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Abel 2007 Medha Question 1 +	When the authors say that they have come u … When the authors say that they have come up with this approach to save time which might be spent in exercising access control by first evaluating plain query on RDF store and then applying access control to each and every triple, can they give some hint about how much time was saved by their approach on similar datasets? ved by their approach on similar datasets?
Abel 2007 Medha Question 2 +	ONE: The given example is a very tiny one … ONE: The given example is a very tiny one w.r.t original query and set of policies defined. Is there any estimate available about what is the number of typical policies on a decent size RDF triple store. TWO: How big a transformed query turns after applying all the policies (THREE:) and especially if multiple policies defined by multiple people get applied? The paper says that if deny policy is applicable then access triple is denied, but then this generic approach doesn't seem to embrace some user's preference to allow access to some information, unless a within policies is provided. E.g. Alice says allow access to (l3s:alice, foaf:phone, Z) and Harry says deny access to (X, foaf:phone, Z)? ry says deny access to (X, foaf:phone, Z)?
Abel2007enabling presented by Tim Lebo 25 sept 2008 Gregory Todd Williams 1 +	ONE: Section 1 states that evaluating comp … ONE: Section 1 states that evaluating complex conditions "for each triple to be potentially returned by the metadata store is not affordable, since it is too expensive in terms of time." Ignoring the context-dependent parts of a policy (which can be verified before query execution as in the presented system), this seems to be essentially exactly what the proposed system does by adding new expressions to the query. TWO: Understanding that it would make for a "repository-dependent and not portable" solution, would there be efficiency benefits to performing these conditions at the triple store level where a clear distinction could be made between the query pattern and the policy conditions? e query pattern and the policy conditions?
Abel2007enabling presented by Tim Lebo 25 sept 2008 Gregory Todd Williams 2 +	In Section 4.3, Example 1, policies 1–3 are said to return ({Var8, foaf:currentProject, Var9}, {(Var8 = Person), (Var9=l3s:rewerse)}). Why are Var8 and Var9 introduced in a path expression only to be immediately constrained in the binary expression?
Abel2007enabling presented by Tim Lebo 25 sept 2008 Jesse Weaver +	ONE: How does this approach apply to infer … ONE: How does this approach apply to inferred triples? For example, consider PB subPropertyOf PA. If a user is denied triples using PA but has access to triples using PB, he/she may be able to effectively "access" (via inference) some of the PA triples. TWO: Also, perhaps the user shouldn't be able to see triples that are inferred from triples to which they do not have access. Is this accounted for? o not have access. Is this accounted for?
Abel2007enabling presented by Tim Lebo 25 sept 2008 Joshua Taylor 1 +	Is there any provision made for whether re … Is there any provision made for whether restricted triples may be indirectly accessed? For instance, A query could be posed asking for individuals ''?x'' and ''?y'' where ''?x hasPhone ?z'' and ''?y hasPhone ?z''. If both ''Joe hasPhone 555-5555'' and ''Mary hasPhone 555-5555'' are restricted, then answering the aforementioned query would be permissible since even answering with ''?x ↦ Mary, ?y ↦ Joe'' wouldn't even indirectly allow either restricted triple to be reconstructed. While this example might seem contrived, it is easily conceivable that with a sufficient number of joins, restricted triples could be used without the particular triples being available from the end result. iples being available from the end result.
Abel2007enabling presented by Tim Lebo 25 sept 2008 Shangguan 1 +	About DISUNIFY(e, θ) function in Section … About DISUNIFY(e, θ) function in Section 4.1. The author introduced the function DISUNIFY(e, θ) and stated that "...The purpose of this function is to extract variable substitutions in order to be able to reuse path expressions in the final RDF query, even if ...". So, why do we need to extract variable substitutions? Why can it help reuse path expressions? And also, what's the purpose of reusing path expressions? s the purpose of reusing path expressions?
Abel2007enabling presented by Tim Lebo 25 sept 2008 Shangguan 2 +	About descriptions of policies. In section 4.2, the author just gave a high-level descriptions of the policies. I'm curious about how to convert this high-level description into the more specific form described in the beginning of this section?
Abel2007enabling presented by Tim Lebo 25 sept 2008 Shangguan 3 +	ONE: About DEFINITION_2 in section 4.3. Th … ONE: About DEFINITION_2 in section 4.3. The author only stated that σ and σ'' (double prime) might exist. Suppose that they do exist, how can we get it? TWO: Another thing that confused me a lot is the example of the returned value after applying pol1_pol4 onto some sample RDF triples, in which Var1-Var9 are not clearly defined. I can understand that this is only an example, so some information fragments might get lost due to space considerations. But, we come back to the example of expanded RDF query in Section 5, things become confusing again --the Var's in this example are still not defined. So, how do we handle this problem? efined. So, how do we handle this problem?
Abel2007enabling presented by Tim Lebo 25 sept 2008 Shangguan 4 +	About evaluation part. The author only ga … About evaluation part. The author only gave the response time when increasing the number of FROM and WHERE clauses. Is this response time acceptable? What portion does it take in the overall query response time? Since the RDF queries are expanded, will this bring extra overheard to the query processing and execution? Moreover, the author should compare with response time resulting from other access control mechanisms, as stated in section 3. ontrol mechanisms, as stated in section 3.
Abnormal Nodes Ankesh +	# I wish authors could have written a lin … # I wish authors could have written a line describing MI & PMI. It would be useful to extend this approach to consider semantic relations between labels (subPropertyOf). # I perceive a disconnect between method of finding outliers and the explanation that is generated. Do you see that as a problem? (Has it got anything to do with getOutliers(profile) algorithm?) Outliers are found using distance based algorithm, where as explanation is generated by selecting the features used by the classifier to classify the nodes into outliers and non-outliers found earlier. I'm not really able to connect the two things. Because o/w we can simply train our classifier to classify based on feature selection- and we can isolate outliers from it. tion- and we can isolate outliers from it.
Alvaro Graves SemRank Gregory Todd Williams 1 +	The paper presents three different semanti … The paper presents three different semantic associations: ρ-Path, ρ-Iso, and ρ-Join. Few details are given about the ρ-Iso Association, but the description in section 2 describes it: "The paths p = p11, p12 ... p1n originating from r1 and p' = p11', p12' ... p1n' originating from r2 are semantically similar in that the corresponding edges in both paths are related in a subproperty relationship, therefore r1 and r2 are related by virtue of this similarity." This definition seems overly restrictive and simplistic to me. Can the presented ranking system be extended to allow for similar associations based on a tree or DAG of properties (not just a single path) from r1 and r2? Alternatively, could the ρ-Iso Association be extended to distinguish the similarity of r1 and r2 based on the similarity of rm and rn (the endpoints of the paths p and p')? rn (the endpoints of the paths p and p')?
Alvaro Graves SemRank Jesse Weaver +	At the end of section 3.1, I(ps) is define … At the end of section 3.1, I(ps) is defined as the sum of the specificity and the theta-specificity of path ps. This definition equally weights the two specificities; do you think this is fair? Also, at the end of section 3.4, SEMRANK(SA) is defined as equally weighted product of the information gained, the refractions (plus one), and the semantic match of keywords (plus one). Do you think equal weighting is fair? For example, maybe the semantic match of keywords deserves a heavier weight because it is affected by the user and perhaps therefore could be considered a better indicator of what would be an appropriate rank for the user. What do you think? ate rank for the user. What do you think?
Alvaro Graves SemRank Joshua Shinavier 1 +	Given that SemRank has exponential time co … Given that SemRank has exponential time complexity and cannot be evaluated for larger data sets, what is an empirical evaluation of the top-K algorithm likely to reveal? The authors expect that it will produce an ordering that is reasonably close to SemRank, but they go on to mention that the refraction count can only be computed at the end of the path building phase (so, the refraction count of a child path does not predict the refraction count of a parent path). Did I read this correctly? This seems important, because the top-K approximation would be critical to any real-world application of the presented technique -- SemRank alone is clearly not suitable for discovery of associations in a large graph. iscovery of associations in a large graph.
Alvaro Graves SemRank Joshua Taylor 1 +	in '''5 EMPIRICAL EVALUATION''' we read, " … in '''5 EMPIRICAL EVALUATION''' we read, "There are an increasing number of publicly available RDF data sets from those that are narrowly focused (e.g. DBLP, ODP) to those with broader scope covering multiple domains (e.g. TAP, SWETO). However, most of these presented limitations that made them unsuitable as evaluation testbeds for SemRank. … Consequently, the evaluation of SemRank discussed here was done on synthetically generated data. The data generation was guided by rules to ensure that data distributions mirror the real world." The authors state that they believe that "testbeds for the Semantic Web" are in "early developmental stages". Nonetheless, it seems like they are claiming that the ''real'' world data available to them does not mirror the real world, and so come up with their own model of the real world. How accurate is their perception that the current datasets do not accurately reflect the real world, and how realistic is their expectation that the structure will evolve significantly? More importantly, how does this affect their evaluation. Have they simply developed data sets on which SemRank is promising, or have they shown that SemRank is ready for the World of Tomorrow? emRank is ready for the World of Tomorrow?
Alvaro Graves SemRank Shangguan +	Computation Complexity Issues. Please note … Computation Complexity Issues. Please note that this question may be outside of the scope of this paper (possibly due to space limit. I'm a little interested in the computation complexity of the method proposed in this paper. As we know, response time will be the key to any search engines, and thus the key to ranking algorithms. But it seems to me that the author did not include this part in the paper -the only empirical results presented in this paper were used to prove that the SemRank method works as expected. And also, given the complexity of SemRank, it will be possible for us to figure out whether it scales well or not. figure out whether it scales well or not.
Alvaro Graves SemRank Shangguan 2 +	(MAY BE DIGRESSIVE) After reading all thro … (MAY BE DIGRESSIVE) After reading all through the paper, I was thinking what if the RDF docs are updated to some extent, e.g., adding only a few number of properties? As far as I can guess after reading, the system has to recalculate all the metrics included in the paper. But, is there any better way, such as incremental computing, to improve performance? emental computing, to improve performance?
Alvaro Semantic Obligation Policies Jesse Weaver +	Section 4 says that the authors' notion of … Section 4 says that the authors' notion of a graph pattern is borrowed from SPARQL, but before that they say that it is a set of triple patterns and that "a graph pattern can be used to represent a conjunctive query." This idea doesn't align with a SPARQL graph pattern but rather with a SPARQL '''basic''' graph pattern (a specific kind of SPARQL graph pattern; see http://www.w3.org/TR/rdf-sparql-query/#GraphPattern for details). Similar to Greg's question, why wouldn't they want to allow other types of graph patterns in SPARQL, allowing for disjunction/alternation or inclusion of optional information? Consider the example in figure six. Wouldn't it be reasonable to include contact information for the employee (phone number, email, cube location... ''something'' to ensure the manager can approach the employee) ''if'' such information was available in the stream? Something like the SPARQL OPTIONAL graph pattern might be useful here, would it not? attern might be useful here, would it not?
Alvaro Semantic Obligation Policies Joshua Shinavier 1 +	The authors state that "the problem of pol … The authors state that "the problem of policy concurrency is addressed by the implicit serialization of events as enforced by our streaming model". However, they also claim that the compiler is able to "plan with large numbers of event sources". When there are multiple sources involved, concurrency certainly is an issue. It is not clear how the compiled policy, a "plan" in Stream S, would go about combining events from multiple sources. Under what conditions can event descriptions from two different sources serve as input to be matched by a single event pattern? t to be matched by a single event pattern?
Alvaro Semantic Policies GTW1 +	Conditions in the Eagle policy specificati … Conditions in the Eagle policy specification language are said to be "described as a conjunction of expressions." Is there a reason why disjunction are not allowed? Disjunction could be emulated by simply producing new conditions, but this runs the risk of over burdening the person charged with maintaining the policies. Wouldn't many real-world conditions involve disjunctions, making it a desirable feature? Why does section 4 restrict the use of variables to just the subject and object of an RDF triple pattern? Are there policies that would benefit from the ability to match on the semantic relationships between individuals, not just the individuals themselves? Is there any provision in the system to support graph pattern matching against multiple discrete events? Could this be handled by a general PE? The evaluation uses what seems like a rather complex setup of randomly generated PEs and RDF graphs with no real discussion of how this might simulate data used in real policies. Is this expected to have any relationship to real-world policies? e any relationship to real-world policies?
Ankesh Sep11 Jesse Weaver +	The paper mentions that variables are repl … The paper mentions that variables are replaced by constants from filter expressions, but depending on the system, the two forms of the query may mean different things. As an example, consider: SELECT ?s WHERE { ?s <test:p> ?o . FILTER(?o = "true"^^xsd:boolean) } According to SPARQL, the '=' operator here checks for _boolean_ equality if ?o is bound to an xsd:boolean literal. Therefore, if ?o binds to "1"^^xsd:boolean (non-canonical but valid lexical representation), FILTER "passes". However, with variable replacement, the query would become: SELECT ?s WHERE { ?s <test:p> "true"^^xsd:boolean . } Depending on the system, this may not be equivalent (although it could be). Does DARQ account for this? it could be). Does DARQ account for this?
Ankesh Summary Abox Gregory Shangguan 1 +	In Section 3.2 we read "Our goal is to def … In Section 3.2 we read "Our goal is to define criteria which are efficient to evaluate using simple queries against relational databases, while balancing the tradeoff between filtering precision and cost..." What do you think is the reason for the author to say this? Seems to me that RDB plays certain roles in the whole ABox reduction procedure. Is this assumption correct? ion procedure. Is this assumption correct?
Ankesh Summary Abox Gregory Shangguan 3 +	In Section 3.4, the paper also writes: ".. … In Section 3.4, the paper also writes: "...Finally, retrieving the image in A of an inconsistent partition Ap' is a simple database operation..." A simple DB operation seems a little profound to me, which it seems like it's pretty easy for the author... So, could you please explain how can we achieve this by using a simple DB operation? hieve this by using a simple DB operation?
Ankesh Summary Abox Gregory Todd Williams 1 +	Section 4 (and in particular Table 3b) sho … Section 4 (and in particular Table 3b) shows that all four of the LUBM test data resulted in an inconsistent filtered Abox, requiring consistency checking images in the original Abox. Do you have any insights as to why the summarization and filtering lead to this problem for all the LUBM data, and not for any of the other Aboxes? Do you think the summarization/filtering algorithms can be improved to avoid this second round of consistency checks? d this second round of consistency checks?
Ankesh Summary Abox Gregory Todd Williams 2 +	Section 3.4 describes associating with each role R that is part of a cardinality restriction the maximum number of R-neighbors that any individual a has in A. Does this require running the tableau algorithm, or is this simply a way of saying