On the topology of the web of data

The Web of Data consists of the open accessible structured data on the Web. This includes the evolving number of Linked Open Data data sets but also the structured data which is embedded in Web pages. In this paper we address questions related to a unified definition of distinct data sets and factors that influence different network representations of structured Web data. The contributions are (1) an algorithm to generate a data set linking structure of the em- bedded structured data sourcing from (a) the Billion Triples Challenge corpus (b) the Web Data Commons corpus, and (c) the sindice crawl, (2) a discussion on the issue of identifying distinct data sets in a generic fashion, and (3) a high level visual abstraction of the current Web of Data topology

On the topology of the web of data

The Web of Data consists of the open accessible structured data on the Web. This includes the evolving number of Linked Open Data data sets but also the structured data which is embedded in Web pages. In this paper we address questions related to a unified definition of distinct data sets and factors that influence different network representations of structured Web data. The contributions are (1) an algorithm to generate a data set linking structure of the em- bedded structured data sourcing from (a) the Billion Triples Challenge corpus (b) the Web Data Commons corpus, and (c) the sindice crawl, (2) a discussion on the issue of identifying distinct data sets in a generic fashion, and (3) a high level visual abstraction of the current Web of Data topology

Social Ranking Techniques for the Web

The proliferation of social media has the potential for changing the structure and organization of the web. In the past, scientists have looked at the web as a large connected component to understand how the topology of hyperlinks correlates with the quality of information contained in the page and they proposed techniques to rank information contained in web pages. We argue that information from web pages and network data on social relationships can be combined to create a personalized and socially connected web. In this paper, we look at the web as a composition of two networks, one consisting of information in web pages and the other of personal data shared on social media web sites. Together, they allow us to analyze how social media tunnels the flow of information from person to person and how to use the structure of the social network to rank, deliver, and organize information specifically for each individual user. We validate our social ranking concepts through a ranking experiment conducted on web pages that users shared on Google Buzz and Twitter.Comment: 7 pages, ASONAM 201

Some Properties of the Speciation Model for Food-Web Structure - Mechanisms for Degree Distributions and Intervality

We present a mathematical analysis of the speciation model for food-web structure, which had in previous work been shown to yield a good description of empirical data of food-web topology. The degree distributions of the network are derived. Properties of the speciation model are compared to those of other models that successfully describe empirical data. It is argued that the speciation model unifies the underlying ideas of previous theories. In particular, it offers a mechanistic explanation for the success of the niche model of Williams and Martinez and the frequent observation of intervality in empirical food webs.Comment: 23 pages, 6 figures, minor rewrite

Interplay between topology and dynamics in the World Trade Web

We present an empirical analysis of the network formed by the trade relationships between all world countries, or World Trade Web (WTW). Each (directed) link is weighted by the amount of wealth flowing between two countries, and each country is characterized by the value of its Gross Domestic Product (GDP). By analysing a set of year-by-year data covering the time interval 1950-2000, we show that the dynamics of all GDP values and the evolution of the WTW (trade flow and topology) are tightly coupled. The probability that two countries are connected depends on their GDP values, supporting recent theoretical models relating network topology to the presence of a `hidden' variable (or fitness). On the other hand, the topology is shown to determine the GDP values due to the exchange between countries. This leads us to a new framework where the fitness value is a dynamical variable determining, and at the same time depending on, network topology in a continuous feedback.Comment: Proceedings of the 5th conference on Applications of Physics in Financial Analysis (APFA5), 29 June - 1 July 2006, Torino (ITALY

Using the Topology of Large Scale Structure to constrain Dark Energy

The use of standard rulers, such as the scale of the Baryonic Acoustic oscillations (BAO), has become one of the more powerful techniques employed in cosmology to probe the entity driving the accelerating expansion of the Universe. In this paper, the topology of large scale structure (LSS) is used as one such standard ruler to study this mysterious `dark energy'. By following the redshift evolution of the clustering of luminous red galaxies (LRGs) as measured by their 3D topology (counting structures in the cosmic web), we can chart the expansion rate and extract information about the equation of state of dark energy. Using the technique first introduced in (Park & Kim, 2009), we evaluate the constraints that can be achieved using 3D topology measurements from next-generation LSS surveys such as the Baryonic Oscillation Spectroscopic Survey (BOSS). In conjunction with the information that will be available from the Planck satellite, we find a single topology measurement on 3 different scales is capable of constraining a single dark energy parameter to within 5% and 10% when dynamics are permitted. This offers an alternative use of the data available from redshift surveys and serves as a cross-check for BAO studies.Comment: 8 pages, 5 figures, 2 tables, Submitted to MNRAS, updated acknowledgement