Zeitschriftenartikel zum Thema „Flexible Metadata Format“

Fragmentation is the most important trends across all media platforms, with the aim of reorganizing and disseminating information in a more personalized way according to the "Long Tail Demand" theory. This paper proposes a fragments reorganizing plan, which considering sequential video, UGC video, graphic, text and social media information as the equivalent information source, utilizing a unified metadata format to describe media resources multi-dimensionally. The implementation of virtual segmenting for video allows a more flexible control of the granularity and achieves a rich content presentation and interactive behavior when combined with interactive scripts.

Multiparameter data with both spatial and temporal components are critical to advancing the state of environmental science. These data and data collected in the future are most useful when compared with each other and analyzed together, which is often inhibited by inconsistent data formats and a lack of structured documentation provided by researchers and (or) data repositories. In this paper we describe a linked table-based structure that encodes multiparameter spatiotemporal data and their documentation that is both flexible (able to store a wide variety of data sets) and usable (can easily be viewed, edited, and converted to plottable formats). The format is a collection of five tables (Data, Locations, Params, Data Sets, and Columns), on which restrictions are placed to ensure data are represented consistently from multiple sources. These tables can be stored in a variety of ways including spreadsheet files, comma-separated value (CSV) files, JavaScript object notation (JSON) files, databases, or objects in a software environment such as R or Python. A toolkit for users of R statistical software was also developed to facilitate converting data to and from the data format. We have used this format to combine data from multiple sources with minimal metadata loss and to effectively archive and communicate the results of spatiotemporal studies. We believe that this format and associated discussion of data and data storage will facilitate increased synergies between past, present, and future data sets in the environmental science community.

Abstract A prerequisite for systems biology is the integration and analysis of heterogeneous experimental data stored in hundreds of life-science databases and millions of scientific publications. Several standardised formats for the exchange of specific kinds of biological information exist. Such exchange languages facilitate the integration process; however they are not designed to transport integrated datasets. A format for exchanging integrated datasets needs to i) cover data from a broad range of application domains, ii) be flexible and extensible to combine many different complex data structures, iii) include metadata and semantic definitions, iv) include inferred information, v) identify the original data source for integrated entities and vi) transport large integrated datasets. Unfortunately, none of the exchange formats from the biological domain (e.g. BioPAX, MAGE-ML, PSI-MI, SBML) or the generic approaches (RDF, OWL) fulfil these requirements in a systematic way.We present OXL, a format for the exchange of integrated data sets, and detail how the aforementioned requirements are met within the OXL format. OXL is the native format within the data integration and text mining system ONDEX. Although OXL was developed with the ONDEX system in mind, it also has the potential to be used in several other biological and non-biological applications described in this paper.Availability: The OXL format is an integral part of the ONDEX system which is freely available under the GPL at http://ondex.sourceforge.net/. Sample files can be found at http://prdownloads.sourceforge.net/ondex/ and the XML Schema at http://ondex.svn.sf.net/viewvc/*checkout*/ondex/trunk/backend/data/xml/ondex.xsd.

The Intermediate Data Structure (IDS) encourages sharing historical life course data by storing data in a common format. To encompass the complexity of life histories, IDS relies on data structures that are unfamiliar to most social scientists. This article examines four features of IDS that make it flexible and expandable: the Entity-Attribute-Value model, the relational database model, embedded metadata, and the Chronicle file. I also consider IDS from the perspective of current discussions about sharing data across scientific domains. We can find parallels to IDS in other fields that may lead to future innovations.

Acquiring data on the occurrences of many types of difficult to identify objects are often still made by human observation, for example, in biodiversity and paleontologic research. Existing computer counting programs used to record such data have various limitations, including inflexibility and cost. We describe a new open-source program for this purpose—Raritas. Raritas is written in Python and can be run as a standalone app for recent versions of either MacOS or Windows, or from the command line as easily customized source code. The program explicitly supports a rare category count mode which makes it easier to collect quantitative data on rare categories, for example, rare species which are important in biodiversity surveys. Lastly, we describe the file format used by Raritas and propose it as a standard for storing geologic biodiversity data. ‘Stratigraphic occurrence data’ file format combines extensive sample metadata and a flexible structure for recording occurrence data of species or other categories in a series of samples.

This paper describes the construction of deeply annotated spoken dialogue corpora. To ensure a maximum of flexibility — in the degree of normalization, the types and formats of annotations, the possibilities for modifying and extending the corpus, or the use for research questions not originally anticipated — we propose a flexible multi-layer standoff architecture. We also take a closer look at the interoperability of tools and formats compatible with such an architecture. Free access to the corpus data through corpus queries, visualizations, and downloads — including documentation, metadata, and the original recordings — enables transparency, verifiability, and reproducibility of every step of interpretation throughout corpus construction and of any research findings obtained from this data.

Despite the widespread efforts to develop flexible formats such as PDB, mmCIF, CIF., to store and exchange data, the lack of best practice metadata pose major challenges. Readily adoptable methods with demonstrated usability across multiple solutions to create on-demand metadata are critical for the effective archive and exchange of data in a user-centric fashion. It is important that there exists a metadata-ecosystem where metadata of all structural and biological research evolve synchronously. Previously we described (Chem-BLAST, http://xpdb.nist.gov/chemblast/pdb.pl) a new `root' based concept used in language development (Latin & Sanskrit) to simplify the selection or creation of terms for metadata for millions of chemical structures from the PDB and the PubChem. Subsequently we extended it to text-based data on Cell-image-data (BMC, doi:10.1186/1471-2105-12-487). Here we describe further extension of this concept by creating roots and rules to define an ecosystem for composing new or modifying existing metadata for demonstrated inter-operability. A major focus of the rules is to ensure that the metadata terms are self-explaining (intuitive), highly-reused to describe many experiments and also that they are usable in a federated environment to construct new use-cases. We illustrate the use of this concept to compose semantic terminology for a wide range of disciplines ranging from material science to biology. Examples of the use of such metadata to create demonstrated solutions to describe data on cell-image data will also be presented. I will present ideas and examples to foster discussion on metadata architecture a) that is independent of formats and b) that is better suited for a federated environment c) that could be used readily to build components such as resource description framework (RDF) and Web services for Semantic web.

Purpose The purpose of this paper is to present a framework for the articulation of relationships between collection-level and item-level metadata as logical inference rules. The framework is intended to allow the systematic generation of relevant propagation rules and to enable the assessment of those rules for particular contexts and the translation of rules into algorithmic processes. Design/methodology/approach The framework was developed using first order predicate logic. Relationships between collection-level and item-level description are expressed as propagation rules – inference rules where the properties of one entity entail conclusions about another entity in virtue of a particular relationship those individuals bear to each other. Propagation rules for reasoning between the collection and item level are grouped together in the framework according to their logical form as determined by the nature of the propagation action and the attributes involved in the rule. Findings The primary findings are the analysis of relationships between collection-level and item-level metadata, and the framework of categories of propagation rules. In order to fully develop the framework, the paper includes an analysis of colloquial metadata records and the collection membership relation that provides a general method for the translation of metadata records into formal knowledge representation languages. Originality/value The method for formalizing metadata records described in the paper represents significant progress in the application of knowledge representation techniques to problems of metadata creation and management, providing a flexible technique for encoding colloquial metadata as a set of statements in first-order logic. The framework of rules for collection/item metadata relationships has a range of potential applications for the enhancement or metadata systems and vocabularies.

Abstract. We introduce tobac (Tracking and Object-Based Analysis of Clouds), a newly developed framework for tracking and analysing individual clouds in different types of datasets, such as cloud-resolving model simulations and geostationary satellite retrievals. The software has been designed to be used flexibly with any two- or three-dimensional time-varying input. The application of high-level data formats, such as Iris cubes or xarray arrays, for input and output allows for convenient use of metadata in the tracking analysis and visualisation. Comprehensive analysis routines are provided to derive properties like cloud lifetimes or statistics of cloud properties along with tools to visualise the results in a convenient way. The application of tobac is presented in two examples. We first track and analyse scattered deep convective cells based on maximum vertical velocity and the three-dimensional condensate mixing ratio field in cloud-resolving model simulations. We also investigate the performance of the tracking algorithm for different choices of time resolution of the model output. In the second application, we show how the framework can be used to effectively combine information from two different types of datasets by simultaneously tracking convective clouds in model simulations and in geostationary satellite images based on outgoing longwave radiation. The tobac framework provides a flexible new way to include the evolution of the characteristics of individual clouds in a range of important analyses like model intercomparison studies or model assessment based on observational data.

Welcome to the third issue of volume 43 of the IASSIST Quarterly (IQ 43:3, 2019). Yes, we are open! Open data is good. Just a click away. Downloadable 24/7 for everybody. An open government would make the decisionmakers’ data open to the public and the opposition. As an example, communal data on bicycle paths could be open, so more navigation apps would flourish and embed the information in maps, which could suggest more safe bicycle routes. However, as demonstrated by all three articles in this IQ issue, very often research data include information that requires restrictions concerning data access. The second paper states that data should be ‘as open as possible and as closed as needed’. This phrase originates from a European Union Horizon 2020 project called the Open Research Data Pilot, in ‘Guidelines on FAIR Data Management in Horizon 2020’ (July 2016). Some data need to be closed and not freely available. So once more it shows that a simple solution of total openness and one-size-fits-all is not possible. We have to deal with more complicated schemes depending on the content of data. Luckily, experienced people at data institutions are capable of producing adapted solutions. The first article ‘Restricting data’s use: A spectrum of concerns in need of flexible approaches’ describes how data producers have legitimate needs for restricting data access for users. This understanding is quite important as some users might have an automatic objection towards all restrictions on use of data. The authors Dharma Akmon and Susan Jekielek are at ICPSR at the University of Michigan. ICPSR has been the U.S. research archive since 1962, so they have much practice in long-term storage of digital information. From a short-term perspective you might think that their primary task is to get the data in use and thus would be opposed to any kind of access restrictions. However, both producers and custodians of data are very well aware of their responsibility for determining restrictions and access. The caveat concerns the potential harm through disclosure, often exemplified by personal data of identifiable individuals. The article explains how dissemination options differ in where data are accessed and what is required for access. If you are new to IASSIST, the article also gives an excellent short introduction to ICPSR and how this institution guards itself and its users against the hazards of data sharing. In the second article ‘Managing data in cross-institutional projects’, the reader gains insight into how FAIR data usage benefits a cross-institutional project. The starting point for the authors - Zaza Nadja Lee Hansen, Filip Kruse, and Jesper Boserup Thestrup – is the FAIR principles that data should be: findable, accessible, interoperable, and re-useable. The authors state that this implies that the data should be as open as possible. However, as expressed in the ICPSR article above, data should at the same time be as closed as needed. Within the EU, the mention of GDPR (General Data Protection Regulation) will always catch the attention of the economical responsible at any institution because data breaches can now be very severely fined. The authors share their experience with implementation of the FAIR principles with data from several cross-institutional projects. The key is to ensure that from the beginning there is agreement on following the specific guidelines, standards and formats throughout the project. The issues to agree on are, among other things, storage and sharing of data and metadata, responsibilities for updating data, and deciding which data format to use. The benefits of FAIR data usage are summarized, and the article also describes the cross-institutional projects. The authors work as a senior consultant/project manager at the Danish National Archives, senior advisor at The Royal Danish Library, and communications officer at The Royal Danish Library. The cross-institutional projects mentioned here stretch from Kierkegaard’s writings to wind energy. While this issue started by mentioning that ICPSR was founded in 1962, we end with a more recent addition to the archive world, established at Qatar University’s Social and Economic Survey Research Institute (SESRI) in 2017. The paper ‘Data archiving for dissemination within a Gulf nation’ addresses the experience of this new institution in an environment of cultural and political sensitivity. With a positive view you can regard the benefits as expanding. The start is that archive staff get experience concerning policies for data selection, restrictions, security and metadata. This generates benefits and expands to the broader group of research staff where awareness and improvements relate to issues like design, collection and documentation of studies. Furthermore, data sharing can be seen as expanding in the Middle East and North Africa region and generating a general improvement in the relevance and credibility of statistics generated in the region. Again, the FAIR principles of findable, accessible, interoperable, and re-useable are gaining momentum and being adopted by government offices and data collection agencies. In the article, the story of SESRI at Qatar University is described ahead of sections concerning data sharing culture and challenges as well as issues of staff recruitment, architecture and workflow. Many of the observations and considerations in the article will be of value to staff at both older and infant archives. The authors of the paper are the senior researcher and lead archivist at the archive of the Qatar University Brian W. Mandikiana, and Lois Timms-Ferrara and Marc Maynard – CEO and director of technology at Data Independence (Connecticut, USA). Submissions of papers for the IASSIST Quarterly are always very welcome. We welcome input from IASSIST conferences or other conferences and workshops, from local presentations or papers especially written for the IQ. When you are preparing such a presentation, give a thought to turning your one-time presentation into a lasting contribution. Doing that after the event also gives you the opportunity of improving your work after feedback. We encourage you to login or create an author login to https://www.iassistquarterly.com (our Open Journal System application). We permit authors 'deep links' into the IQ as well as deposition of the paper in your local repository. Chairing a conference session with the purpose of aggregating and integrating papers for a special issue IQ is also much appreciated as the information reaches many more people than the limited number of session participants and will be readily available on the IASSIST Quarterly website at https://www.iassistquarterly.com. Authors are very welcome to take a look at the instructions and layout: https://www.iassistquarterly.com/index.php/iassist/about/submissions Authors can also contact me directly via e-mail: kbr@sam.sdu.dk. Should you be interested in compiling a special issue for the IQ as guest editor(s) I will also be delighted to hear from you. Karsten Boye Rasmussen - September 2019

Welcome to the second issue of volume 42 of the IASSIST Quarterly (IQ 42:2, 2018). The IASSIST Quarterly has had several papers on many different aspects of the Data Documentation Initiative - for a long time better known by its acronym DDI, without any further explanation. DDI is a brand. The IASSIST Quarterly has also included special issues of collections of papers concerning DDI. Among staff at data archives and data libraries, as well as the users of these facilities, I think we can agree that it is the data that comes first. However, fundamental to all uses of data is the documentation describing the data, without which the data are useless. Therefore, it comes as no surprise that the IASSIST Quarterly is devoted partly to the presentation of papers related to documentation. The question of documentation or data resembles the question of the chicken or the egg. Don't mistake the keys for your car. The metadata and the data belong together and should not be separated. DDI now is a standard, but as with other standards it continues to evolve. The argument about why standards are good comes to mind: 'The nice thing about standards is that you have so many to choose from!'. DDI is the de facto standard for most social science data at data archives and university data libraries. The first paper demonstrates a way to tackle the heterogeneous character of the usage of the DDI. The approach is able to support collaborative questionnaire development as well as export in several formats including the metadata as DDI. The second paper shows how an institutionalized and more general metadata standard - in this case the Belgian Encoded Archival Description (EAD) - is supported by a developed crosswalk from DDI to EAD. However, IQ 42:2 is not a DDI special issue, and the third paper presents an open-source research data management platform called Dendro and a laboratory notebook called LabTablet without mentioning DDI. However, the paper certainly does mention metadata - it is the key to all data. The winner of the paper competition of the IASSIST 2017 conference is presented in this issue. 'Flexible DDI Storage' is authored by Oliver Hopt, Claus-Peter Klas, Alexander Mühlbauer, all affiliated with GESIS - the Leibniz-Institute for the Social Sciences in Germany. The authors argue that the current usage of DDI is heterogeneous and that this results in complex database models for each developed application. The paper shows a new binding of DDI to applications that works independently of most version changes and interpretative differences, thus avoiding continuous reimplementation. The work is based upon their developed DDI-FlatDB approach, which they showed at the European DDI conferences in 2015 and 2016, and which is also described in the paper. Furthermore, a web-based questionnaire editor and application supports large DDI structures and collaborative questionnaire development as well as production of structured metadata for survey institutes and data archives. The paper describes the questionnaire workflow from the start to the export of questionnaire, DDI XML, and SPSS. The development is continuing and it will be published as open source. The second paper is also focused on DDI, now in relation to a new data archive. 'Elaborating a Crosswalk Between Data Documentation Initiative (DDI) and Encoded Archival Description (EAD) for an Emerging Data Archive Service Provider' is by Benjamin Peuch who is a researcher at the State Archives of Belgium. It is expected that the future Belgian data archive will be part of the State Archives, and because DDI is the most widespread metadata standard in the social sciences, the State Archives have developed a DDI-to-EAD crosswalk in order to re-use their EAD infrastructure. The paper shows the conceptual differences between DDI and EAD - both XML based - and how these can be reconciled or avoided for the purpose of a data archive for the social sciences. The author also foresees a fruitful collaboration between traditional archivists and social scientists. The third paper is by a group of scholars connected to the Informatics Engineering Department of University of Porto and the INESC TEC in Portugal. Cristina Ribeiro, João Rocha da Silva, João Aguiar Castro, Ricardo Carvalho Amorim, João Correia Lopes, and Gabriel David are the authors of 'Research Data Management Tools and Workflows: Experimental Work at the University of Porto'. The authors start with the statement that 'Research datasets include all kinds of objects, from web pages to sensor data, and originate in every domain'. The task is to make these data visible, described, preserved, and searchable. The focus is on data preparation, dataset organization and metadata creation. Some groups were proposed a developed open-source research data management platform called Dendro and a laboratory notebook called LabTablet, while other groups that demanded a domain-specific approach had special developed models and applications. All development and metadata modelling have in sight the metadata dissemination. Submissions of papers for the IASSIST Quarterly are always very welcome. We welcome input from IASSIST conferences or other conferences and workshops, from local presentations or papers especially written for the IQ. When you are preparing such a presentation, give a thought to turning your one-time presentation into a lasting contribution. Doing that after the event also gives you the opportunity of improving your work after feedback. We encourage you to login or create an author login to https://www.iassistquarterly.com (our Open Journal System application). We permit authors 'deep links' into the IQ as well as deposition of the paper in your local repository. Chairing a conference session with the purpose of aggregating and integrating papers for a special issue IQ is also much appreciated as the information reaches many more people than the limited number of session participants and will be readily available on the IASSIST Quarterly website at https://www.iassistquarterly.com. Authors are very welcome to take a look at the instructions and layout: https://www.iassistquarterly.com/index.php/iassist/about/submissions Authors can also contact me directly via e-mail: kbr@sam.sdu.dk. Should you be interested in compiling a special issue for the IQ as guest editor(s) I will also be delighted to hear from you. Karsten Boye Rasmussen - June, 2018

Purpose – This paper aims to propose a service-oriented framework for performing content annotation and search, adapted to the task context. Media production workflows are becoming increasingly distributed and heterogeneous.The tasks of professionals in media production can be supported by automatic content analysis and search and retrieval services. Design/methodology/approach – The processes of the framework are derived top-down, starting from business goals and scenarios in audiovisual media production. Formal models of tasks in the production workflow are defined, and business processes are derived from the task models. A software framework enabling the orchestrated execution of these models is developed. Findings – This paper presents a framework that implements the proposed approach called Metadata Production Management Framework (MPMF). The authors show how a media production workflow for a real-world scenario is implemented using the MPMF. Research limitations/implications – The authors have demonstrated the feasibility of a model-based approach for media processing. In the reification step, there is still information that needs to be provided in addition to the task models to obtain executable processes. Future research should target the further automation of this process. Practical implications – By means of this approach, the implementation of the business process defines the workflow, whereas the services that are actually used are defined by the configuration. Thus, the processes are stable and, at the same time, the services can be managed very flexibly. If necessary, service implementations can also be completely replaced by others without changing the business process implementation. Originality/value – The authors introduce a model-based approach to media processing and define a reification process from business-driven task models to executable workflows. This enables a more task-oriented design of media processing workflows and adaptive use of automatic information extraction tools.

<p><strong>Abstract.</strong> While public participation in scientific achievements has a long history, the last decades have seen more attention and an impressive increase in the number of involved people. Citizen science, the term used for denoting such an attitude, is a very diverse practice, encompassing various forms, depths, and aims of collaboration between scientists and citizen researchers and a broad range of scientific disciplines. Different classifications of citizen science projects exist based on the degrees of influence and contributions of citizens. Haklay, Mazumdar, and Wardlaw (2018) distinguish the citizen science projects in three different classes:</p> <ol><li>Long-running citizen science, which are the traditional ones, the projects similar to those run in the past (Koboriet al., 2016; Bonney et al., 2009)</li> <li>Citizen cyberscience, strictly connected with the use of technologies (Grey, 2009) and which can be subclassified in:<ol><li>volunteer computing, where citizens offer the unused computing resources of their computers;</li><li>volunteer thinking, where citizens offer their cognitive abilities for performing tasks difficult for machines;</li><li>passive sensing, where citizens use the sensors integrated into mobile computing devices to carry outautomatic sensing tasks.</li></ol></li> <li>Community science, involving a more significant commitment of citizens also in designing and planning theproject activities in a more egalitarian (if not bottom-up) approach between scientists and citizen scientists(Jepson &amp; Ladle, 2015; Nascimento, Guimarães Pereira, &amp; Ghezzi, 2014; Breen, Dosemagen, Warren, &amp;Lippincott, 2015), which can be divided into:<ol><li>participatory sensing, where citizens use the sensors integrated into mobile computing devices to carry outsensing tasks;</li><li>Do It Yourself (DIY) science, which implies participants create their scientific tools and methodology to carry out their researches; </li><li>civic science, “which is explicitly linked to community goals and questions the state of things” (Haklay et al., 2018).</li></ol></li></ol> <p>The work presented here is of interest of community scientists which voluntarily offer their time for the development of scientific projects. Many software tools have been developed in order to simplify the insertion of data into structured forms and the aggregation and analysis of the obtained data. In recent years, the growing availability of feature-rich and low-cost smartphones have boosted the development of innovative solutions for data collection using portable devices. In this field, ODK (OpenDataKit) is widely known. It is an open-source suite of tools focused on simplicity of use, which includes an Android application for data collection. We used ODK for the first applications we developed.</p><p>One of the applications we developed using ODK is Via Regina (http://www.viaregina.eu/app). The application aims to support slow tourism in Via Regina, which is a road that overlooks the west coast of Lake Como in Northern Italy. Over the centuries, Via Regina has been a critical trade and pilgrim route in Europe. Moreover, from this road, a compact system of slow mobility paths departs, which span the mountainous region at the border between Italy and Switzerland. This region is rich in culture, regarding history, art, architecture, cuisine and people’s lifestyle. Considering collecting data on Via Regina and the paths around it would enable to rediscover and promote its culture while enjoying the territory, an Interreg project named “The Paths of Regina” started. The application developed within this project allows collecting data in predefined types: historical and cultural, morphological, touristic, and critical. Moreover, while reporting a point of interest (POI), the application asks the name, the position (through GPS or an interactive map), a picture, and optionally a video and an audio record of it (Antonovic et al., 2015).</p><p>However, since ODK application can be used only on Android devices, we developed a cross-platform application to collect similar data for the same purpose. It is available on Android, iOS, and web (http://viaregina3.como.polimi.it/app/). The application is developed using Apache Cordova, which is a mobile application development framework that enables running the application in multiple platforms. Leaflet library is used for web mapping. The data is stored in NoSQL PouchDB and CouchDB database, which enables both online and offline data collection. While reporting a POI, the application asks for its type, the user’s rating, a comment, and a picture of it either uploaded from device’s storage or taken using the camera of the mobile device. In addition to being cross-platform, it has the advantage of displaying and enabling the query of POIs reported, compared to the ODK-based version (Brovelli, Kilsedar, &amp; Zamboni, 2016). Regarding citizen science, besides the citizens using these two applications, Iubilantes, a voluntary cultural organization, has been involved in the project as community scientists. Iubilantes created slow mobility paths to walk in and around Via Regina, using their experience gained through studying ancient paths while protecting and enhancing their assets since 1996.</p><p>Mobile data collection can also be used to compensate for the lack of reference data available for land cover validation. We developed the Land Cover Collector (https://github.com/kilsedar/land-cover-collector) application for this purpose, which collects data using the nomenclature of GlobeLand30. GlobeLand30 is the first global land cover map at 30-meter resolution, provided by National Geomatics Center of China, available for 2000 and 2010 (Chen et al., 2015). There are ten land cover classes in the GlobeLand30 dataset, which are: artificial surface, bare land, cultivated land, forest, grassland, permanent snow and ice, shrubland, tundra, water body, and wetland. The collected data will be used for validating GlobeLand30 (Kilsedar, Bratic, Molinari, Minghini, &amp; Brovelli, 2018). The data is licensed under the Open Database License (ODbL) v1.0 and can be downloaded within the application in JSON format. The application is currently available in eight languages: English, Italian, Arabic, Russian, Chinese, Portuguese, French and Spanish. The technologies used are the same as the cross-platform Via Regina application. As a result, it is available on Android, iOS, and web (https://landcover.como.polimi.it/collector/); and it supports display and query of the collected data. While reporting a POI, the application asks the land cover class of it, the user’s degree of certainty on the correctness of the stated class, photos in north, east, south and west directions, and the user’s comment. Three hands-on workshops were given to teach this application and various ways to validate GlobeLand30: the first on September 1, 2018 at the World Bank in Dar es Salaam, Tanzania (in conjunction with the FOSS4G 2018 conference); the second on September 3, 2018 at the Regional Centre for Mapping of Resources for Development (RCMRD) in Nairobi, Kenya; and the third on October 1, 2018 at the Delft University of Technology in Delft, Netherlands. The workshops, run by representatives of the project's principal investigators &amp;ndash; Politecnico di Milano (Italy) and the National Geomatics Center of China (China) &amp;ndash; were attended by a total of 100 people with a background in GIS and remote sensing. (Brovelli et al., 2018).</p><p>Nonetheless, there are no widely adopted cross-platform open-source solutions or systems for on-site surveys that address the problem of information silos: isolated databases, where the information is not adequately shared but rather remains sequestered within each system, which is an obstacle to using data mining to make productive use of data of multiple systems.</p><p> PSAB (Participatory Sensing App Builder) is a platform that provides an open-source and easy to use cross-platform solution for the creation of custom smartphone applications as well as web applications and catalog service for publishing the data and make them available to everyone. It takes advantage of established standards (like XLSForm for defining the structure of the form and DublinCore for exposing metadata) as well as less known yet effective solutions, like WQ (https://wq.io), a framework developed for building reusable software platforms for citizen science. These technologies have been merged, together with other software like Django, PyCSW, PostgreSQL, in a single solution, in order to assist the user during the entire process, from the definition of the form structure, to the creation of an ad-hoc application and the publication of the collected data, inside a flexible and open-source platform.</p><p> Users registered to PSAB are allowed to create a new application by filling a web form where they can upload their XLSForm files and submit the metadata describing the data to be collected. A new application for collecting data on the field is generated and accessible via web and Android (while iOS requires a particular setup), ready to be used online and offline. The creator of each application is also the administrator of it, which means he/she is allowed to add or ban users and modify or remove existing data. Data is automatically synchronized between all the users participating in the project.</p><p> In the presentation we will show the applications we developed, starting from the ODK-based ones and coming to the PSAB application builder, and our experience related to their usage.</p>

AbstractGenes encoding synaptic proteins are highly associated with neuronal disorders many of which show clinical co-morbidity. We integrated 58 published synaptic proteomic datasets that describe over 8000 proteins and combined them with direct protein–protein interactions and functional metadata to build a network resource that reveals the shared and unique protein components that underpin multiple disorders. All the data are provided in a flexible and accessible format to encourage custom use.

Abstract Background In biological experiments, comprehensive experimental metadata tracking – which comprises experiment, reagent, and protocol annotation with controlled vocabulary from established ontologies – remains a challenge, especially when the experiment involves multiple laboratory scientists who execute different steps of the protocol. Here we describe Annot, a novel web application designed to provide a flexible solution for this task. Results Annot enforces the use of controlled vocabulary for sample and reagent annotation while enabling robust investigation, study, and protocol tracking. The cornerstone of Annot’s implementation is a json syntax-compatible file format, which can capture detailed metadata for all aspects of complex biological experiments. Data stored in this json file format can easily be ported into spreadsheet or data frame files that can be loaded into R (https://www.r-project.org/) or Pandas, Python’s data analysis library (https://pandas.pydata.org/). Annot is implemented in Python3 and utilizes the Django web framework, Postgresql, Nginx, and Debian. It is deployed via Docker and supports all major browsers. Conclusions Annot offers a robust solution to annotate samples, reagents, and experimental protocols for established assays where multiple laboratory scientists are involved. Further, it provides a framework to store and retrieve metadata for data analysis and integration, and therefore ensures that data generated in different experiments can be integrated and jointly analyzed. This type of solution to metadata tracking can enhance the utility of large-scale datasets, which we demonstrate here with a large-scale microenvironment microarray study.

Watch the VIDEO here. Presenter – Maria SöderholmResearch data management (RDM) is a complex and dynamic topic, and demands diverse expertise, skills and knowledge. The RDM expertise includes subtopics like collection/provision of data; storage and processing of data; long-term preservation requirements of the data; and funders’ demands and solutions to share, re-find and re-use research data. Usually the expertise related to these RDM subtopics is spread to several university units, both academic and administrative. Therefore, many tasks related to RDM, for example, day-to-day practices, the supply of services and the development work are best carried out in a network-based cooperation.In the presentation, we will introduce our RDM related partnership and networking of Aalto University. As a starting point, we introduce the internal service development working principles that our RDM network work is based on. However, the focus will be on describing our RDM working group and development activities.Aalto’s Research Data Management Programme forms the backbone for RDM work. It establishes seven separate action points for RDM activities: 1) open access publishing; 2) implementation of data management planning tool; 3) metadata catalogue for open data; 4) data publishing; 5) comprehensive repository service for storage, back-up and collaboration; 6) combining openness and innovation; and 7) RDM awareness building activities. The actors in the RDM network consist of Research and Innovation Services (leading the group), IT Services, and Learning Centre (previously Library).In the presentation, we will introduce the core actors in more detail, paying attention to the complementarity of the roles; and the activities and the aims, which steer the work. We also discuss the meaning and consequences of the network-based cooperation for the working group.First, the RDM group acts as a joint platform for comprehensive RDM information. Important means of data gathering are surveys and informal discussion with researcher. In the future, formal group discussions on RDM needs are hosted. The previous discussions with researchers have underlined the importance of arranging services for both disciplinary and data specific needs in addition to common university level service needs.Second, the group is a messenger of the RDM topics. Our task is to rise internal RDM awareness and disseminate national and international information and development trends in the university.The third and the most challenging aim is the RDM service planning and delivery. Our task is to identify the existing in-house services, to map the suitable services provided by national and international agents as well as to recognize the needs for new services. Our service portfolio covers both consultation/informational services and technical, hands-on services. However, many of our research data services are still in the planning or piloting stage, thus cooperation with researchers is essential.In our experience, the network-based collaboration model that foster individuals’ interconnectedness is crucial for surviving with the built-in dynamism of RDM. This model provides a non-hierarchical and flexible environment for actions to meet the increasing expectations for research data services we face from the funders, governments, and researchers.