Exaptation, Degeneracy and Innovation

In innovation processes, exaptations are innovation-development processes through which an initial attribution of new functionality to existing artifacts leads to new artifacts and eventually new markets. In this article I focus on the theoretical foundations of these processes, proposing a theoretical framework to analyze them. The essay provides a contribution in the following two directions: • a discussion of the different levels of organization through which exaptations emerge in a market system; • an analysis of the complex links between exaptation and degeneracy (a many-tomany rather than one-to-one map between structure and function). Using this theoretical framework, I focus on the need for an analysis of the consequences of exaptations, arguing that exaptations may contribute to emerging degeneracy, which, in turn, may trigger further exaptations. In market systems one form of degeneracy is the coexistence of many structurally different artifacts providing at least in part the same functionality. I present historical examples that suggest that degeneracy increases the complexity of the system: the attribution of functionality previously provided by existing artifacts to new artifacts potentially able to provide them in a new way is a significant process giving raise to new artifacts and new marketsInnovation; Exaptation; Degeneracy; Adaptation;

Comparative Analysis of Five XML Query Languages

XML is becoming the most relevant new standard for data representation and exchange on the WWW. Novel languages for extracting and restructuring the XML content have been proposed, some in the tradition of database query languages (i.e. SQL, OQL), others more closely inspired by XML. No standard for XML query language has yet been decided, but the discussion is ongoing within the World Wide Web Consortium and within many academic institutions and Internet-related major companies. We present a comparison of five, representative query languages for XML, highlighting their common features and differences.Comment: TeX v3.1415, 17 pages, 6 figures, to be published in ACM Sigmod Record, March 200

Graph Summarization

The continuous and rapid growth of highly interconnected datasets, which are both voluminous and complex, calls for the development of adequate processing and analytical techniques. One method for condensing and simplifying such datasets is graph summarization. It denotes a series of application-specific algorithms designed to transform graphs into more compact representations while preserving structural patterns, query answers, or specific property distributions. As this problem is common to several areas studying graph topologies, different approaches, such as clustering, compression, sampling, or influence detection, have been proposed, primarily based on statistical and optimization methods. The focus of our chapter is to pinpoint the main graph summarization methods, but especially to focus on the most recent approaches and novel research trends on this topic, not yet covered by previous surveys.Comment: To appear in the Encyclopedia of Big Data Technologie

Using SPARQL – the practitioners’ viewpoint

A number of studies have analyzed SPARQL log data to draw conclusions about how SPARQL is being used. To complement this work, a survey of SPARQL users has been undertaken. Whilst confirming some of the conclusions of the previous studies, the current work is able to provide additional insight into how users create SPARQL queries, the difficulties they encounter, and the features they would like to see included in the language. Based on this insight, a number of recommendations are presented to the community. These relate to predicting and avoiding computationally expensive queries; extensions to the language; and extending the search paradigm

Innate immunity and neuroinflammation

Copyright © 2013 Abhishek Shastri et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Inflammation of central nervous system (CNS) is usually associated with trauma and infection. Neuroinflammation occurs in close relation to trauma, infection, and neurodegenerative diseases. Low-level neuroinflammation is considered to have beneficial effects whereas chronic neuroinflammation can be harmful. Innate immune system consisting of pattern-recognition receptors, macrophages, and complement system plays a key role in CNS homeostasis following injury and infection. Here, we discuss how innate immune components can also contribute to neuroinflammation and neurodegeneration

Functional Dependencies Unleashed for Scalable Data Exchange

We address the problem of efficiently evaluating target functional dependencies (fds) in the Data Exchange (DE) process. Target fds naturally occur in many DE scenarios, including the ones in Life Sciences in which multiple source relations need to be structured under a constrained target schema. However, despite their wide use, target fds' evaluation is still a bottleneck in the state-of-the-art DE engines. Systems relying on an all-SQL approach typically do not support target fds unless additional information is provided. Alternatively, DE engines that do include these dependencies typically pay the price of a significant drop in performance and scalability. In this paper, we present a novel chase-based algorithm that can efficiently handle arbitrary fds on the target. Our approach essentially relies on exploiting the interactions between source-to-target (s-t) tuple-generating dependencies (tgds) and target fds. This allows us to tame the size of the intermediate chase results, by playing on a careful ordering of chase steps interleaving fds and (chosen) tgds. As a direct consequence, we importantly diminish the fd application scope, often a central cause of the dramatic overhead induced by target fds. Moreover, reasoning on dependency interaction further leads us to interesting parallelization opportunities, yielding additional scalability gains. We provide a proof-of-concept implementation of our chase-based algorithm and an experimental study aiming at gauging its scalability with respect to a number of parameters, among which the size of source instances and the number of dependencies of each tested scenario. Finally, we empirically compare with the latest DE engines, and show that our algorithm outperforms them

An Analytical Study of Large SPARQL Query Logs

With the adoption of RDF as the data model for Linked Data and the Semantic Web, query specification from end- users has become more and more common in SPARQL end- points. In this paper, we conduct an in-depth analytical study of the queries formulated by end-users and harvested from large and up-to-date query logs from a wide variety of RDF data sources. As opposed to previous studies, ours is the first assessment on a voluminous query corpus, span- ning over several years and covering many representative SPARQL endpoints. Apart from the syntactical structure of the queries, that exhibits already interesting results on this generalized corpus, we drill deeper in the structural char- acteristics related to the graph- and hypergraph represen- tation of queries. We outline the most common shapes of queries when visually displayed as pseudographs, and char- acterize their (hyper-)tree width. Moreover, we analyze the evolution of queries over time, by introducing the novel con- cept of a streak, i.e., a sequence of queries that appear as subsequent modifications of a seed query. Our study offers several fresh insights on the already rich query features of real SPARQL queries formulated by real users, and brings us to draw a number of conclusions and pinpoint future di- rections for SPARQL query evaluation, query optimization, tuning, and benchmarking

A Trichotomy for Regular Simple Path Queries on Graphs

Regular path queries (RPQs) select nodes connected by some path in a graph. The edge labels of such a path have to form a word that matches a given regular expression. We investigate the evaluation of RPQs with an additional constraint that prevents multiple traversals of the same nodes. Those regular simple path queries (RSPQs) find several applications in practice, yet they quickly become intractable, even for basic languages such as (aa)* or a*ba*. In this paper, we establish a comprehensive classification of regular languages with respect to the complexity of the corresponding regular simple path query problem. More precisely, we identify the fragment that is maximal in the following sense: regular simple path queries can be evaluated in polynomial time for every regular language L that belongs to this fragment and evaluation is NP-complete for languages outside this fragment. We thus fully characterize the frontier between tractability and intractability for RSPQs, and we refine our results to show the following trichotomy: Evaluations of RSPQs is either AC0, NL-complete or NP-complete in data complexity, depending on the regular language L. The fragment identified also admits a simple characterization in terms of regular expressions. Finally, we also discuss the complexity of the following decision problem: decide, given a language L, whether finding a regular simple path for L is tractable. We consider several alternative representations of L: DFAs, NFAs or regular expressions, and prove that this problem is NL-complete for the first representation and PSPACE-complete for the other two. As a conclusion we extend our results from edge-labeled graphs to vertex-labeled graphs and vertex-edge labeled graphs.Comment: 15 pages, conference submissio

Ontological Matchmaking in Recommender Systems

The electronic marketplace offers great potential for the recommendation of supplies. In the so called recommender systems, it is crucial to apply matchmaking strategies that faithfully satisfy the predicates specified in the demand, and take into account as much as possible the user preferences. We focus on real-life ontology-driven matchmaking scenarios and identify a number of challenges, being inspired by such scenarios. A key challenge is that of presenting the results to the users in an understandable and clear-cut fashion in order to facilitate the analysis of the results. Indeed, such scenarios evoke the opportunity to rank and group the results according to specific criteria. A further challenge consists of presenting the results to the user in an asynchronous fashion, i.e. the 'push' mode, along with the 'pull' mode, in which the user explicitly issues a query, and displays the results. Moreover, an important issue to consider in real-life cases is the possibility of submitting a query to multiple providers, and collecting the various results. We have designed and implemented an ontology-based matchmaking system that suitably addresses the above challenges. We have conducted a comprehensive experimental study, in order to investigate the usability of the system, the performance and the effectiveness of the matchmaking strategies with real ontological datasets.Comment: 28 pages, 8 figure