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e-mail: elw@stderr.org Resume (somewhat out-of-date) My links at del.icio.us/elijah My photos/moblog at flickr
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Thu, 25 Jun 2009
thinks the --replace option to mysqldump is the be
2009 permanent link Fri, 19 Jun 2009
having a busy day.
2009 permanent link
@karlstolley i am very impressed with the #twitrhe
2009 permanent link Tue, 16 Jun 2009
14-14-21 or bust.
2009 permanent link
Iran protest pictures - Iran is ready to change.
2009 permanent link Mon, 15 Jun 2009
restaurant recommendation - "Double Dogs" in Bowli
2009 permanent link Wed, 10 Jun 2009
a bit perturbed at having lost all of the data on
2009 permanent link Sun, 07 Jun 2009
Told H her pants were on fire after she told a fib
2009 permanent link Mon, 12 Nov 2007
OLPC and AoIR 8.0 slideshows
2007 permanent link Mon, 10 Sep 2007
animal rescue
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calendar updates
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tiger botia update
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tiger botia (multiple)
2007 permanent link Fri, 24 Aug 2007
greek mythology personality test
Your Score: Dionysus33% Extroversion, 33% Intuition, 72% Emotiveness, 71% Perceptiveness![]()
(link) [elijahwright] 2007 permanent link
boogs!
2007 permanent link Sun, 05 Aug 2007
Bloomington OpenSolaris User Group (BTN-OSUG)
2007 permanent link Wed, 27 Jun 2007(link) [elijahwright] 2007 permanent link Thu, 22 Mar 2007
twitter
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planetplanet update
2007 permanent link Tue, 20 Mar 2007
Why Doesn't Google Calendar Format Entries Correctly... Or Does It?
2007 permanent link Tue, 25 Jul 2006
flickr brokenness
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recent movie watching
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new fishies
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Crackers
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arrrrgh.
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test post
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the tone adults supposedly can't hear
2006 permanent link Mon, 12 Jun 2006
Special Issue on FL/OSS
========================================
Call for Papers for a special issue 'Socio-technical Dynamics in the
Free/Libre Open Source Software (FLOSS) Social World' in the journal
Science Studies, an Interdisciplinary Journal for Science and Technology
Studies (http://www.sciencestudies.fi/), to be published autumn 2007
Guest Editors:
Yuwei Lin (University of Manchester) & Lars Risan (University of Oslo)
========================================
The development of Free/Libre Open Source Software not only intrigues
computer scientists to review processes and methods in software
engineering, but also stimulates social scientists to look into what
have become a mythical phenomenon of our digital era. Questions around
how distributed groups of individuals work together in an on-line
environment, seemingly without formal ties, to produce high-quality
software that acquire cross-sector acceptance continue to puzzle social
scientists. Over the past years, anthropologists, economist, historians,
lawyers, philosophers, and sociologists have tried to provide various
explanations to the phenomenon of on-line social networking, on-line
collaboration and on-line knowledge creation and sharing (i.e.
common-based peer production). However, the existing body of literature
on FLOSS faces a bottleneck, namely that of lacking a STS-inspired
empirical investigation of the multiplicity of FLOSS-practices. Here, we
try to raise some provocative questions: What kind of questions do
FLOSS-practices and networks pose to STS? And does STS really possess
theoretical tools that are good enough to analyse the FLOSS development?
Might it be that the materiality - and the immateriality - of code needs
theoretical and methodological contributions from other fields in social
sciences such as politics and economics (such as network effects, lock
in and abstract objects)? But then, that challenge is also
bidirectional: How does the theoretical vocabularies and the empirical
methods of STS add something new to the more economical understandings
of FLOSS?
This special issue aims to meet these theoretical and methodological
challenges in both FLOSS and STS studies. It does so by encouraging
research based on qualitative research methodologies and methods. Such a
qualitative inquiry challenges the universally vocal and normative way
of depicting FLOSS culture and practices (e.g. a homogeneous gift-giving
and volunteering culture). The special issue will take a practice-based
view to exploring multiple cultures and practices in developing,
localizing, appropriating, commodifying, customizing FLOSS. The issue
would also like to address the diversity in FLOSS communities through
asking how seemingly global FLOSS culture is translated (un)successfully
into different contexts and locales.
We believe that this issue will demystify several stereotypes and
misunderstandings about FLOSS and shed light on many emerging and
changing cultural and socio-technical practices in our digital society
and knowledge driven economies. Thinking reciprocally, we would also
like to allow peculiar im/materialities of FLOSS practices challenge the
way STS has traditionally dealt with socio-technical networks.
-----------------------
Instructions to authors
-----------------------
Manuscripts in English in any area relevant to the special issue should
be submitted electronically to the guest editor Yuwei Lin
<yuwei{at}ylin.org> and Lars Risan <lars.risan{at}tik.uio.no>. You will
normally receive an acknowledgement within a few days. Please provide
email addresses for all authors.
Papers, no exceeding 10,000 words including notes, references and
abstract, are accepted in electronic format, with Open Document Text
(.odt) or OpenOffice.org 1.0 Text Document (.sxw) being the preferred
formats (other formats are acceptable by prior arrangement). Files
should not be security protected, and should be anonymised. The editors
reserve the right to make the style of presentation uniform prior to
publication, whilst making every effort not to alter the content of an
article. Paper submission will be acknowledged via email. Subsequent
enquiries concerning paper progress should be made to the guest editor
Yuwei Lin <yuwei{at}ylin.org> and Lars Risan <lars.risan{at}tik.uio.no>.
For details of preparation of the manuscript, see the Science Studies
Journal website
http://www.sciencestudies.fi/?q=authors/#preparationofmanuscripts and
http://www.sciencestudies.fi/authors.
---------------
Important dates
---------------
October 29, 2006: full paper submissions to guest editors.
January 15, 2007: Guest editors and authors complete manuscripts and
round robin referee each other's articles.
February 7, 2007: Guest editors submit a complete set of articles to
Science Studies for review. Science Studies may return articles for
revision if needed before sending to outside referees.
April 25: Deadline for referee reports to be sent back to Science
Studies. Reports and decisions sent to authors and guest editors.
August 22: Final Copy Due
September - October 2007: Layout and proof-reading.
November 2007: Issue goes to press. (link) [elijahwright] 2006 permanent link Wed, 24 May 2006
T2000 / Solaris 10
2006 permanent link Fri, 14 Apr 2006
tooling around with databases
2006 permanent link Mon, 12 Dec 2005
Which OS are you?
2005 permanent link Mon, 21 Nov 2005
The top 20 geek novels, ones I've read in bol
2005 permanent link Mon, 14 Nov 2005
People love SLIS podcasts!
2005 permanent link Mon, 07 Nov 2005
elke michelmayr: a case study on emergent semantics in communities
folksonomies - what are they? comparison to taxonomies multi-user web applications that provide a simple categorization sy stem - items: web pages, images, citations tags = keywords ... can be chosen freely every user has a web page with a list of own items - sorted in reverse-chron order - can be filtered by tags public access to item collections and metadata bottom-up approach to categorization - no pre-defined model or hierarchy - inconsistencies -- synonyms, homonyms -- singular and plural versions of a tag -- keywords that conssit of two terms (ie semantic web, semantic_web, semanticweb) -- relies on aggregation of metadata -- tag frequency distribution: tags most often used to annotate an item categorize it best; no need to reach consensus -- relationships between tags evolve from metadata - amount of metadata crucial! -- number of users, lifetime of folksonomy comparison of metadata - lots of discussion about taxonomies vs. folksonomies, eg clay shirky 2005 - experiment: compare metadata from two big community projects that categorize web pages to find out about the differences - dmoz open directory project http://dmoz.org -- taxonomy for web pages -- ~ 600k concepts and about 5M instances -- available in RDF format (two big files) - social bookmarking site del.icio.us -- no official numbers; ~100k users -- download the web pages (simple html) procedure -- use only items from del.icio.us that were annotated by more than 100 users (=popular items) -- download random popular items from del.icio.us -- lookup if items are present in the dmoz collection (~25% of the items were also present in dmoz) -- 788 items with metadata from both sources (~50% of them are instances of dmoz concept Top/Computers) preparation of data - preparations (much mangling of data here...) - example: Top/Science/Math/Publication -> publication math science - how to compare? -- avg dmoz hierarchy length: 4.67 -- avg del.icio.us tags per item: 24.59 comparison -- lookup for each dmoz category (is it included in the del.icio.us tags?) -- take top 1,3,5,10,15,all tags into account --- top tag is included in ~50% of all cases --- top 5 is the fairest comparison --- top tags match more often than the less popular ones folksonomies and peer to peer networks - architectures are very diffferent -- folksonomies are centralized systems, aggregation is easy -- p2p networks are distributed, aggregation is hard. - user behavior is comparable -- act autonomously -- no central authority -- want to share information - data from a folksonomy can be used to model peers and content distribution - ... can interest-based locality be observed? - interest based locality (defn) - method -- retrieve all users from del.icio.us that store a random bookmark -- retrieve all their collections - retrieved 4 test sets -- 155, 248, 280, 551 users -- distribution of items among users nearly equal in the test sets -- avg.: 84% of items are not shared. related work adam mathes, 2004: folksonomies - cooperative classification and communication through shared metadata clay shirky, 2005: ontology is overrated: categories, links, and tags scott golder and bernardo huberman, 2005... summary - investigated the properties of metadata provided by a folksonomy - compared it to dmoz data collection - tried to find interest based locality - paper contains some other experiments i did not have time to tell you about - open questions -- is there a way to combine the bottom-up and top-down approach for creating metadata -- how much could the semantic web benefit from it? audience questions: have you thought about comparing the tags used at delicious to the meta tags provided by page authors? e.g. to detect spamming by page authors of search engines - mention of delicious director 2005 permanent link
Phillipe Cudre-Mauroux: analyzing semantic interoperability in bioinformatic database networks
1) peer data management systems 2) semantic interoperability in the large 3) the sequence retrieval system - degree distribution - analysis of giant component - weighted analysis 4) conclusions beyond keyword search - searching semantically richer objects in large scale herterogenous networks (semi-structured or structured data) decentralized data integration large scale information systems (e.g. WWW) VS distributed databases data integration: LAV/GAV - traditional database techniques (LAV/GAV) rely on centralized schemas to integrate data sources. - not applicable to our context -- scale (upper ontologies?) -- churn -- autonomy - how can we foster semantic interoperability in decentralized settings? semantic interoperability - from 'own schema' to 'known schema' - extending semantic interoperability to .... peer data management systems - pairwise mappings -- peer datamanagement systems (PDMS) - local mappings overcome global heterogeneity -- interactive query rewriting semantic mediation layer - semantic mediation layer over: - overlay layer over: - physical layer correlated/uncorrelated among the three layers. schema-to-schema graph - inter-organization of the different schemas used by the peers -- logical model -- directed -- weighted -- redundant the semantic connectivity graph - definition (semantic interoperability - - - observations - theorem - observation 1 - observation 2 semantic interop in the large - how can we analyze semantic interop in large-scale pdms? - size of the giant component the sequence retrieval system why is srs interesting? - applying our heuristics on a real large-scale corpus of interconnected databases -- more than 380 databanks -- more than 500 (undirected) links -- data used by professionals on a daily basis crawling the srs schema-to-schema graph - custom crawler - as of may 2005 (ebi repository) -- 388 nodes -- 518 edges - giant connected component (187 nodes) - power law distribution of node degrees - clustering coefficient = 0.32 - diameter = 9 results - connectivity indicator ci = 25.4 -- super critical state - size of the giant component -- 0.47 (derived) -- 0.48 (observed) graphs with same power-law degree distribution - varying number of edges analyzing weighted networks - do we have a sufficient number of 'good' mappings - introducing quality measures from the mappings -- weights -- attribute /schema level -- cf. Chatty Web (WWW03) - semantic query forwarding -- per hop forwarding behaviors -- only forward if w sub i >= tau --- tau = 0 : flooding --- tau = 1 : exact answers weighted results - same degree distribution (388 nodes) - uniformly distributed weights between 0 and 1 conclusions - analysing a real network of bioinformatic databases -- accurate results (even for relatively small networks) -- weighted / unweighted - current works -- compositions of weights along a path -- semantic random walkers -- public domain simulator - future works -- analysing other forwarding behaviors -- implementation in a real pdms (self-organizing mappings) --- gridvine references a necessary condition for semantic interoperability in the large cudre-maroux and karl aberer (ODBASE 2004) gridvine: building internet-scale semantic overlay networks ISWC2004 semantic overlay networks (tutorial) VLDB 2005 complete reference list available at http://lsirpeope.epfl.ch/pcudre 2005 permanent link
heiner stuckenschmidt: social network analysis as a basis for partitioning
motivations - the case for ontology partitioning a partitioning method - create a dependency graph - strength of dependencies ontologies are the backbone of semantic web applications more and more large ontologies become available maintenance and handling is becoming a problem the case for partitioning: distributed development and maintenance selective publication and use of terminologies manual inspection and validation editing, visualization, and reasoning an abstract view of the problem: despite the standardization of languages there is no agreement on the way ontologies are represented. - all ontologies contain classes - most organize them in a hierarchy - many define relations between classes - some provide formal definitions of classes we concentrate on partitioning ontologies into disjoint sets of concepts. class hierarchy, relations, and definitions provide input for the partitioning algorithm. overview of the process: 1) create dependency graph dependencies I: subclass relations dependencies II: shared relations 2) determine strength of dependencies relative strength networks - compute relative strength [Burt, '92] of dependencies 3) compute partitions computing islands - we use maximal line islands [Batagejl 2000] to compute partitions in the dependency graph [a set of vertices is a line island in network if and only if it induces a connected subgraph and the lines inside the island are stronger related among them than with the neighboring vertices. in particular there is a maximal spanning tree T over nodes in the island such that.... - the minimal weight in the spanning tree is called the 'height' of an island. - understanding islands - result for the example 4) improve partitioning improving partitions - islands are often very small (2-4 nodes) resulting in unwanted partitions of the ontology - observation: small islands almost always have a large height value (1 or 0.5) - approach: merge partitions with a height of 1 or 0.5 with neighboring partitions, based on strength of connection: ... ontology partitioning tool - features: -- owl and kif import -- selection of criteria -- computation of line islands -- graph export -- precision and recall measurement an experiment - data: acm topic hierarchy - partitioning method: -- relations: hierarchy -- maximal size: 100 -- merging threshold: 0.2 - evaluation: -- topics on dutch cs department home pages -- compared with root nodes of determined modules - results -- terms do correspond to major areas in CS -- quite some overlap with the extracted terms -- further experiments needed 2005 permanent link Sun, 23 Oct 2005
Wallace and Gromit: the Curse of the Were-Rabbit
2005 permanent link Thu, 20 Oct 2005
Sea Lions vs. Stateys
2005 permanent link
Wow.
2005 permanent link Fri, 14 Oct 2005
the "google *name* needs" meme
2005 permanent link |
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