00 pm October 6, 2017 at 10:59 am GeekWire Summit: Tickets here! Tomorrow, Facebook's Seattle engineering hub will host a hackathon focused on applying machine learning to Seattle's wealth of public data. Here is an example of the kinds of things we might see come out of the event according to Aria Haghighi, a Facebook engineering manager who is leading the event: "We have bicycle accident data -- where bicycle accidents are happening -- and we also have map data on what the terrain looks like there," Haghighi said. "So, one thing you could do is build a model to predict, based on the map, where are you likely to see accidents and see how that does with some of the data we have." N. David Doyle, program manager for Seattle's open data initiative, said the city hasn't yet delved deeply into what machine learning can do for its municipal data sets.