Group items tagged

"[...] Mazzagatti calls this new data structure the Triadic Continuum, in honor of the theories and writings of Charles Sanders Peirce, one of the least well-known scientific geniuses of the late 19th century. Peirce, who is recognized as the father of pragmatism, is also known for his work in semiotics, the study of thought signs. Using Peirce's theoretical writings on how thought signs are organized into the structure of the human brain, Mazzagatti extrapolated a computer data structure that is self organizing - in other words, a data structure that naturally organizes new data by either building on the existing data sequences or adding to the structure as new data are introduced"

I quote: "Mazzagatti continued research into how Peirce's sign theory could be adapted to create a logical structure composed of signs that could be used in computers. Using Peirce's theoretical writings on how thought signs are organized into the structure of the human brain, Mazzagatti extrapolated a computer data structure that is self organizing - in other words, a data structure that naturally organizes new data by either building on the existing data sequences or adding to the structure as new data are introduced. "

Database systems are notorious for being hard to use. It is even more difficult to integrate data from multiple sources and collaborate on large data sets with people outside your organization. Without an easy way to offer all the collaborators access to the same server, data sets get copied, emailed and ftp'd--resulting in multiple versions that get out of sync very quickly. Today we're introducing Google Fusion Tables on Labs, an experimental system for data management in the cloud. It draws on the expertise of folks within Google Research who have been studying collaboration, data integration, and user requirements from a variety of domains. Fusion Tables is not a traditional database system focusing on complicated SQL queries and transaction processing. Instead, the focus is on fusing data management and collaboration: merging multiple data sources, discussion of the data, querying, visualization, and Web publishing. We plan to iteratively add new features to the systems as we get feedback from users.

The Semantic Web isn't just about putting data on the web. It is about making links, so that a person or machine can explore the web of data. With linked data, when you have some of it, you can find other, related, data. Like the web of hypertext, the web of data is constructed with documents on the web. However, unlike the web of hypertext, where links are relationships anchors in hypertext documents written in HTML, for data they links between arbitrary things described by RDF,. The URIs identify any kind of object or concept. But for HTML or RDF, the same expectations apply to make the web grow: 1. Use URIs as names for things 2. Use HTTP URIs so that people can look up those names. 3. When someone looks up a URI, provide useful information. 4. Include links to other URIs. so that they can discover more things.

Protocol buffers are a flexible, efficient, automated mechanism for serializing structured data - think XML, but smaller, faster, and simpler. You define how you want your data to be structured once, then you can use special generated source code to easily write and read your structured data to and from a variety of data streams and using a variety of languages. You can even update your data structure without breaking deployed programs that are compiled against the "old" format.

Twitter Data is a simple, open, semi-structured data representation format for embedding machine-readable, yet human-friendly, data in Twitter messages. This data can then be transmitted, received, and interpreted in real time to enable powerful new kinds of applications to be built on the Twitter platform.

The MOBY system for interoperability between biological data hosts and analytical services The MOBY-S system defines an ontology-based messaging standard through which a client will be able to automatically discover and interact with task-appropriate biological data and analytical service providers, without requiring manual manipulation of data formats as data flows from one provider to the next.

Public Data Sets on AWS provides a centralized repository of public data sets that can be seamlessly integrated into AWS cloud-based applications. AWS is hosting the public data sets at no charge for the community, and like all AWS services, users pay only for the compute and storage they use for their own applications.

The relationship among data, information and knowledge is often depicted as a pyramid. With data at the base, it's converted to information and information converted to knowledge. This metaphor of a pyramid or ladder to explain these concepts is unhelpful because you start to believe one is better than the other and there is a tendency to extrapolate to the next level believing that knowledge is simply extrapolated to form wisdom-I have even heard people talk about wisdom management. My two days at the meaning making symposium has helped me see this relationship differently, that is, viewing data, information and knowledge as a system.

Pig is a platform for analyzing large data sets that consists of a high-level language for expressing data analysis programs, coupled with infrastructure for evaluating these programs. The salient property of Pig programs is that their structure is amenable to substantial parallelization, which in turns enables them to handle very large data sets.

The FlyWeb Project is implementing a proof-of-concept data web to integrate research image data from the FlyTED Project with related data from the Berkeley Drosophila Genome Project, FlyBase, FlyAtlas and other sources.

So far little awareness exists about the commercial opportunities of linked data. Andreas Blumauer (SWC) talked to Chris Bizer, mastermind behind the DB-Pedia project and advocate of the linking open data philosophy, about the emerging market for deep web applications, its value for corporate purposes, and the need for information accountability and privacy awareness.

The exponential growth of diverse types of biological data presents the research community with an unprecedented challenge and opportunity. The challenge is to stay afloat in the flood of biological data, keeping it as accessible, up-to-date, and integrated as possible. The opportunity is to cultivate new models of data curation and exchange that take advantage of direct participation by a greater portion of the community.

Rapid advances in information technologies continue to drive a flood of data and analysis techniques in ecological and environmental sciences. Using these resources more effectively and taking advantage of associated cross-disciplinary research opportunities poses a major challenge to both scientists and information technologists. These challenges are now being addressed in projects that apply knowledge representation and Semantic Web technologies to problems in discovering and integrating ecological data and data analysis techniques. In this paper, we present an overview of the major ontological components of our project, SEEK ("Science Environment for Ecological Knowledge"). We describe the concepts and models that are represented in each, and present a discussion of potential applications of these ontologies on the Semantic Web

WikiProteins enables community annotation in a Wiki-based system. Extracts of major data sources have been fused into an editable environment that links out to the original sources. Data from community edits create automatic copies of the original data. Semantic technology captures concepts co-occurring in one sentence and thus potential factual statements. In addition, indirect associations between concepts have been calculated. We call on a 'million minds' to annotate a 'million concepts' and to collect facts from the literature with the reward of collaborative knowledge discovery. The system is available for beta testing at http://www.wikiprofessional.org

Human Proteinpedia is a community portal for sharing and integration of human protein data. It allows research laboratories to contribute and maintain protein annotations. Human Protein Reference Database (HPRD) integrates data, that is deposited in Human Proteinpedia along with the existing literature curated information in the context of an individual protein. All the public data contributed to Human Proteinpedia can be queried, viewed and downloaded.

KHarvester (Informal Knowledge Harvester) is a SOA layer which collects RDF data from web pages. It provides REST based Web Services for managing data available on Social Semantic Information Sources (SSIS): semantic blogs, semantic wikis, and JeromeDL (the Social Semantic Digital Library). These Web Services allow saving harvested data in the informal knowledge repository, and providing them in a form of informal Learning Objects (LOs) that are described accroding to LOM (Learning Object Metadata) standard. Also, IKHarvester is an extension to Didaskon system. Didaskon (διδάσκω - gr. teach) delivers a framework for composing an on-demand curriculum from existing Learning Objects provided by e-Learning services (formal learning). Moreover, the system derives from SSIS which provide informal knowledge. Then, the selection and work-flow scheduling of Learning Objects is based on the semantically annotated specification of the user's current skills/knowledge (pre-conditions), anticipated resulting skills/knowledge (goal) and technical details of the clients platform.

Linked Data is a term used to describe a recommended best practice for exposing, sharing, and connecting pieces of data on the Semantic Web. The practice emphasizes Web access to data using existing Web technologies such as URIs and HTTP. It also emphasizes links between related Web resources.

The Web is ephemeral. Pages change frequently, and it is nearly impossible to find data or follow a link after the underlying page evolves. We present Zoetrope, a system that enables interaction with the historical Web (pages, links, and embedded data) that would otherwise be lost to time. Using a number of novel interactions, the temporal Web can be manipulated, queried, and analyzed from the context of familar pages. Zoetrope is based on a set of operators for manipulating content streams. We describe these primitives and the associated indexing strategies for handling temporal Web data. They form the basis of Zoetrope and enable our construction of new temporal interactions and visualizations.

This is a sub-project of the BioMoby project. It aims to develop tools in Java in order: * to access BioMoby registries, allowing all features provided by such registries, including but not limited to registering and deregistering of the BioMoby services and their parts, discovering them, and understanding their data in various formats (such as RDF), * to create Java implementations of BioMoby services, especially to help service providers with creating BioMoby data containers (input and output data) without exposing providers to the complexity of the XML required and produced by BioMoby services, and finally

Purpose 1. Act as a central point of reference and support for people who think they are interested in open data in science. 2. Identify practices of early adopters, collecting data and developing guides. 3. Act as a hub for the development of low cost, community driven projects around open data in science.