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Activity 1: Research
Activity leader: Oscar Corcho
The research activity will tackle open questions in the context of large‐scale data management, including dynamicity, context sensitivity, spatial, temporal, social aspect of data, quality, and access control mechanisms. The three research work packages described below will analyze the best of breed techniques and approaches from across multiple disciplines to create roadmaps and white papers addressing each of the specific objectives. Together they address the most critical issues related to large‐scale data management in a holistic and integrated manner. As such they provide the baseline and working environment for the PlanetData Programs and the impact activities of the network; see also Section B.1.3.2 on the alignment of activities, where synergies and complementarities between different activities are discussed in more detail:
- WP1 – Data Streams and Dynamicity: The purpose of this work package is to explore the main research challenges associated with the dynamicity of large‐scale data sources. It has a special focus on data streams coming from periodic sources such as news feeds or from continuous sources such as sensor networks. The work package aims to improve storage and data management infrastructure in the context of processing data streams (and as such complements the data management work package WP5). Furthermore this work package researches the mining of streaming sources for publishing such data in more structured manners. Finally, work will be conducted on annotating streaming data sources in order to facilitate the processing, mining, and fusion of such resources.
- WP2 – Quality Assessment and Context: The aim of this work package is to develop representations and mechanisms to put data in context and assess its quality, with the possibility of repairing this. Determining the quality is essential, when selecting between different data sources or when fusing multiple data sources together. This work package also defines relevant dimensions of quality and mechanisms for measuring data quality in a multi‐ dimensional manner. These dimensions include accuracy, consistency, timeliness, completeness, relevance, interpretability, and trustworthiness. Context models will be developed or adapted to support and guide data publishing efforts in terms of augmenting data and sources with spatial, temporal, and social information. In particular, the research carried out will focus on how to represent, store, query, and reason with such aspects of data in large and distributed settings. In each case the developed mechanisms and best practises will be applied to the data provisioned in WP4 in order to establish proven guidelines on how to annotate data sources, and on how to assess quality.
- WP3 – Provenance and Access Policies: Companies, governments, and other public bodies increasingly publish and share large data sets, sometimes restricted by privacy critical concerns. The ability of a data consumer to utilize a particular data set depends thus on a number of aspects such as the mentioned privacy regulations, corporate regulations, and other security restrictions. This work package will thus explore the different dimensions of digital rights management, privacy, and access control to data sets. The work package will produce an access control specification language for describing data sets and will provide mechanisms for enforcing this access control. As a baseline, provenance takes on a major role, as provenance denotes the origin of data and may include information on how data was processed, derived, or inferred via reasoning. As such, knowledge about the provenance of data is crucial to determine its usage and access regulation and is highly relevant when establishing trust mechanisms and policies for privacy and rights management.
Activity 2: Data Provisioning and Management
Activity leader: Karl Aberer
This activity will be guided by the work conducted in the research activity and will put in place the data sets, vocabularies, benchmarks, best practices and data management technology needed to support the real‐world uptake of the representation and techniques developed by PlanetData researchers, and to educate the user community worldwide to get their data online in a useful way. To do so, the PlanetData network will establish the following work packages:
- WP4 – Data Provisioning: This work package is responsible for putting in place a comprehensive infrastructure of real‐world, real‐time data sets that match the functional requirements of the research work packages and well‐defined vertical sectors in which online data exposure is expected to bring the most benefits. Work package WP1, for example, requires huge volumes of data, in particular streaming data from blogs, sensors, or transaction logs; work package WP2 has need for spatial, temporal, and quality of data variations to experiment with its research results. The role of this work package is thus to support the work packages in the research activity and the PlanetData Programs by providing a catalogue of diverse data sets. Besides being a support activity to research, WP4 will release its own results in terms of best practices for representing and providing data sets in a self‐descriptive manner on the Web, and by supporting the creation of vocabularies for describing Web data and hosting these vocabularies. A catalogue of data provisioning tools will further stimulate the data exposure by PlanetData partners, associate partners or other user organizations.
- WP5 – PlanetData Lab: Experimenting with large volumes of data requires adequate systems and management facilities. The goal of this work package is to leverage data management technologies and infrastructures developed within and outside the project for the benefit of the research work packages. This work package is thus gathers and publishes a catalogue of recommended systems suited for particular research tasks and particular large‐scale data sets. As such WP5 yields the necessary components for testing, experimenting, and evaluating the research results from activity A1. It will provide lab settings for PlanetData core and partners to undertake specific experiments and assist them on how to use the systems.
Together these work packages provide the data, tools, and infrastructure to assist researchers and industry in the process of large‐scale data management. This activity will also improve the landscape of data sets available on the Web, by providing best practices and provisioning new vocabularies, data sets, and benchmarks.
- WP9–PlanetData Call1: Urban Games RTD
- WP12–PlanetData Call1: NorthPole RTD
- WP13–PlanetData Call1: ParkMe RTD
- WP15-PlanetData Call2: Linked Map, Requirement descriptions RTD
- WP16-PlanetData Call2: Linked Map, Linked data provisions RTD
- WP17-PlanetData Call2: Linked Map, Read-write Lined data WMS framework RTD
- WP18-PlanetData Call2: Linked Map, Platform integration&development RTD
- WP19-PlanetData Call2: Linked Map, Quality&crowdsourcing experiments RTD
- WP22-PlanetData Call2: Quadapt, Concept and Design RTD
- WP23-PlanetData Call2: Quadapt, Implementation RTD
- WP24-PlanetData Call2: Quadapt, Evaluation RTD
- WP26-PlanetData Call2: ETIHQ, Semantic Modeling RTD
- WP27-PlanetData Call2: ETIHQ, Data Publishing and Linking RTD
- WP28-PlanetData Call2: ETIHQ, System Development RTD
- WP31-PlanetData Call2: Meta Reasons Metatheory development RTD
- WP32-PlanetData Call2: Meta Reasons Prototype implementation RTD
- WP33-PlanetData Call2: Meta Reasons Prototype evaluation RTD
Activity 3: Impact
Activity leader: Lyndon Nixon
This activity aims to ensure the impact of the work conducted in PlanetData through two major initiatives, namely training, and dissemination and community building. Training students, researchers, and professionals ensures the sustainability of the large‐scale data management community and will lead to new research, technologies, and ultimately to new innovative products. While dissemination and community building will result in the creation of high quality integrated community around the topics of large‐scale data management:
- WP6 – Training: Before starting training activities is it crucial to ensure that high quality training materials are available. A flexible curriculum for the different training events will be developed as part of this work package, along with the accompanying learning materials. Ensuring easy access to these training materials across multiple channels will make it easy for learners to study and also enable self‐learning. This work package will develop an open training infrastructure using multiple channels, including slides, videos, serious games, podcasts, webinars, and tutorials. This infrastructure will provide a feedback mechanism for learners and also enable closer communication between trainers and learners. A third aspect covered by this work package is the PlanetData mentoring and career development. Professional experts in the network will act as mentors to researchers pursuing doctoral or postdoctoral research. In addition to mentoring, researchers in the network will have access to tailored career development planning and F2F‐meetings with fellow junior researcher and senior mentors.
- WP7 – Dissemination and Community Building: While training is essential to ensure transfer and sustainability of knowledge, high quality contributors to the network and long term scientific success of researchers across all partner institutions, this work packages focuses on building a integrated data management community far beyond the initial consortium. For this reason, work package WP7 is responsible for setting up the public Web site of the network and for coordinating the organization of dissemination events as active outreach activity (conferences, workshops, stakeholder forums, industry days). In collaboration with activities A1 and A2, this work package will issue challenges related to particular data sets, scientific questions, or application scenarios, which will be reflected in roadmaps forming the baseline for the PlanetData Programs. Moreover, this work package supports the consortium members in exploiting and particularly in contributing to standardization activities related to large‐scale data management. Of particular interest are standardization efforts of W3C in terms of linked data, annotation languages, and provenance modeling of data. Finally, work package WP7 coordinates the mobility program of PlanetData that aims to establish tighter links between researchers of the community.
- WP10–PlanetData Call1: Urban Games OTHER
- WP14–PlanetData Call1: ParkMe OTHER
- WP20-PlanetData Call2: Linked Map, Dissemination OTHER
- WP29-PlanetData Call2: ETIHQ, Dissemination OTHER
Activity 4: Management
Activity leader: Dieter Fensel
This activity will monitor the state of the project, from administrative, financial, and scientific perspectives, and will ensure that the project on a whole stays on track and delivers its results in a timely fashion, as per the work plan.
- WP8 – Project Management: This work package will implement the management procedures needed to execute the project on a day‐to‐day basis, ensuring timely execution of tasks and delivery of results. It is also responsible for putting in place and executing the quality assurance procedures for the project, which will ensure that results delivered by the project meet an acceptable quality level. Finally, it is through this work package that the project will communicate with the commission; specifically related to management reports, contract amendments, changes in the consortium etc. This work package also manages the execution of the two PlanetData Programs and ensures that the work plan of the project is successfully executed across the lifetime of the project, that the quality of the results produced are of a high standard, and that the PlanetData Program meets the high expectations in impact and quality.
- WP11–PlanetData Call1: Urban Games MGT
- WP21-PlanetData Call2: Linked Map, Management MGT
- WP25-PlanetData Call2: Quadapt, Management MGT
- WP30-PlanetData Call2: ETIHQ, Management MGT