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Posts Tagged ‘SAC’

SAC – Paper Notification

October 16th, 2011 by Martin No Comments

Our paper was accepted at the SAC 2012 as a poster paper. It is not what we hoped for, but considering that the paper is the first tangible scientific result of our work with students (Martin Perebner, Matthias Neumayr), we believe that is a good result. Overall, our presentation had some weakness in terms of the general quality of the paper (e.g., grammar mistakes and typos – ? @johannes2112 proofread.paper) and problems in concerning its technical maturity. We will improve on this and produce an improved version of our paper for the conference.

Since we try to follow an open scientific paper writing process, we would like to share the comments of our reviewers who we thank for their input:

 

Title: Mobile ad hoc Workflows with Twitter

Authors: Martin Treiber, Daniel Schall, Schahram Dustdar and Christian Scherling
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REVIEWER #1
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Reviewer’s Scores
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Technical Content and Accuracy: 2
Significance of the Work: 5
Appropriate Title, Introduction, and Conclusion: 3
Overall Organization: 2
Appropriateness for SAC: 6
Style and Clarity of the Paper: 3
Originality of Content: 5
OVERALL RECOMMENDATION: 2

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Comments
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The choice of scenario is interesting and convincing, however personally I am a
skeptical of its potential for uptake, as I believe that radio comm will
continue to dominate events organization for some time to come — one factor
that must be  considered is the skillset needed for users to take advantage of
this  technology. Indeed, what is certainly missing from the paper is a
usability test of this idea in the field.

More fundamentally, it is not clear who does what and when — this is directly
related to my previous        comment.  For example, in Listing 4, it is not clear to
me who executes each of these commands. Surely, some human is involved in
taking pictures and videos? so you inherently have humans as workflow actors.
But this does not emerge from your presentation.
It seems to me there are at least three roles: workflow designer, workflow
executor (whoever launches the workflow), and apparently, humans in the loop
who execute some of the actions. It would be good to clearly identify in your
scenario when each of these actions happen (I find it hard to imagine that a
field worker would sit down and assemble a workflow during operations, for
example).

Also, the authors seem to forget to clarify the relationship between a workflow
model and Twitter. Oddly, this is not explained at all and it’s referred to
quite casually for the first time in sec. 3.  It still is not clear to me why
the architecture relies on twitter messaging.
is this about exchanging  pre-formatted tweets between colleagues? and without
the flexibility of writing your own tweet, it seems.

more detailed comments:

sec 3.        there are many inaccuracies that make the presentation less than
satisfactory.

-  what justifies your specific choice of process model? (i.e. no nesting)
- there are odd circularities in some of the definitions, for instance
“Likewise, the ad-hoc and per- sonal characteristics of Tweetflows need to be
addressed by a lightweight workflow language that we call Tweetflows.”

- there are also semantic inaccuracies:  “unstructured activities” is not the
same as “a set activities that can be executed in any order”. You seem to refer
to independent activities.
-  Similarly: “after an activity is completed, the result serves as input for
the next activity and triggers its execution.”        is not a transitionCondition
that activities can have: it seems inevitable as it’s part of the core process
model.

- “The object describes the type of input.”  what “object”? mapping the types
to what?

Related work.
I am not convinced that crowdsourcing is  close enough to this work to even
be considered related.

============================================================================
REVIEWER #2
============================================================================

—————————————————————————
Reviewer’s Scores
—————————————————————————

Technical Content and Accuracy: 2
Significance of the Work: 5
Appropriate Title, Introduction, and Conclusion: 4
Overall Organization: 4
Appropriateness for SAC: 7
Style and Clarity of the Paper: 3
Originality of Content: 5
OVERALL RECOMMENDATION: 3

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Comments
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Very interesting paper and approach, I quite like the concept explained in that
paper.

Unfortunately, it probably lacks some maturity. I think I would have
appreciated some more detail on how users get to interact with the system in
practice. Some hints are provided but it’s not enough. The use of a personas
and stories approach would have been welcome to give more clarity. Also, the
workflow example would have been a good opportunity for that work, presenting a
small scenario of how people would go through the workflow.

============================================================================
REVIEWER #3
============================================================================

—————————————————————————
Reviewer’s Scores
—————————————————————————

Technical Content and Accuracy: 4
Significance of the Work: 5
Appropriate Title, Introduction, and Conclusion: 3
Overall Organization: 2
Appropriateness for SAC: 5
Style and Clarity of the Paper: 2
Originality of Content: 5
OVERALL RECOMMENDATION: 2

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Comments
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General comments
- Too many grammar and spelling errors; more diligent proof reading required b4
submission to a conference or symposium (e.g. third paragraph of introduction:
“to” missing; many more)
- precise definition of “ad hoc workflow and “service workflow” missing (don’t
assume reader to come from BPM community)
- the festival example is intuitive but not presented in a technically deep
enough fashion (what are the exact requirements by stakeholder and what are the
technical design issues that make existing technology like production workflows
inappropriate?); consider using a recognized SE method like OOAD or agile
practices to present the case study accurately
- it did not get clear to me what your contribution is – is it the Tweetflow
language? or did Tweetflow exist already and you use/extend it for mobile
context?
- crowd sourcing kinds of falls out of the blue in Section 3; proper
introduction needed
- Section 3 remains on a rather abstract level, the language is only introduced
via a listing and a table; this makes your novel concepts hard to grasp and
assess; I would recommend to look at leading text books and popular tutorials
for general purpose languages to get a feel for inspiration how to introduce a
language (formal definition of concrete syntax can then go to appendix)
- language introduction in Section 3 contains a lot of comparisons e.g. with
BPEL; this makes the text hard to follow. I would recommend a refactoring so
that the BPEL comparisons are co-located in one section (design principles:
high cohesion in one section, low coupling between sections)

Detailed comments
- Title has the word Twitter, introduction does not mention Twitter at all
- Abstract: which established SOA principles do you leverage? please be precise
- Introduction, 2nd paragraph (p): very shallow arguments against WS-*
(complexity is only perceived, as many production references using WS-* show;
REST has hidden complexities and re-assigns middleware and tool design issues
back to the programmer)
- capitalization of headings and sub-heading is inconsistent e.g. in section
2.2 (Lightweight Workflow Model vs. Ad hoc creation…)
- it did not get clear to me in 2.2 why the BPEL features are not needed/used
for ad hoc coordination; not having BPEL compatible interfaces on mobile
devices is not an argument as one could write adapters, and there is work
around BPEL+REST
- absence of GPS on laptops is not an argument either, see e.g. USB GPS devices
and Web cams (general point: be careful with weak arguments, and claims w/o
evidence)
- don’t assume reader to be familiar with specific concepts such as the Amazon
Mechanical Turk; do you really need the analogy? if yes, please provide brief
introduction and positioning
- Figure 2 appears before Figure 1
- paper ends rather suddenly with a very short section on future work there are
no conclusions and there is no summary

your ikangai science team

Creating contextualized mobile workflows

August 8th, 2011 by Martin No Comments

This post continues our work (introduction , application scenario) on mobile workflows which we conduct during a public paper writing process.
Context information is considered as important additional information source for workflows during their execution. Existing approaches use context information (location, time, user profiles) during the execution for various purposes, such as adaptation. All approaches need to specify the type of contextual information during the design time which are bound during the execution of the workflow. However, in situations, where the format of context information cannot anticipated a-priori, we need to follow a different approach. This is illustrated by our working example, where context information can be available in different formats: pictures, geo coordinates, textual descriptions or videos. Furthermore, the availability of this contextual information may even be discovered directly at the site. For example, a picture of an entrance gate with a person standing next to it can be used to assess the size of the gate. Thus, it is very difficult to It’s very difficult to create generic context slots because of the arbitrary nature of context information. To overcome this limitation, we propose to integrate concrete context data the design of the workflow. In doing so, we use context information where it is available: at the location where the workflow is designed.

Example. The power generator delivery service must know where to deliver the power generator and requires information about the location infrastructure. Thus, a request a posted, to collect pictures of the festival location and to upload them to a picture sharing site to make it available for the delivery company. A video of the organizer is made explaining the for security that the presenter of this video is allowed backstage access to install the power generator. A code snippet of this workflow is shown below.

LG didCreate.TwitterList http://festival.org #powergeneratordelivery
SR @security follow.TwitterList http://festival.org #powergeneratordelivery
SR make.Pictures location=festival | SR upload.Pictures url=http://festival.org #powergeneratordelivery
SR comment.Pictures url=http://festival.org #powergeneratordelivery
SR @delivery.folllowTwitterList http://festival.org #powergeneratordelivery
SR @delivery download.Pictures http://festival.org
SR @delivery notify.arrival @security
LG didUpload.Video http://festival.org | SR @secretary email.Video @delivery

In a first step, we create a Twitter follower list that severs as black board for the exchange of messages concerning the Tweetflow. This makes it easy for all participants to follow the Tweets that are exchanged in the context of the delivery of the power generator workflow. Context information (pictures, video) is directly linked in the Tweets of the Tweetflow. It is worth noticing, that the actual interpretation of the context data depends on the receiver of the message. In our example, context information such as pictures or video are interpreted by people and people provide the actual service.

your ikangai science team

Application Scenario

August 1st, 2011 by Martin 2 Comments

This post is the second part of our public paper writing experiment for the SAC 2012, the 27th Symposium On Applied Computing. The complete version of the paper can be foundhere and will change in the in the course of the next weeks.

We now introduce a more complex application scenario. The organization of music festivals is a complex task and requires the coordination of dozens of mobile workers which offer security, technical or other support (human provided) services on a festival site. Basically, these workers are in charge of maintaining the functioning of the festival infrastructure (power generators, stage lighting, sound) and ensure the safety of the spectators.
In our application scenario, we consider the case of having problems with power outages on one of the festival stages, due to problems with the local power supply. To solve this problem, we require to organize an auxiliary power generator and to transport it to the stage. This process involves the coordination of local workers and services which provide the power generator and for the transport of the power generator.
For example, the power generator transport team needs to know about the characteristics of the festival location, like narrow roads or other obstacles that can hinder the transport. The security workers must know when the power generator arrives, to clear the transportation route (e.g., moving spectators away) in time and to lead the transport team to the stage. Stage technicians must inform the provider of the power generator about the electrical specifications that are necessary to connect the power generator to the stage.
While scenarios like the aforementioned can be modeled and handled with existing workflow languages and systems, there are several challenges that limit the application of existing workflow systems.

2.1 Challenge One: Context information
It is very difficult to foresee exceptions during the design of a workflow. In particular, in scenarios like festivals, we need to handle different physical execution contexts. For instance, the transportation of a power generator may be difficult to a festival location A, because of infrastructure limitations (narrow or muddy roads). The same might pose no problem on festival location B, because B has a highway nearby. Thus, we need to weave contextual information into the workflow at design time, which in fact can only be known at the location. This context information can take various formats: photos of the festival location can inform transport teams about the condition of roads (e.g., a muddy road because of rain), sensor data of mobile phones can give the exact geo location (instead of the address which can be ambiguous).

2.2 Challenge Two: Ad hoc creation of a workflow in a mobile environment
Workflow editors are tools (Active BPEL, express flow) that require at least a laptop to work. While laptops are per-se mobile, the size of a laptop limits its mobility. In scenarios like festivals, creating ad hoc workflows that includes context information, walking around with a laptop is not practical. In addition, laptops might do not provide the necessary sensor array to capture context information (GPS data, camera). Consequently, we need a tool that can be used on mobile phones to create the workflow in situ and be able to integrate sensor data (GPS, pictures) during the design of the workflow.

2.3 Challenge Three: Lightweight communication interfaces
Workflow languages like BPEL provide a large set on functions that are not used for ad hoc coordination (transactions, rollback). Evidently, BPEL has simply a different design goal which hinders its application in the mobile domain: connect and coordinate businesses and exchange data between businesses with complex business processes. On a conceptual level, we do the same in our working scenario: we connect different service providers and coordinate their activities. However, we operate on a different scale in terms of hardware and software. Our workers have access to services on their mobile devices (e.g., google maps) which do not offer a BPEL compatible service interfaces. Thus, we need to integrate these mobile services with a lightweight coordination and communication infrastructure which is available on mobile devices.

2.4 Challenge Four: Working the Crowd
In contrast to traditional workflow systems which are used in static settings with a small number of participants, we have a considerably larger number of participants (which may be subject to change). As discussed in our scenario, we may have to get context data like photos of the location. For this purpose, we can advise local workers and volunteers to take pictures of different areas of the location with their mobile devices. After selecting the most meaningful location photos (entry gates, streets, transportation routes), the transport team can access these and assess the characteristics of the festival location for selecting the proper transport vehicle. This task requires the ability to address a crowd consisting of volunteers and local workers in order to perform a specific task.

your ikangai science team

SAC Paper – Introduction

July 18th, 2011 by Martin 2 Comments

Service compositions are one of the key concepts of Service Oriented Computing (SOA). The SOA standard Stack (WS-*) facilitates the reuse and interoperability of Services across company boundaries. Today, there is a large number of languages and tools available that targets the composition of Services out of already existing ones. Languages like BPEL, YAWL and tools like JOpera, Active BPEL Designer support the creation of composite SOA Services to create value added Services.

More recently, Service mashups build of Restful Services were proposed as alternative to the SOA stack, because the of the perceived complexity of the WS-* stack. Restful Service compositions (Bite, et al) are considered as means for technical unexperienced users to create Service compositions, without having to understand Service concepts like WDSL or SOAP. Generally speaking, Service compositions move from an enterprise setting with complex standards and tooling towards a more end user driven, lightweight setting.

By following this development, we consider composing Services in an mobile environment as a potential next step. As we move the creation of Service compositions into the mobile domain, we also change the character of Service compositions. In a mobile Service (composition) environment, we do not target complex, long running Service compositions. Instead, we aim for the creation of ad hoc and personal Service compositions which are created and executed spontaneously. By emphasizing the personal aspect of Service compositions, we implicitly take their social aspect into account: personal Service compositions are created in a social context of the Service composer. For instance, a user decides to go out with friends to have dinner, to watch a movie and to a bar for cocktails. This requires to coordinate the users friends according their availability, their restaurant recommendations and their movie taste. Furthermore, the ad hoc creation of a Service composition implicitly adds several additional context dimensions to the Service composition: attributes like location of the Service composer, time, language are available and can be included in the Service composition.

your ikangai science Team

The current version of the paper can be found here. The paper is work in progress and will be updated in the next weeks in the process of writing a scientific paper in the public.

SAC Paper – Application Scenario Thoughts

July 7th, 2011 by Martin No Comments

We discussed the application scenario in more detail and Martin pointed out that both, the creation and the execution of a Tweetflow happens in a mobile environment. Thus, a Tweetflow is created and executed in a mobile context. This gave Daniel and me the idea, to enrich the workflow during the design time with context data. In our case, this would be sensor data like pictures taken with the camera, location information, movement data or gestures. In doing so, we implicitly contextualize the creation of the Tweetflow. This has the very interesting consequence that we weave context information into the design phase of Tweetflows. For example, one could think of a Tweetflow that is created to solve an immediate problem like having insufficient power on a festival location (we discussed this in a previous post). Without having to specify the required context information a priori, we can enrich a Tweetflow (consisting of several (human) activities like connecting diesel generators to stages) with geo-location data and images from the actual location. The geo-location can help organizing the transport and images can be used to inform about peculiarities of the location (e.g., a narrow gate that prevents bigger trucks from entering the festival location or a people crowd gathered around a stage).
The inclusion of context in the design of a Tweetflow hinders its universal application. But, since ad hoc Tweetflows are not designed to be generic solutions in the first place, this should not pose a problem. Furthermore, the issue of context integration is actually a technical one, because we need to address how to “put” context data into the Tweetflow language and how to access it during the execution of the Tweetflow.

your ikangai science Team

SAC Paper Ingredients

July 6th, 2011 by Martin 1 Comment

One of the problems with our current SAC paper is its positioning. We already discussed this in our last post and now we are going to elaborate on this topic by investigating some of the key “ingredients” of our proposed approach. We have four main ingredients that we wish to discuss:

Ingredient Number One:Social network. People are connected and know each other. What is that good for? Does it help us? If so, how? Can we use data like user profiles for our purpose?

Ingredient Number Two: Mobile Devices. Being permanently online appears to be the future. We are connected to the Web all the time. This can only be done with mobile devices, because we always have them with us. What is the impact of this for our work? One consequence is that we can build workflows anytime/anyplace, if we have the means to do so. This is the argument for needing a mobile workflow editor (which we fortunately already have:-))

Ingredient Number Three: Mobile Services. Mobile devices equals mobile Services. But how do Services “look” like? They aren’t SOAP Services, that is for sure. Are they Restful Services? Or can we think of a different abstraction to use? Again, we have an answer for this. In our previous work, we introduced the concept of App as a Service which can be employed to make use of Apps. However, Apps are self-contained, and do not come with public interfaces that can be addressed. Thus, we require a programming model that is able to plug into the social network directly from the App. Actually, this has been done to some extent by social platforms like Facebook/Twitter; they provide an API that allows to write “social” Applications that work on their platform.

Ingredient Number Four: Tweetflows. If we have mobile Services, we need to compose/orchestrate them in the context of the social network. How do we do this? This is related to the question of integrating Apps into social networks. In contrast to existing approaches which provide no communication means between different social Apps, we will investigate this aspect in extensive detail.

your ikangai science Team